Finding hidden growth opportunities in your product | Albert Cheng (Duolingo,

Albert ChengGrowth as the job is to connect users to the value of your product. Growth sometimes gets this reputation that it's just pure metrics hacking.

Lenny RachitskyYou've worked at three of the most successful consumer subscription products in the world. What do you think is the biggest missing piece that people don't get about building a successful consumer subscription product?

Albert ChengUser retention is gold for consumer subscription companies. If you don't retain your users, then a lot of the onus is on getting them to pay on day one.

Lenny RachitskyNoam Levinsky, he said that I need to ask you about the biggest monetization win that you found at Grammarly.

Albert ChengThe lived product experience for most of the free users was that Grammarly was just a product to fix your spelling and grammar because those were the free suggestions. What if we actually sampled a number of different paid suggestions and interspersed them to free users across their writing? All of a sudden, people were seeing Grammarly as a much more powerful tool than they were before.

Lenny RachitskyWhat's the most counterintuitive lesson you've learned about building teams?

Albert ChengI saw some of the highest performers just being people that had very high agency, had that clock speed, had that energy, but they didn't necessarily need to have deep experience on that matter. Sometimes experience could be a crutch, especially in this world where the grounds are shifting so fast with AI. A lot of your learned habits actually need to be intentionally discarded.

Lenny RachitskyToday my guest is Albert Cheng. Albert is known as one of the top consumer growth minds in the world. He led growth and monetization at three of the most successful and beloved consumer products in the world, Duolingo, Grammarly, and now Chess.com. Earlier in his career at YouTube, he worked on streaming and gaming features used by over 20 million people.

His unique approach to growth blends marketing, data, strategy, and product management, and in our conversation, we cover a lot of ground, including his explore and exploit framework to find growth opportunities. His biggest and most interesting growth wins at Duolingo, Grammarly and Chess.com, how he uses AI to accelerate his growth work, what he's come to realize about the power of brand and community in your growth work, his top experimentation, best practices, why his goal at every company is to run 1,000 experiments a year and so much more.
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Albert ChengThanks for having me, Lenny. Excited to be here.
That is super nice. Thank you, Jorge. I've learned so much from him. I'm the type of weird person that likes to wake up before their kids and pull up a bunch of browser tabs and look at experiments. So it was perfect that Jorge brought me into the growth world at Duolingo, learned a ton of best practices, and he's just a great guy. Thanks, Jorge.

Lenny RachitskyWe're already getting into these tactics. I love it. Let me just give a little framing on what I want to do with this conversation. What I want to try to do is to help people learn tools and mental models for finding growth opportunities for their own products and essentially learn the growth mentality that you bring into the companies and products that you work on.

What I want to start with is to give us a little insight into how you became what you became. There's an interesting pattern I found across a bunch of recent guests, which is many people were very good at piano when they were younger and were very serious piano players. For example, Head of ChatGPT, Nick Turley was almost going to become professional jazz pianist. You were very serious as a piano player earlier in your career. How did you go from pianist to one of the top growth minds in the world briefly?

Albert ChengWell, that's very flattering, but I appreciate it. Yeah, I grew up playing a lot of piano. My parents were immigrants from Taiwan and I was the oldest kid that they had, and so I definitely felt that strong encouragement, if you will, to learn a bunch of things, take them seriously, study hard, and so I did. And my parents, even though they weren't musically proficient, they had a deep love for classical music.

So I was the stereotypical baby that would listen to Mozart, I guess when I was sleeping type of thing. And I still vividly remember we had this upright Yamaha piano, and at the very top of the piano we had this countdown clock from 90 minutes. Literally every single day of my childhood, just practice really, really consistently.
At first, I really was irritated by that thing, but as I grew older, I started to appreciate music quite a bit more. But anyway, I think what really accelerated my interest and abilities in piano was I feel like I hit the lottery. I had perfect pitch, and so I was able to quickly understand whether I was playing the right stuff or the wrong stuff and just pick up music pretty rapidly.

Lenny RachitskyWhat does perfect pitch even mean? Does that mean which note is playing?

Albert ChengExactly.

Lenny RachitskyOkay.

Albert ChengExactly.

Lenny RachitskyWow.

Albert ChengSo I could listen to a song and then just a very, very clear understanding of which note I'm supposed to start with and if I'm playing something wrong. So it's very helpful.

Lenny RachitskyUnfair.

Albert ChengIt's unfair. Definitely. So anyway, yeah, I got quite good as a teenager in high school and even considered studying at a music conservatory. My intrinsic motivation for music wasn't necessarily as strong at that point, and so I decided to go to engineering school instead, but that would've been an incredibly different career. And to your original point around the relationship between music and growth, I didn't really reflect on this until recently.

I have a four-year-old and I'm starting to teach him how to bang on the keys a little bit, but a couple things stand out. One is that I think music and growth, they both rely on this just consistent repetition. You're constantly making mistakes. You have this super tight feedback loop. You have to get really resilient to just making mistakes all the time. And you know that the way of learning is through those mistakes. So that's a thing that I learned very early, and the second thing that occurred to me is that they both have this structural underpinning to them.
With growth, you have a growth model, you have metrics, you have experiments, you have channels, things like that. But you also need on a day-to-day basis to have creativity, you got to come up with interesting solutions or hypotheses to test. And the same is true on the music side. You have music theory of scales and stuff, but to create beautiful music, you need that passion, that emotion, that flow. So I think that's the beautiful combination between the two.

Lenny RachitskyFun fact, my wife bought me piano/singing lessons for Father's Day recently, and I've gotten really into this stuff. So I'm learning how to play very basic piano now and learning to identify notes and hit notes with my voice.

Albert ChengNice.

Lenny RachitskyWhat a weird new thing.

Albert ChengCould be your next act.

Lenny RachitskyIt could be. I could go the reverse, I could become a professional piano player. Oh man. No, it's so fun, so hard though. I'm just like, my fingers are like, how do you do four freaking keys at once? I'm just like "What is going on here?" Okay, so let's get into the meat of it. I want to talk about growth.

There's a very specific framework that as we were chatting that I think would be really helpful for people to hear and learn from you. You call it explore and exploit. I think there's a bunch of different ways to think about this. Talk about this framework and how that informs the way you think about growth.

Albert ChengYeah, I initially came up or heard with, heard about explore and exploit through my engineering partner at Grammarly, Nermal, and I think he actually had taken some reforged classes. So maybe the original inventor of it might be Brian Balfour, who I know has been on your pod. But anyway, it's a great concept.

The gist of it is that when you're in exploratory mode, think of it as finding the right mountain to climb. And then when you're in exploitation mode, it's like focusing your resources on climbing that mountain effectively. And certain companies, I think the warning is to basically spend too much of your time on one end of the spectrum. If you do too much exploration, you can have your team feel a little bit too scattershot, just trying a hundred different random ideas.
What's the through line? What's the strategy? How do you pattern match successes across them? And if you do too much in exploitation, which is often the MO of growth teams, it can lead to this saturation and stagnation where you're just locally maximizing a thing. And even though this principle of explore and exploit, it's typically thought of as a macro thing. I like to work with my teams more on the insight level. So I'll give you a concrete example.
So I work at chess.com and one of our priorities is to encourage chess players to improve, to learn and improve. So one of the PMs that we have, Dylan, he works on all the learning features. The most used learning feature in our product is called game review. So you play a game of chess, after the game is over, we have this virtual coach that teaches you about your worst moves, best moves, et cetera. And his job is to improve user engagement and retention.
And so he's in this exploratory phase trying to figure out how do I drive more of that type of activity? And what he observes is that 80% of people that review their games actually do so after a win. And that's really counterintuitive to when we initially built the feature. We thought that people would want to use it after losses or to see their mistakes such they could work on their mistakes. That turned out not to be the truth when it came to the human psychology and the actual data of it. And so we made some changes in the product experience.
When you lose a game now as opposed to surfacing your blunders and your horrible stuff that you did, we flip it on its head and so we show you your brilliant moves, your best moves, and we have coach say something encouraging, "Losing, just part of learning, keep it up." That type of thing. That change alone was pretty dramatic for us.
It grew game reviews by 25%, subscriptions by 20%, user retention by a lot as well. So that was fantastic, but the point is that it doesn't just stop there. You have to take that insight, share it broadly across the company. Now, adjacent product managers like the PM working on puzzles can now think about, "Okay, how do I audit these cold patterns in my product and think about making them more positive?"
I can change the success rating, I could tweak some copy, change the color of some buttons, and so you now can take this experiment win and expand it out 10X across your organization and that's the kind of exploitation phase of it. So when done right, you can oscillate between the two until you saturate out of exploitation mode and then you encourage the teams to brainstorm and get more creative again.

Lenny RachitskyAmazing. Okay, so there's a lot here to follow up on. One is the core piece of advice when you find something that works really well, find ways to build on that learning. One is here's an insight, it can apply to other parts of the product. "Hey teams, here's something we learned unexpected. Maybe this can help you. Also, just keep find more, run more experiments in the same zone." I imagine is a part of that.

Albert ChengYeah, exactly right. In my experience, the typical win rate, and I hate to use that term for experiments, is often something like 30 to 50%. Usually you're trying a bunch of things, a lot of hypotheses turn out not to be true, consumer products are very unpredictable like that, but when you do find a thing that breaks through the noise, and it could actually be a hugely losing experiment too, those are also super valuable.

Surfacing those across the company, the original PM running that experiment doesn't necessarily need to be the person that figures out what you should do for all the other parts of your product experience, but the onus is on them to clearly articulate what their hypothesis is, what they found such that then as a growth leader, I can encourage people to swarm around that and try a bunch of different ideas such that the success rate is up and the impact is up. So it's just oscillating back and forth between the two. That is the magic bullet.

Lenny RachitskyI think another takeaway here/something that I think about when I hear what you're saying is there's often a lot more wins in an area than people expect that you can continue to find wins and growth in something for a long time.

Albert ChengExactly right. Yes. At the end of the day, users, I think within a company sometimes you can have this siloed approach where you break apart the product experience in 50 different ways and distribute them across different teams, and you assume that users interact with each of the different features with a different mentality, but oftentimes that's actually not necessarily the case. And so sometimes, you can surface an insight that's more human psychology based that can resonate across the entire product experience. And so I think when you can find that, you can double down.

Lenny RachitskyPeople hearing this might feel like, "Okay, yes, find big wins and then find more." Is there something you find that helps you figure out when to explore versus when to exploit when you've exploited too far? Just like any heuristics or I don't know, ways of helping people guide them along this process of exploring and exploiting?

Albert ChengOne thing that I try to focus on at a company of our scale of a chess.com, right? We're running roughly 250 experiments a year. So we're not the highest in the industry, but we run a decent volume. And so when that happens, I invest in these experiment explorer tools and we can talk about AI as well as another way to uncover and pick out these nuggets of wisdom, but basically, these explorer tools can allow me to look across the spectrum of experiments that are going on.

Try to figure out if there are patterns between the hypotheses and the learnings that are happening. And if I'm starting to see more and more experiments that are not statistically significant, that may be a signal to me to say, "Okay, we might've tried to exploit a little bit too far. There might not be as much juice to squeeze. Hey guys, let's get back to the table and brainstorm and be a little bit more divergent with our thinking."

Lenny RachitskyWell, let me follow this thread on AI and how you're using AI to help you figure this out. That is very cool. Talk about that.

Albert ChengI think one of the latest things that we've been tinkering around with is this text to SQL capability. It's actually pretty powerful. We have this data request Slack channel where for the longest time, and this is still true today, people will toss in all sorts of just one-off questions. How many subscribers do we have in South Africa? Or how long did somebody play puzzles last month or something?

And these ad hoc questions, they often take a lot of human time to just go in and a data analyst needs to prioritize it and find time to go run the query. And yes, you can invest in self-serve tooling to improve at this, but also I found that AI is quite good at doing that first pass answer as well. And so we're working on training some of these Slack bots to essentially be the first party provider of a lot of these answers, which makes the company as a whole lot more data informed, I guess.
And I think what's also kind of interesting is that just human nature is that if you have a question that you feel like you might be a bit embarrassed to ask or you don't want to bother someone, you just don't ask the question. And so by the nature of having these tools, you get actually a pretty large explosion of questions being asked. And I think you see this in ChatGPT too, right? It's like just having a thing that you can converse with that you feel comfortable in makes a huge difference.

Lenny RachitskyOkay, this is extremely cool. So is this something you build basically it's a Slack bot that gives you the SQL query or does it actually do the analysis for you?

Albert ChengNo, it does the analysis. Yeah.

Lenny RachitskyWhoa, so cool. Okay. Is this something you guys are going to release or is this just like somebody, you guys should just build this at every company?

Albert ChengWe should. It's a good idea.

Lenny RachitskyOkay. Okay. Well, there's an episode where everyone in the comments is like, "Open source this." So we'll see if that happens again. That is very cool. Are there other examples of that kind of stuff that you've done or seen?

Albert ChengAn adjacent example is a lot of the product managers, we're tinkering around with all sorts of different prototyping tools right now. It's just like go from an idea to a representative solution. Today, there's a lot of humans involved in taking an idea, writing up a spec, doing a review, doing design, et cetera. I'm sure you've interviewed plenty of people that have talked about this specific problem.

And so for us, we've invested a bit in at least carving out the main screens of our product experience, things like our onboarding flow, our home screen, our chessboard as an example, and building essentially AI prototypes of those using tools like a V0 or a Lovable. And when you have those foundational pieces, you can then share them with the rest of the company and they can use that as a starting point and then they can try to put their ideas on top of that and then they become a lot more discussable and hopefully testable relatively soon.

Lenny RachitskyWhat's in your AI stack along those lines?

Albert ChengThe PMs are mostly using V0. The designers love Figmas, they're using Figma Make. The engineers are using a combination of tools right now. So Cursor, Cloud Code, GitHub, Copilot. Marketing teams use all sorts of tools for translation, subtitles, content adaptations, et cetera. Customers support uses Intercom then. So there's quite a lot of tools that are used across the company.

I would say though that something that is annoying to me is that we haven't yet figured out the bridging from the tinkering to the workflow quite as seamlessly as I would like. And so each sub-function, even though the common I guess wisdom now is that AI is going to strip away these functional titles. It is true that based on your experience, you may gravitate to using a type of tool more. And if that tool isn't as interoperable with some of the other tools that you need to pass down the chain to actually ship it into production, at least at our scale.
I think for smaller startups, sure, PMs should just go ship it, but for us, we are still doing some handoffs between functions. I expect that to change over time and we are investing in some of design system components and MCPs and stuff to make it a little bit easier. But yeah, it's an investment and it takes time to smooth things out.

Lenny RachitskyI want to come back to this topic of how things have changed and how you work as a product person, as a growth person across the companies you've been at. But first of all, I want to talk about another example of finding growth wins and monetization wins. Noam Levinsky, who is Chief Product Officer at Grammarly, you worked with him for a while while you were at Grammarly. He said that I need to ask you about the biggest monetization win that you found at Grammarly and how you discovered the opportunity.

Albert ChengI had the pleasure of working with Noam and his product team at Grammarly. Some context first for those that don't use Grammarly. So Grammarly is an AI-powered writing assistant. And so typically, people will use it as a Chrome extension or a downloadable desktop client. And basically what it does is it overlays your writing with a bunch of different-

Lenny RachitskyI use it. I'm a big fan. I use it-

Albert ChengCorrection, so you're a big fan.

Lenny Rachitsky... And it saves my life.

Albert ChengFantastic. Glad to hear that. Grammarly is a freemium business model, which means that over 90% of our users are on the free service and the rest of it pay for subscriptions essentially, right? And so one of the teams, they work on subscriber conversion, PM there is Kayla, that team is great and their job is to figure out the free to paid subscription path.

And so one of the realizations, one, is that we weren't actually tracking the events that well for the types of essentially suggestions that people were getting and how often were users seeing paywalls and stuff like that. That's kind of step number one. We have to put that instrumentation in. Step number two is that, "Hey, we noticed, actually first let me explain some of the logic."
So as a free user, you basically get these underlines across your writing and if you accept all of them, then you see the paywall and that encourages you to subscribe for more nuanced features. As a free user, the main things you get are spelling, grammar, they're basically correctness things. And as a paid user you get that, how do you improve your tone to be more empathetic? How do you improve your writing to be more clear?
How can you rewrite entire sentences, that type of thing. And so the observed behavior from all that tracking and data was that actually a very small percentage of our free users was deciding to accept all of their suggestions. They were more picking and choosing as they go, and I wonder if your experience is kind of similar too.

Lenny RachitskyDefinitely, yeah. I'm always like, "Wait, stop rewriting everything." Just like this part is wrong. I will fix it. Yeah, I'm very much a pick and choose.

Albert ChengThat's right.

Lenny RachitskyCorrection person.

Albert ChengAnd then the second thing, which is I think equally if not more interesting is that I was at this company during this generative AI transformation, which is obviously still going on. And quite frankly, both the company brand as well as the lived product experience for most of the free users was that Grammarly was just a product to fix your spelling and grammar because those were the free suggestions we were showing people.

And so we decided to flip that on its head entirely and we said, "Okay, what if we actually sampled a number of different paid suggestions and interspersed them to free users across their writing?" Such that they were intermingled and we would provide a limited taste of what the paid offering had to provide. And on the surface, even though it's rational, the concern is that if we give too much of this away, then will people want to subscribe?
And we found completely that was not the case all of a sudden, people were seeing Grammarly as a much more powerful tool than they were before and our upgrade rates nearly doubled just through this change. And so I think this is interesting, just modernization learning that especially if you work on a freemium product, try to have your free product be a reflection of everything that your product can offer you. Obviously to an extent there's some costs involved with some of the paid features and things like that, but it generally will pay for itself if you're able to put your best foot forward and go do that. So that really worked well for us there.

Lenny RachitskyI think this is what converted me to being a paid Grammarly subscriber. Wow, what a genius move. So essentially, it's here's a bunch of improvements, but you get three, I think max, and then it's like, "Okay, now you get upgrade."

Albert ChengIt's basically a reverse free trial but in real time while you're writing as opposed to a time-based one. So we adopted some patterns that are in the industry, but molded it to Grammarly's specific use case.

Lenny RachitskyRight. I was going to ask, so it's not like a full trial, it's like a capped trial where you get a certain number of things and then you run out and then they get refreshed. I think once a day or something like that is what I found.

Albert ChengYeah, you got it.

Lenny RachitskyYeah. Grammarly is the best/most devious at their upsells. I'm always just like, "God damn it, I'm so close to seeing an improvement, I just have to upgrade." And it's right there, it's right there where my mouse is.

Albert ChengYeah, well, I'm not proud of being devious, but.

Lenny RachitskyIn really getting me to buy the thing. Good job. What was it? Kayla? Okay, nice job Kayla. It's very effective. I love that. Okay, so in terms of the free trial, I don't know, is there anything there of just, there's always this question of freemium, give things away and then there's pro account, there's like trial versus time. Some features are limited. I don't know, do you have for consumer subscription products like here's the way to go?

Albert ChengYeah, I think first of all, why do freemium subscription in the first place is a common question that I've joined all these companies that are freemium subscription. What do I like about it I guess? Well one, I think it ties really nicely to mission orientation of a lot of these companies. It's often like you want to spread the product as wide as possible because that's why the founders built the thing, right?

You're trying to improve education with Duolingo or Grammarly or Chess.com, these are meant to be widespread products with a really wide value proposition that fits globally. And so obviously, the lowest friction to that is going to be a free product. So that alone is part of it. Another part of it is that a lot of these products primarily grow through word of mouth and especially if you can build network effects in the product, like Duolingo has a bunch of social features or with Grammarly, they have a bit of a B2C2B play as well.
So you see Grammarly being used by teams and by companies and whatnot, and even if users are on the free plan, they still provide quite a lot of value in making sure that Grammarly can be purchased by a coworker or by a team member or whatever. So I think these things are usually why I lean toward make sure that the core value proposition that you're providing users is free and is permanently free and then you layer on a sampling or a taste of some of the premium features that are on top of it. That's usually the sweet spot that I've seen.
As to the trials, reverse trials type of thing, I think it largely depends. I think if you have especially a B2B feature where you may have some lock-in, reverse trials can be super powerful. You just want to get people in there. You don't need to ask for their credit card because they're using your CRM or they're investing quite a lot of time in building out material and content. And so by the time that window drops, you actually feel, "Oh man, I probably should keep this and start paying." I think for a lot of consumer products it's a little bit harder for that to work. And so I've typically seen more just normal free trials be the norm.

Lenny RachitskyLet me follow this thread of just consumer subscription products. I feel like this is the category that every indie developer dreams of building a product in because it's easy to build. Cool, I'll build an app, I add a paywall, and then they realize this is a lot harder than I thought. From a perspective of distribution and CAx and growth like that, is that the biggest missing piece that people don't get about building a successful consumer subscription product?

Albert ChengYeah, user retention is gold for consumer subscription companies. If you don't retain your users, then a lot of the onus is on getting them to pay on day one, that's super hard. Then you're dealing with totally different business models where you're paying for users, you're trying to aggressively upsell them before they hit any habitual usage patterns with your product.

A lot of apps naturally do that because that's how they break the mold and get their first users to do it, but I don't know, I've been fortunate to join companies after that initial phase, but especially take Duolingo and Chess.com, these are organic word of mouth driven businesses and in both ways, they grew the market from a much smaller market and as opposed to it being a very competitive space where you're competing and taking market share from others and bidding for higher terms and stuff like that. So I don't know, there's something to that.

Lenny RachitskySo what I'm hearing here is you need to find a way to grow through word of mouth for this to have any chance of success and also retention needs to be very high. Do you have a heuristic of what retention needs to be for you to have a chance building a successful consumer subscription business?

Albert ChengI think consumer companies tend to track essentially two main types of user retention. There's more of the new user, one, D1, D7, et cetera. I think when you have your D one retention somewhere around the 30 or 40% mark, that's quite solid I think for a consumer app. If it's much lower than that, then sometimes I might question the intent of the user or the ability for that, you to I guess acquire just mathematically acquire enough users such that you can grow a big enough daily active user base.

Lenny RachitskyThat's surprisingly low.

Albert ChengYeah.

Lenny RachitskySo it feels achievable in theory.

Albert ChengIt's achievable. It's achievable in theory, but there are so many options out there in the market and people are feeling a lot of app and product bloat.

Lenny RachitskyAnd so just to be clear, you're saying 20 to 30% of people come back the next day?

Albert ChengYeah, 30 to 40.

Lenny Rachitsky30 to 40.

Albert Cheng40%. I think you're an okay place. I think even more importantly, and you mentioned Jorge to kick this off, but he wrote that very, very popular article about the growth model and how current user retention rate was the biggest thing for them. And I think especially if you have a product that has daily frequency, that's actually the retention that matters the most is that of your existing user base that has developed a habitual pattern, how sticky is your product? And it's that retention rate that really compounds and builds that daily habit.

So over time, especially when companies mature a little bit, you actually focus most of your energy on the existing user retention mechanics. You find that that's a much, much bigger lever. One exception is that Grammarly was a different type of product and that you install it and you don't proactively open it every day. So that was interesting to me because I assumed that you should always just focus on existing user retention, but for a product like Grammarly, it's actually the activation installation aha moment that's really, really critical and will carry the user for a very, very long time.

Lenny RachitskyThat makes sense. Yeah, the stats would show someone's a daily active user because they're typing things and that's not an accurate step for Grammarly. The other interesting trend I've noticed across successful consumer subscription products is they always start very scrappy and very cost-efficient and spend efficient because I think it's because it takes them a long time to find something that's working and they're surviving on that margin of retention to growth cost essentially.

Albert ChengYeah, that's right.
Yeah, and I think just to take Chess.com example, I think probably 80% of our daily or weekly active users, I'll check the numbers, but something like that would be a current user or an existing user and then a new and a reactivated or resurrected user. Those are actually about similar size for a company of our sale. So even though there's a lot of attention on that new user experience, it's actually pretty interesting that the components of your active user base are actually not heavily weighed in the new user set after you mature to a certain degree.

Lenny RachitskyCan you explain that a little bit more?

Albert ChengYes. So after some period of time, you stack up a lot of inactive users in your product and you also stack up sporadic users, people that may not have a daily habit, but they will use it once or twice a week or once or twice a month type of thing. And so eventually that math adds up where you have, let's say hundreds of millions of dormant users that are coming back and it's actually worth spending some time making sure that that resurrected, for lack of a better word, experience inside the product is really excellent and that you find novel ways to try to bring them back.

Duolingo as an example, they did a good job of using social notifications. And so if people would use contact sync or something, you might get a push notification that one of your best friends just started using Duolingo and that might encourage you to come back and resurrect into the product. And whether you resurrected in the product, it might be the case that your proficiency of the language you were learning, you were learning French three years ago, but now you for forgot most of it. And so when you open the app again, it encourages you to essentially replace yourself, do another placement test and put you in the right spot. And so some of these types of mechanics for a more mature company can lead to pretty good ROI guess is what I'm trying to say.

Lenny RachitskyGot it. Essentially, so many people have already tried in the past that to grow, you need to resurrect people that have been there. And so thinking through, it's almost like a user experience for resurrected users.

Albert ChengExactly.

Lenny RachitskyOkay. Let's zoom out a little bit. You've worked at three of the most successful consumer subscription products in the world. What is the difference between how these three operate? I think there's many ways to be successful. It feels like these companies are very different. What's the gist of each of these, how they operate?

Albert ChengWell, first of all, there's obviously a lot of similarities, but I'll just focus my answer on the differences. So I think Duolingo, what struck me most working there is they're very particular, they have an approach of product development that is infused across everyone in the company. And they actually wrote a playbook about this. It's called the Green Machine if you look it up. That was one of my most successful tweets ever really.

Lenny RachitskyI just tweeted something about Duolingo just released their playbook and I screenshotted the owl's butt and screened like a page and it was like 5,000 likes.

Albert ChengThat's hilarious.

Lenny RachitskyYeah. So yeah, keep going. Sorry.

Albert ChengBut yeah, the ethos of the company. They hire a lot of intelligent, energetic people out of college basically, and they give them a lot of amazing experimentation, tooling, and they care a lot about the clock speed of the company. So it's a lot of creativity, a lot of ideation.

The product experience of dual legal actually changes multiple times per day for each user, which is pretty shocking. And so I'd never worked in a place like that before, but it really struck me about how consistently the company operated and they had specs and processes for doing each of those steps in their product development cycle and they were really, really tight about it.

Lenny RachitskyOkay, so that's still lingo.

Albert ChengYeah, that's still lingo. Grammarly. This is an interesting company because they started as a paid product oriented at students. Then they expanded into more of a freemium model tailored to everyone gradually focusing more on the professional base. And then as they accumulate a lot more professionals, they realize, "Hey, there's patterns." We're seeing that a bunch of marketing teams or a bunch of sales teams or a bunch of customer support teams or whatever, particular functions within particular companies were really adopting Grammarly at scale.

And so they were able to then layer on much more of a managed enterprisey motion. And while I was there, I was focused on the consumer self-serve motion, but they weren't siloed. They were intermixed with each other. And so a big part of my job was not just to grow the self-serve revenue and self-serve active users, but it was also how do you uncover the right teams, the right functions, the right companies for demand gen and sales to go reach out to?
So that was a very interesting, it's a product-led sales work, and it's really fascinating thing for me to learn. And then on top of that, with all the transformation going on with generative AI, and even recently with them acquiring CODA and Superhuman and becoming more of a productivity suite, the company is just evolving pretty rapidly. It's a really exciting thing for me to be a part of and to see from the sidelines, but that just made it at its core of a different growth job than Duolingo for sure.

Lenny RachitskyEssentially a B2B business versus a very consumer business?

Albert ChengYeah, and a lot more meaningful strategic decisions as well.

Lenny RachitskyMm-hmm.

Albert ChengAnd then the core product team also, I'm used to in growth, laying out the entire user journey that a user go through acquisition, activation, engagement, so on and so forth. And typically, growth teams, if they're well-resourced, they can do enough to move each one of these various levers. And it's just a matter of the sequencing of them and what you want to prioritize first. But Grammarly was unique in that the core product experience itself was what drove repeated activity.

It's that I previously mentioned that current user retention thing, what most drives that is the frequency and the quality of the suggestions that you get every day. And so it was an interesting learning in that I staffed up a growth team, tried to work on this metric, and then I realized actually I'm just getting in the way. This is really a thing that the core product team most influences. Let me have a conversation with the core product leader and then shift that over to them. So yeah, just a super interesting experience.

Lenny RachitskyAnd then Chess.com.

Albert ChengThe thing that's most unique about chess.com is that they're super fanatical about chess.

Lenny RachitskyMakes sense.

Albert ChengCrazy. You shouldn't be surprised. Obviously the name of the company is like this, but they've always hired people from around the world. The company's always been globally remote. They just hire people that love chess. They play all day, they watch the streams. Our Slack is always blowing up with people's chess moves and games and whatnot. I think I want to say this a little bit delicately, like Duolingo, even though the product they're providing is around language learning, I think the original ethos of how to start the company was really around motivation.

The hardest thing to its habits, it's how do you build that daily habit? And I actually in many ways see language learning as their first vehicle. And what they have a superpower in is that, again, the motivation, the habits, et cetera. So that's Duolingo, and Grammarly actually similarly. People know them for the spelling and grammar corrections, but what's really unique about them is they're integrated across tons and tons and tons of applications.
There's not many products that work like that, that's really unique. And so now if you hear Shishir, their new CEO talk about the AI super highway and all that type of stuff, they can now use that technology to provide a lot more than just grammar writing. And so my point is just that Chess is about chess 100%. It's in the ethos. People are crazy passionate. That just means we're always dogfooding the product. There's just an amazing energy in the company to just use the product all the time, come up with ideas, and I love that environment. I think that's fun for me.

Lenny RachitskyThat is so cool. What I love about what you're saying is there's no right or wrong answer. All of these companies are killing it. I think Duolingo is worth like $10 billion, something like that, and keeps growing. I'll look it up in a second. And Grammarly is worth a ton, and then Chess.com is doing super well. So I think that's a really interesting takeaway here is you can succeed in a lot of different ways.

Albert ChengYeah.

Lenny RachitskyWhat's really cool about Duolingo, I was just thinking as you were talking, is yeah, it's just interesting that this very structured, methodical way of building is working so well because you could listen to that and be like, "Oh, I don't want to work." This is rigid way. But the fact that it is killing, it tells us this actually works really well. If you find something that works, lead into it.

Albert ChengYeah, that's right. Yeah, the structure is rigid, but the ideas are the farthest away from rigid as possible. You have seen their, I don't know, Superbowl commercials, they're memes, gamification, tactics. It's a super fun creative environment. So rigid is the farthest possible word to use, but what I just mean is they're consistent. They have for everything, and their product reviews are 10 or 15 minutes. It's just people go in and out. So it's just this kind of a surreal environment about how rapidly and consistently they work.

Lenny RachitskyAwesome. They're worth $12 billion, and they were much higher actually, not too long ago. They're coming down a little bit. So speaking of Duolingo, when people think Duolingo, they think of the brand and the owl and the success they had on TikTok and things like that. I'm curious to get your take on as a very growth-oriented person watching that work and your take on growth, experimentation data versus marketing, viral TikTok videos, mascots, things like that.

Albert ChengYeah, I used to think it was versus, but now I realize that they combine really well. It could be rocket fuel for your growth. Yeah, being a product person. I joined a lot of these companies literally on the home screen on my phone, and I like using them. And I consider myself someone that's not easily swayed by ads or TV commercials telling me what to buy.

So I always had an element of skepticism on the marketing side for much of my career. But then, yeah, you join a place like Duolingo and you see how Duo the owl has developed a personality through the push notifications and the product experience, and then seeing the marketing team leverage that personality in their TikTok and in their YouTube and all throughout social media and just feed into those memes. And then we would track back in the product experience, how did you hear about us?
And put all those channels in there. And some days, it would be like, holy, it's bringing in 20, 30% of our new users and any given day. So those two things really go hand in hand, and that feeling has only been reinforced by Chess.com over the last five years. The first 15-ish years of this company was really under the radar. 800 million people play chess around the world, but most of that is over the board.
Until recently, there wasn't actually that much online, but five years ago, everything changed. You had the pandemic, you had Queen's Gambit, you had a lot of YouTube and Twitch streamers, you had a bunch of kids playing it in school, et cetera. And so it's really the combination of those two things that make it take off. And it's like the growth experimentation is more the slow and steady or fast and steady, I should say, approach where you're just continually iterating, you're making the product experience better, but then every so often, there's a big wave that comes in. You can quadruple your registrations overnight and you'd be a fool not to take advantage of that.

Lenny RachitskyI was actually speaking at Chess.com and playing chess. I was at a coffee shop this weekend. There's a family, a dad and mom and a daughter ordering, and the dad's sitting at the table and he's just on his phone, just opened up Chess.com secretly and just plain while he is waiting. Oh man.

Albert ChengI will not admit or deny that I've done that before.

Lenny RachitskyBut if I can think of anything more wholesome, I can't. That's an amazing thing to be doing while you're just sitting.

Albert ChengMy 4-year-old can actually set up the pieces, which is pretty great. So he enjoys the game quite a bit.

Lenny RachitskyOh man, this 4-year-old already a pianist, playing chess.

Albert ChengThat's right.

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I want to follow that thread. As a growth person, imagine AI informs chess.com in a lot of ways, so there's kind of two buckets here. How is AI changing the product, say chess and other places you've worked? And then how is AI impacting your work as a growth person? So pick one or both buckets and share there.

Albert ChengYeah, I'll tackle them in sequence. I'll start with the chess one just because I have maybe a slightly unique take on that one. So chess and AI, they've been intertwined for almost a century. Some of the early computing pioneers, they just figured, "Yeah, chess is an interesting game. We can test machine intelligence and write some algorithms or not." And then fast-forward to 1997, and you had IBM, they had their DeepBlue application who actually beat the world champion back then, which was Garry Kasparov.

And that was a huge moment of shock and reckoning of like, "Oh man, is AI going to take over? Humans are, we're going to have jobs and all this stuff." And this is 30 years ago, and thankfully we're all still here and more people are playing chess than ever. And so the game of chess and chess.com specifically have learned how to augment, I guess the human playing experience with the power of chess engines, which are definitely a powerful form of AI. It's not LLMs to be clear, but there's engines like Stockfish these days that are just dramatically better than the top grand masters in the world.

Lenny RachitskyIs that where we're at? I remember when it beat humans and now it's just dramatically better.

Albert ChengIt's dramatically better.

Lenny RachitskyWow.

Albert ChengYeah, I think there's a rating system that compares relative skill level and an average chess player somewhere like a thousand, maybe 1,500 on the high end, a top grandmaster like Magnus Carlsen, it's like a 2,800 and then Stockfish and similar engines are like 3,600.

Lenny RachitskyWow.

Albert ChengAnd so to put that in comparison, yeah.

Lenny RachitskyAt least it's not 10,000 or a million. I don't even know if that's possible.

Albert ChengNo, it's not 10,000. But it's similar to if the chess engine was playing without a major piece like a rook or something, they would still be competitive against the best players.

Lenny RachitskyAnd this is the Elo score? Is that the term?

Albert ChengYeah, the Elo score, Elo rating.

Lenny RachitskyMagnus is what you said about 2,800, and then the Stockfish is would you say 3,600?

Albert ChengYeah, and really it's because computing power is so amazing and there's so many techniques for how to do deep evaluation on specific chess lines. They can calculate tens of millions per second. So it's not realistic for a human to compete against that. But yet, watching some of these chess engines played has opened up a lot of creativity, new strategies, new lines, new appreciation for the game. And our chess.com approach is that we can bring this technology for every user.

Even people that have never moved a piece before. I talked earlier about that game review product, that's exactly what this does. So behind the scenes, we're running chess engines to basically spit out evaluations for every move that you make. And then we translate that and make that approachable to the user using their native language and plain approachable style, and even with audio and things like that as well. And that part of it, the personality, the speech back to the user, that part is LLMs.
And so I guess my point is that, again, chess and AI have been intertwined forever, but for us, what's most important is that we keep the customer at the North Star of it. We're not just applying LLMs just because the new hot thing, you've got to apply the right technology for the right feature to provide value to the user. And so we try not to ever lose sight of that and let hype get us too carried away.

Lenny RachitskyIt's just really surprising. I think people would not have expected AI and cannot beat every human alive ever. And chess is at an all-time high. People want to keep playing and are playing more and more than ever played, not unexpected.

Albert ChengInterestingly, LLMs themselves are quite bad at playing chess. They hallucinate moves, they look at patterns. They're very good at pattern recognition, but not so good at going super, super, super deep on a specific chest thing. And if you've even tried to create or look at chessboard images on ChatGPT, a lot of them have the wrong number of squares. They're not set up properly, and so I don't want to be too dismissive.

I'm sure it's going to get much stronger at reasoning. And actually, Google recently sponsored a tournament where all the top LLMs played a tournament against each other. So that was pretty fun to watch. They're improving, but chess is specifically a game that having a trained deep, deep computing engine is just going to be much, much, much more powerful than LLMs.

Lenny RachitskyAnd not to go down this track too far, but AlphaZero famous for beating the Top Go player. Was that trained specifically for Go? Obviously not in LLM, but that was a Go specific model.

Albert ChengYeah. My understanding is that the one, that documentary is incredible, by the way. I don't know if you've watched AlphaGo, it's amazing how they took something so technically deep and made it so emotional and human. But I think that's the crux of how we feel, I guess, about AIs and the products that we build, actually. But to your point, my understanding is that the way AlphaZero is primarily trained is that it just plays a bunch of games against itself. And so through the neural network, it just gets smarter every time. And because it can have that repetition times a billion or a trillion, I don't know exactly what number, but it's going to get pretty damn good.

Lenny RachitskyOkay. Let's go back on track to where we were going. So this was how AI is impacting chess.com. How is AI changing just the work of a growth person?

Albert ChengI like to describe growth as the job is to connect users to the value of your product. And in order to do that, what I like to do is think about that user journey again, and essentially, staff teams that are oriented around each element of that user journey. And those teams have specific metric goals, they have roadmaps, et cetera. And then they go run against them.

So that's how it's structured. AI, I think can be applied to speed up some elements of that essentially experiment cycle that you get through. So one example is in product discovery. As opposed to core product, which tends to have longer timeframes, and you might do thorough user research or market research. It's more foundational, more for first principles, et cetera. Growth is a little bit less like that.
It's like you're running a lot of experiments and the output of any given experiment is the input to your next idea. And so historically, I don't even mean historically, but just a few months ago, we were operating in a, that's history, I suppose, but there would be a lot of manual writing of these analysis docs. You'd have to read them, you'd have to understand what insight you want to grab from them and then write another spec to translate that idea. That's still happening to some degree, but I think that's a spot where even tools like ChatGPT are super helpful.
You can just plug in like an analysis that another person wrote and just have it summarized for you and give you advice on ideas to go try. And so that ideation, that research cycle was much, much faster. I talked a little bit about prototyping also just becoming much, much faster than before. We have not yet gotten to the point where product managers themselves are actually shipping the code into production, but it's dramatically shortened the amount of time it takes to conceive of especially a bolder idea that you might have.
And so when I talked earlier about explore and exploit, a lot of the explore was harder to do, but now it's a little bit easier to do. You can take a broader concept and visualize it, and when you can visualize it, send it around the team, get people to click around it, that makes a world of difference. So those are just a couple examples that come to mind.

Lenny RachitskyAwesome. I want to go back to this phrase right at the beginning of this answer that you shared that I think is really helpful that you see growth as simply your job is to connect users to the value of your product.

Albert ChengYeah.

Lenny RachitskyCan you speak more to that? Because I think that's such a nice way clarifying what is growth's role?

Albert ChengYeah, it resonates deeply with me because I feel like growth sometimes gets this reputation I guess that it's just pure metrics hacking, like we're cold people that just are trying to move a particular metric up and we're going to do whatever it can to throw walls and pay walls and add friction in all these spots. And even though that could theoretically work at a micro level on a specific feature or a specific metric, I think what's most healthy for a company, and I want to work at durable companies is to think about the user holistically.

And when you take that framing of connecting users to the value of your product, that value can change for a user over time, and that also lines up really nicely to the journey. What someone that's not even a user yet needs to understand about the value proposition is super different than what a habitual user of three plus years might need. And so the teams working on them should think from that perspective and then from there, then ladder into specific problems to solve hypotheses, et cetera.

Lenny RachitskyFollowing that thread a little bit more, people listening to this are imagining, "How do I get better at experimentation? How do I run more experiments? How do we do this better?" What are two or three tips and best practices that you think people need to hear maybe are not totally aware of when they think about getting better at experimentation on our teams?

Albert ChengI think the first thing is just start somewhere. I just read this Atlassian state of product report and it was like 40% of product teams basically don't run experimentation at all. And there may be some good reasons for it. It could be philosophical or maybe you're more B2B oriented or whatever. So I get it, but I think for a lot of, especially if you work on a consumer product that has some degree of scale, some degree of frequency with your product, you can collect enough data.

And also I have found I can pattern match all day long. I've worked a lot of companies, right? But I'm wrong all the time. And I think consumer behavior can be very fickle and especially when you work at a company, you become a power user naturally. So sometimes you may forget what the actual user experience is for a brand new user, and so you leave a lot of opportunities on the table if you don't even try to experiment.
So I just encourage taking that first step, just run an A/B test, find a third-party tool or something that you can integrate quickly or even just work with your engineers to spin something up. Just get in the practice of crawl then walk then run type of thing.

Lenny RachitskyDo you have a favorite tool, by the way? Just to throw out? Is there a go-to tool for you?

Albert ChengWe used Statsig at Grammarly and I saw that they recently got acquired, so that was exciting news. Duolingo and Chess.com both have an in-house experimentation approach.

Lenny RachitskySweet.

Albert ChengPros and cons to either. Obviously Duolingo is an experimentation machine, and so it's been a huge accelerant to have our own thing specifically tailored to be excellent at that. But no, I typically don't encourage companies to build experimentation in-house from day one. At a certain scale it can make sense. And some of these companies, they were started 15 years ago when these tools weren't out. So it was just something they had to do.

Lenny RachitskySomething that you mentioned to me at Chess.com, your goal is to run a thousand experiments a year. You said you were at 250. Talk about just that as a North Star.

Albert ChengYeah, so part of having team members that are fanatical about Chess is that the company can get pretty far just building for themselves, building for the community, and not actually being very experimentation and data oriented. The problem with that is that you can have relatively lumpy growth. And so part of the excitement of me joining the company was to help smooth that out and bring in that experimentation mindset.

So prior to 2023, the company practically didn't experiment at all. Last year they did about 50, this year they're on pace for about 250. And then next year we have that ambitious target of a thousand. Did I make it up? Yes, absolutely, I made it up, but it's still a target and a thing for the teams to think about and a thousand experiments by itself. If you just did that but you didn't learn, you didn't make an impact, that's kind of a waste of time.
The whole point of setting a goal is that you can have conversations about what would need to be true to actually hit that goal, and so that leads to insights. Actually we need not just product management or engineering to be running these experiments. We can experiment with lifecycle marketing, changing copy of push notifications and emails. We can experiment with app store screenshots and keywords and stuff like that. We have all sorts of content marketing teams, et cetera. We could have engineering enable no code for specific screens.
Think about our home screen or our pricing screen where we might want to do a lot of just tests that are configurable without engineering support. We might want to just track our progress and look at it from time to time and make sure that we have the right observability around this. So anyway, that's the stuff that really matters as opposed to the hitting that goal itself. So don't tell the team, but I don't actually care that much if we actually hit a thousand, but I think if we get pretty close and we accomplish some of these things, we'll be in really good shape.

Lenny RachitskyOkay, we'll make sure none of them watch this. I think chess.com is in, this is just such a cool example of a culture shifting dramatically from zero experiments to sounds like two years later, a thousand, which is three a day. There's many teams running experiments in parallel, but that's a lot. What has helped you most shift that culture? Is it just the CEO being like, "This is the way we're going to go." What have you learned about helping shift to culture from No, we're not doing experiments to a thousand experiments a year.

Albert ChengYeah, definitely a lot of credit to the CEO and co-founders like Erik and Danny, they're amazing. It's not their intuitive way of thinking about growing companies, but their mental flexibility and encouragement to evolve and add this as a tool for the company has been awesome, and they've been on the front lines preaching product-led growth and experimentation just as much as I have.

So I'm glad that you brought that up because I think that is critically important for me, joining a company to not be at odds with the co-founders and the existing approach of the company. I think that's absolutely, absolutely critical. I think I started this podcast with the example of the game review and the positivity and how that was shared. I think those types of things are really what motivate people. They need to see this working in practice.

Lenny RachitskyWins.

Albert ChengYeah, you need wins, you got to celebrate them. People feel good about the learning. It's applied across the board. Who's not going to be energized by that, I think, right? So you can't just set goals in a vacuum and create it from top, right? People have to see it working and when it works, the metrics move and you learn faster and you ship faster, and that's a great environment to be part of.

Lenny RachitskyWhat was the first experiment you guys ran? Do you remember?

Albert ChengI don't know, before my time actually.

Lenny RachitskyOkay. Okay. Got it. So they're already going down this track before they brought you in?

Albert ChengThey had run some.

Lenny RachitskyOkay, sweet. Are there any other key lessons that you think people need to know to be successful running experiments at scale?

Albert ChengThe system matters just as much as any given experiment, probably even more, right? I think starting with a growth model, so you have an understanding of how your company grows in the first place and which channels you're going to leverage is critical. You need to make sure that you are instrumenting your product in and out. Otherwise, you're going to run experiments and have wonky results.

I won't name which company, but I was part of a company that had an in-house experimentation tool. It's about three months into the company, we're running some experiments and we realized that user retention was actually configured backwards. So all positive results were negative results.

Lenny RachitskyGeez.

Albert ChengSo that was kind of embarrassing and that will never happen again.

Lenny RachitskyYou just go through and undo all those experiments and just drive up retention.

Albert ChengIt's kind of weird. We're seeing people use the features a lot more. Why is user retention going negative? So I have plenty of horror stories around that type of stuff, but yeah.

Lenny RachitskyOh my God. On the flip side of horror stories, you've shared a bunch of cool examples of experiment wins. Is there another that comes to mind of one you're really proud of or that was really trajectory changing either at Duolingo or Grammarly or Chess?

Albert ChengSo I already shared one of Chess.com and one of Grammarly. I could talk a bit about Duolingo as well. Duolingo and you had Jackson on the podcast, right? Where you talked about the streaks.

Lenny RachitskyYes, talked about the streaks.

Albert ChengSo I also don't want to steal his thunder because I was going to think about that, but the amount of learning through commitment and putting streaks on a calendar and just getting people started as opposed to achieving some large milestone, that was huge. I think we did something interesting. We spun up a virality team and virality is this really amorphous thing to me.

I think it's really hard to generate virality in your product, but Duolingo is a product that is shared quite a bit. And so we invested actually in some time to essentially add screenshot tracking for a brief period of time in the app just so we could find out the hotspots of where users were doing screenshots. And you see this in other apps too, it's not necessarily some horrible thing, but we did this for some period of time and we were able to basically articulate and say, "Okay, streak milestones is the obvious one."
Really funny challenges that you get in the Duolingo experience is also super highly shared. Advancing in the top three of a leaderboard is another thing. Anyway, so you can find these different moments where that's the case. And then we staffed those moments with illustrators and animators and created these really delightful experiences around them, and that worked amazingly well.
So as opposed to going against I guess human intuition and trying to get them to share stuff that they otherwise wouldn't on the margins want to share, lean into it more, actually grab the moments where users are already organically screenshotting and make those much, much, much better. And you can 5X or 10X and drive a lot of growth that way too. So that's not so much an experiment, it's more a core product thing, but it just resonated with me that that was interesting.

Lenny RachitskyWell, it connects to your explore and exploit methodology. Just find or explore where things are happening and then try to exploit in a nice positive way.

Albert ChengYou got it.

Lenny RachitskySpeaking of that, you mentioned this with Duolingo is just very good at habit formation and motivation behavior. It feels like chess is good at this too. You've worked at both these companies. What have you learned about how to motivate people? How to create habits?

Albert ChengAgain, Duolingo would not have started without this insight from day one. They aim to focus on motivation and build a lot of these tactics. Jorge actually had this model of gamification patterns having essentially three pillars to it. You have the core loop, you have the metagame, and then you have the profile. And so we actually thought about it that way too, where your core loop is your lesson that you go through. You do a lesson, you get some rewards, you extend your streak, and then the next day you get a push notification.

It's the core loop of the product and making that really tight is super important because people need a habit to stick to. Then you need a metagame, which for Duolingo is the path, but it's also the leaderboard achievements. It's long-term things that you're going to strive to such that you have long-term, I guess, motivation to continue doing the thing. And then the profile is also critical because you build up a profile over time.
It's a reflection of your investment inside the product experience. And so when you nail those three things, you can end up with a long-term learning journey that can be quite successful. And then to flip over to the Chess.com side, what we see is that over 75% of our new users, they classify themselves as like, "I'm completely new to chess." Or, "I'm a beginner." And unfortunately, if you're new to chess and you're a beginner, you're not going to have that fun of a time playing live games, and we see this in the data. It's like less than a third of those users actually win their first game. And when you lose a game, user retention is 10% worse than when you win a game.

Lenny RachitskyThat's not so bad, but at scale, that's bad.

Albert ChengYeah, and it could be worse. That's true. And so typically what a lot of mobile games will do is they'll just create a super simplified version of the game. It's harder for us to do at chess, and so without changing the rules of that, I think that's, I don't know, it's just very eye-opening to me when you're trying to learn something, whether that be language learning or chess or whatever, usually those first steps are fraught with a lot of self-doubt and reinforcement that you're not good at the thing. And so it pays to be very intentional to craft experiences that guide the user around that.

Lenny RachitskyWell, I can't help but ask, is there anything that helped that along?

Albert ChengYeah, so something we're experimenting right now is just like purely if you say that you're new to chess, we're going to craft a more delightful learn how to play experience as opposed to dropping into a live game, that's an example. Another is hiding your ratings for the first five times such that you're not seeing your rating plummet. So there's a lot of tips and tricks you can do.

Lenny RachitskyI'm just imagining a little guide that's like, "Here's how you win."

Albert ChengYeah, or play against a coach, play against a friend, play against a bot. There's a bunch of different avenues you could take.

Lenny RachitskyWell, what I'd love is play against someone real and here's where you should move. Just like, "Hey, here's we're going to help you win."

Albert ChengLike a hint in real-time?

Lenny RachitskyYeah, yeah, yeah.

Albert ChengI don't want to be playing with you then.

Lenny RachitskyOkay. Let me ask you a couple more questions. One is just zooming out a little bit, what's the most counterintuitive lesson you've learned about building products or building teams across the many companies you've worked at?

Albert ChengYeah, I've talked a lot about products. So maybe I'll flip to the team side for a bit. I think the standard way to hire and build a team is you fill out a JD, it's got a whole bunch of different characteristics that you're looking for. You typically will find a short list of companies that are kind of similar to yours, and then you try to hire for that, right? I think that's the typical default path that a lot of companies take.

And I was really struck by my experience working at some smaller startups or take Duolingo as an example, where over and over and over, I saw some of the highest performers just being people that had very high agency, had that clock speed, had that energy. Yes, they cared about the mission, but they didn't necessarily need to have deep experience on that matter. And in fact, sometimes that experience could be a crutch in certain ways, especially in this world where the grounds are shifting so fast with AI, a lot of your learned habits actually need to be intentionally discarded.
You need to have a beginner's mind on this type of stuff. So I think this is more true than ever, looking for people that respond and move quickly and think just faster and move faster. I think the fastest speed of learning, those types of companies are the ones that I want to bet on. I think those will end up surviving and thriving.

Lenny RachitskySo just to double click on this idea of high agency is very trending these days of just higher high agency people. To unpack that a little bit, you mentioned a few of these traits, so let's just help people see what you see. So one is clock speed, just they think fast, they move fast, they learn fast. What else? What else do you look for that helps you see that there are high agency people?

Albert ChengYeah, a lot of it actually happens outside of the interview process interestingly. So a lot of it is the types of questions they asked, "Have they actually tried your product and gone deep into it?" A lot of it is, it's the references, it's the communication that they have to even set up your interview, it's the energy they bring into the conversation.

You can actually pick up a lot of soft signals on some of these traits over time. You've got to pick up on some of these patterns. I don't know that I'm perfect at it, but I've learned to balance those things quite a bit more than I did in the past when I would just purely read from my questions and my rubric and not care about anything else.

Lenny RachitskyYeah, there's like a vibes component to it. This is also support for the work trial way of interviewing versus just a talk interview where you have them actually work with you for a week or whatever.

Albert ChengThat's a great point.

Lenny RachitskyOkay. One other question I wanted to ask you. You've worked at a bunch of different sizes of companies from startup to Grammarly, I don't know, you call it a big company, bigger company. Duolingo, I don't know how big is Duolingo?

Albert ChengThere are about a thousand people.

Lenny RachitskyOkay, cool.

Albert ChengBut I worked at Google too to start my career.

Lenny RachitskyOh, right, okay. What have you learned about just the size of company that makes you happy? What have you learned about just helping other people that you talk to decide what size of company is good for them?

Albert ChengI definitely believe that everyone has a company stage that they shine best at. I've personally gone through this journey of big tech to tiny, tiny, tiny startup, then landed in the middle, which I consider my own goal lock zone. I talked earlier about what actually gives me personally a lot of energy is seeing across a company's efforts, but also the company being small enough that I can get into the details, I can work with the specific teams.

I can read experiment results, I can look at the pixels. And so I find that the balance of those two things tends to fit best with medium-sized companies, but that's me, right? I think at big companies like a Google, you're dealing with immense scale, which is interesting by itself. You learn a lot of best practices from your peers. They have all the tools and functions that you would possibly want to go learn from, but they can tend to move slower and it's harder to ship things and get them out the door, which eventually drove me nuts a little bit.
On the flip end of the spectrum, these tiny startups, they move incredibly fast, but I grew all my gray hair from those tiny startups because no one knows about your company, and so you're recruiting people one by one. You're trying to get users one by one. So yeah, you can learn fast and ship a lot of things, but if you're trying to make a big impact on the world, it can be actually pretty grueling to do so at really, really, really small startups.
Now, some of them do hyperscale and make it out, and obviously, I am not one to trash that because the path that I tried for quite a while. But for me, I really like the zone where I can contribute at scale, but also execute at a pace that's more on the daily and weekly scale as opposed to monthly and quarterly.

Lenny RachitskyAnd when you say medium, what size of company is that roughly?

Albert ChengYeah, so these companies that we've talked about in the podcast are about 500 to a thousand people. Typically, these companies who have been around let's say 10 to 20 years. They're durable, ideally profitable, have a good leadership team, but there's still a lot of dimensions to go figure out. A lot of them are in key inflection points, so they're certainly not stagnant. You need to find a place that's dynamic too.

Lenny RachitskyInteresting, 10 to 20 years old, I don't know if that's a, not many people would feel like that's where I want to be. I love that you found a number of companies like that that you enjoyed working at. The last question, and this is going to be taking us to a recurring segment on the podcast that I call Failed Corner.

People hear all these stories of all these experiments and all these companies that worked at, they're all killing it up into the right. In reality, you've touched on this, a lot of things don't work out great. So can you share a story when something went wrong, when you failed and what that taught you?

Albert ChengFirst of all, in the growth world, you're failing all the time. So I'm not going to pick a specific growth story because those don't actually hit my ego too much. But earlier in my career I did a lot of core product work. I worked for this startup called Chariot. I don't know if you ever lived in San Francisco, but.

Lenny RachitskyYes, it was like the bus super thing.

Albert ChengThe blue commuter shuttles, like 15-person shuttles, they would essentially drive from various neighborhoods into downtown San Francisco. It's a commuting use case across between the public bus system and an Uber and Lyft. So I was there for some time. I led product there and the core service was really loved by its users. It was reliable and fast and affordable enough, but we got pretty interested in this idea that maybe we can improve utilization, maybe we can make the service a little bit more innovative if we offer dynamic routes more similar to Uber and Lyft.

How could the drivers are driving these fixed routes? But if they have spare time, they can go out of their way, go pick up somebody at their house or something and keep going. So we tried this, we called the chair direct, really interesting attempt, but I learned a lot of lessons there because ultimately it didn't work out. One lesson is like this was kind of a solution searching for a problem. You never just purely want to chase A, it wouldn't it be nice if we did this as opposed to this is our user and this is the problem that we're solving, this is why it's going to delight them, et cetera, that's one.
Second is you got to consider, especially in these more marketplace type businesses, there's more than just one end user and we focus so much of our attention on the writer app without realizing, oh yeah, the drivers are carrying a lot of the brunt of this experience and our operations team is as well. And so when the drivers are confused or disgruntled, that can lead to a challenging overall experience for the product. So that's definitely another one.
And the third one is we did a lot of actually PR, prior to the service going out just to get the word out. And PR has its time in place, but I think doing it before you have validation that customers definitely want, the thing is quite risky and it can lead to a lot of sun cost once you get it out because you need to see it through, you want to see it succeed. So yeah, this is a decade ago, honestly, I had a great time at that company, but I still remember that vividly because it contained three or more key lessons that carried forward as I have built many products since then.

Lenny RachitskyYeah, it feels like you went to the complete other end run experiments of everything before you tell anyone about it.

Albert ChengThat's right.

Lenny RachitskyYeah, I remember the chariot bus showing up at the Airbnb office and people getting, I'm like, "What the hell is this?"

Albert ChengThat's right.

Lenny RachitskyVery cool. I didn't know you worked there. Albert, we've covered so much ground everything I was hoping we'd cover. Is there anything else that you wanted to cover, anything else you want to leave listeners with before we get to a very exciting lightning round?

Albert ChengNo, this is great. I hope it was useful for your listeners. I will say over the last few days, as I was prepping for this, I was honestly a little bit anxious about do I have enough deep independent frameworks that I need to come up with? But just being authentic to my actual experience at these companies, a lot of my lessons learned have been off of the backs of other people that have tried similar things and have succeeded or failed.

And I think what's important is that you have that your mental sponge. You can try a bunch of different things, you can absorb them and then put them in practice right away, discard the things that don't work and evolve them for yourself and for the company's needs. And so I don't know, I think that was just a realization that I had as I was thinking through this podcast, and I think that's partly why I haven't done too much public speaking.

Lenny RachitskyI know exactly what you mean. When I left Airbnb, I was just like, and that was the first time I ever took a break in my career of 30 years of just working straight in school. I was just like, what have I actually learned? I've never just sat down and thought about, here's the thing I've learned. And that led me to writing this medium post that did really well what I learned at Airbnb, and then that basically led to what I do now. So there's a lot of power and I love that this is the excuse to make you think through what have I learned concretely that I can share.

Albert ChengThat's right. Thank you for that.

Lenny RachitskyYeah, and so at the beginning of this podcast, before I started recording, I always like to ask guests, what is your goal? What do you want to get out of this conversation? And usually, it's like we're hiring. We want to make sure people know about our company or we want to get the users. And your answer is just, I just want to give back things I've learned, which I love.

Albert ChengThat's it.

Lenny RachitskyAnd you've done that. With that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready?

Albert ChengI'm ready.

Lenny RachitskyWhat are two or three books that you find yourself recommending most to other people?

Albert ChengYeah, so the truth of it is I have a, not just the four-year-old, but I also have a one-year-old. So most of the books that I'm reading these days are kids' books, trying to make them laugh in all.

Lenny RachitskyWait, any favorite kids books? Because I have three or two year olds already.

Albert ChengWell, you said that you started singing. There's a book called Snuggle Puppy that has a song in it that just makes my daughter crack up.

Lenny RachitskyOh my God.

Albert ChengThat is heartwarming for me. But no, a book that I recommended recently at work is Ogilvy on Advertising. Do you know this book?

Lenny RachitskyI don't know the book. I've seen these tenants of marketing or whatever.

Albert ChengYeah, it's interesting. So it's 40 years old, but it's just packed with a bunch of different practical examples about copy and creative that work in, these are old school ads, but he took a very experimentation-oriented approach to just try a lot of things.

I think in the book, it makes a good reminder that what ultimately matters is to compel your users to some action for him as buying a product, right? It's not about just creating clever ads or sexy creatives, it's to do things that compel that action. I think that's very true for many of our product and life cycle teams. And so I shared that around as an interesting recommendation.

Lenny RachitskyIs there a movie or TV show? Sorry, were you going to share another book?

Albert ChengYeah, actually.

Lenny RachitskyOh yes, please.

Albert ChengOur co-founder at Chess.com, his name's Danny Rensch, and he is quite well known in the chess circles. He's releasing a memoir called Dark Squares, and it is super fascinating. He grew up in an abusive cult and was a chess prodigy. And so it is just this unbelievable story and I'm about halfway through it, it's a reminder that sometimes the people that you work with, you don't realize how deep their pasts go, but this is something else, and I think it should be out by the time this podcast releases.

Lenny RachitskyAnd it's called Dark Squares?

Albert ChengDark Squares.

Lenny RachitskyWhich is a reference to the chess board and also I imagine the difficult past.

Albert ChengExactly.

Lenny RachitskyWow. How cool. Okay. Are there movie or TV shows you really enjoyed that you've recently watched?

Albert ChengThese days it's football season, so I'm consumed by all the hot takes of my favorite teams that I love and the teams I love to hate as well, so.

Lenny RachitskyWho's your team?

Albert ChengThe 49ers. I have season tickets and I go all the time. We had a rough season last year, so hoping to turn around.

Lenny RachitskyOkay, very cool. Okay. Is there a product you've recently discovered that you really love?

Albert ChengYeah, so last 20 years of my life roughly, I've moved around a lot, but I've always been within walking distance of a coffee shop. It's just like a ritual that I go and get coffee and it starts my day, right? Two years ago, I bought a house and for the first time ever in my life I'm like not buy a coffee shop, and I was so depressed about this for a little while.

So my favorite product is the bread bowl barista, and it just starts my day off. I like making horrible latte art with it, and I think it's just a reminder. I don't know. The products that most impact me, I guess are the ones that I use all the time, and it's a daily habit-

Lenny RachitskyAnd have the most caffeine.

Albert ChengThen the most caffeine. You got it.

Lenny RachitskyAmazing. Do you have a favorite life motto that you find yourself using in work or in life?

Albert ChengAs I was thinking about my piano stories, I also remember that my mom used to have a quote. She just said, "Nothing is more important than your reputation." And she used to say this, and I think the charitable understanding of this is that a lot of the small decisions that you make each day, how do you treat people? How do you show up? What's your character, et cetera. They can compound and they open doors for you in many surprising and amazing ways.

A lot of these companies that have actually joined have come through relatively light connections. And even just being on this podcast, I think I've seen a number of folks that I've worked with before beyond the show. And so I think doing the right thing, building a good reputation, they can carry you a long way. And the flip side of that is reputations are fragile too, right? So if you do the wrong thing, take a long time to repair that. So I don't know, it just stuck with me my entire life. I thought that was an interesting life motto.

Lenny RachitskyLast question. You work at Chess.com, how's your chess?

Albert ChengTerrible compared to serious, serious players, but quite compared to the casual ones, yeah. My yellow rating is about 1,800 for a rabbit games.

Lenny RachitskyIt sounds really-

Albert ChengAnd about 1,500 for blitz. Yeah, but I play many times every day.

Lenny RachitskyBlitz is like fast chess?

Albert ChengBlitz is like faster chess, three minute games. Rapid is more like a 10-minute game, which is still pretty fast.

Lenny RachitskyAnd you say you play multiple times a day? Do they make time? Is this like-

Albert ChengThey do.

Lenny RachitskyOkay. At Patagonia, there's a famous book, the founder wrote called Let My People Go Surfing, and the rule at Patagonia is you can go surfing if the waves are great. Is that how it works at Chess.com?

Albert ChengAbsolutely.

Lenny RachitskyOkay.

Albert ChengChess is always fun. So we play all the time and they even have chess coaches on staff.

Lenny RachitskyStaff, just like you can book to do?

Albert ChengYou can book. So I get bi-weekly lessons and it's helping me improve.

Lenny RachitskyWow. Okay. This is going to drive a lot of hiring for you guys. Saved it for the end. Albert, this was awesome. Thank you so much for doing this. Thanks so much for giving back and sharing all these stories. Two final questions, work and folks find you if they want to follow up on some of this stuff, and how can listeners be useful to you?

Albert ChengYeah, thanks for having me. This was great. You can find me on LinkedIn or Twitter. Not a super active poster, but I read it all the time. If there's something that I said today that resonates with you and you just want to get in touch, trade notes, feel free to reach out.

Lenny RachitskyAnd can they play with you on, can they find you on Chess.com to play?

Albert ChengThey can.

Lenny RachitskyOkay. Do you want to share your username or you don't want that?

Albert ChengI am happy to.

Lenny RachitskyNo. Okay.

Albert ChengI just mentioned that I'm a 49ers fan, so my username is Go9ers, so.

Lenny RachitskyWow.

Albert ChengI'm sure I'll get a lot of game requests now.

Lenny RachitskyHere we go. Here we go. 1,800. Okay. Albert, thank you so much for being here.

Albert ChengYeah, thank you so much.

Lenny RachitskyBye everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcast, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.

Albert ChengGrowth as the job is to connect users to the value of your product. Growth sometimes gets this reputation that it's just pure metrics hacking.

Lenny RachitskyYou've worked at three of the most successful consumer subscription products in the world. What do you think is the biggest missing piece that people don't get about building a successful consumer subscription product?

Albert ChengUser retention is gold for consumer subscription companies. If you don't retain your users, then a lot of the onus is on getting them to pay on day one.

Lenny RachitskyNoam Levinsky, he said that I need to ask you about the biggest monetization win that you found at Grammarly.

Albert ChengThe lived product experience for most of the free users was that Grammarly was just a product to fix your spelling and grammar because those were the free suggestions. What if we actually sampled a number of different paid suggestions and interspersed them to free users across their writing? All of a sudden, people were seeing Grammarly as a much more powerful tool than they were before.

Lenny RachitskyWhat's the most counterintuitive lesson you've learned about building teams?

Albert ChengI saw some of the highest performers just being people that had very high agency, had that clock speed, had that energy, but they didn't necessarily need to have deep experience on that matter. Sometimes experience could be a crutch, especially in this world where the grounds are shifting so fast with AI. A lot of your learned habits actually need to be intentionally discarded.

Lenny RachitskyToday my guest is Albert Cheng. Albert is known as one of the top consumer growth minds in the world. He led growth and monetization at three of the most successful and beloved consumer products in the world, Duolingo, Grammarly, and now Chess.com. Earlier in his career at YouTube, he worked on streaming and gaming features used by over 20 million people.

His unique approach to growth blends marketing, data, strategy, and product management, and in our conversation, we cover a lot of ground, including his explore and exploit framework to find growth opportunities. His biggest and most interesting growth wins at Duolingo, Grammarly and Chess.com, how he uses AI to accelerate his growth work, what he's come to realize about the power of brand and community in your growth work, his top experimentation, best practices, why his goal at every company is to run 1,000 experiments a year and so much more.
Head on over to lennysnewsletter.com and click Product Pass. With that, I bring you Albert Chain, my podcast guest tonight love talking about craft and taste and agency and product market fit. You know what we don't love talking about? SOC 2. That's where Vanta comes in. Vanta helps companies of all sizes get complying fast and stay that way with industry-leading AI automation and continuous monitoring. Whether you're a startup, your first SOC 2 or ISO 27001 or an enterprise managing vendor risk, Vanta's trust management platform makes it quicker, easier, and more scalable.
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It's flexible so it adapts to the way your team works and helps you build a roadmap that drives alignment, not questions. And because it's built on Jira, you can track ideas from strategy to delivery all in one place, less chasing, more time to think, learn and build the right thing. Get Jira Product Discovery for free at Atlassian.com/lenny, that's Atlassian.com/lenny. Albert, thank you so much for being here and welcome to the podcast.

Albert ChengThanks for having me, Lenny. Excited to be here.
That is super nice. Thank you, Jorge. I've learned so much from him. I'm the type of weird person that likes to wake up before their kids and pull up a bunch of browser tabs and look at experiments. So it was perfect that Jorge brought me into the growth world at Duolingo, learned a ton of best practices, and he's just a great guy. Thanks, Jorge.

Lenny RachitskyWe're already getting into these tactics. I love it. Let me just give a little framing on what I want to do with this conversation. What I want to try to do is to help people learn tools and mental models for finding growth opportunities for their own products and essentially learn the growth mentality that you bring into the companies and products that you work on.

What I want to start with is to give us a little insight into how you became what you became. There's an interesting pattern I found across a bunch of recent guests, which is many people were very good at piano when they were younger and were very serious piano players. For example, Head of ChatGPT, Nick Turley was almost going to become professional jazz pianist. You were very serious as a piano player earlier in your career. How did you go from pianist to one of the top growth minds in the world briefly?

Albert ChengWell, that's very flattering, but I appreciate it. Yeah, I grew up playing a lot of piano. My parents were immigrants from Taiwan and I was the oldest kid that they had, and so I definitely felt that strong encouragement, if you will, to learn a bunch of things, take them seriously, study hard, and so I did. And my parents, even though they weren't musically proficient, they had a deep love for classical music.

So I was the stereotypical baby that would listen to Mozart, I guess when I was sleeping type of thing. And I still vividly remember we had this upright Yamaha piano, and at the very top of the piano we had this countdown clock from 90 minutes. Literally every single day of my childhood, just practice really, really consistently.
At first, I really was irritated by that thing, but as I grew older, I started to appreciate music quite a bit more. But anyway, I think what really accelerated my interest and abilities in piano was I feel like I hit the lottery. I had perfect pitch, and so I was able to quickly understand whether I was playing the right stuff or the wrong stuff and just pick up music pretty rapidly.

Lenny RachitskyWhat does perfect pitch even mean? Does that mean which note is playing?

Albert ChengExactly.

Lenny RachitskyOkay.

Albert ChengExactly.

Lenny RachitskyWow.

Albert ChengSo I could listen to a song and then just a very, very clear understanding of which note I'm supposed to start with and if I'm playing something wrong. So it's very helpful.

Lenny RachitskyUnfair.

Albert ChengIt's unfair. Definitely. So anyway, yeah, I got quite good as a teenager in high school and even considered studying at a music conservatory. My intrinsic motivation for music wasn't necessarily as strong at that point, and so I decided to go to engineering school instead, but that would've been an incredibly different career. And to your original point around the relationship between music and growth, I didn't really reflect on this until recently.

I have a four-year-old and I'm starting to teach him how to bang on the keys a little bit, but a couple things stand out. One is that I think music and growth, they both rely on this just consistent repetition. You're constantly making mistakes. You have this super tight feedback loop. You have to get really resilient to just making mistakes all the time. And you know that the way of learning is through those mistakes. So that's a thing that I learned very early, and the second thing that occurred to me is that they both have this structural underpinning to them.
With growth, you have a growth model, you have metrics, you have experiments, you have channels, things like that. But you also need on a day-to-day basis to have creativity, you got to come up with interesting solutions or hypotheses to test. And the same is true on the music side. You have music theory of scales and stuff, but to create beautiful music, you need that passion, that emotion, that flow. So I think that's the beautiful combination between the two.

Lenny RachitskyFun fact, my wife bought me piano/singing lessons for Father's Day recently, and I've gotten really into this stuff. So I'm learning how to play very basic piano now and learning to identify notes and hit notes with my voice.

Albert ChengNice.

Lenny RachitskyWhat a weird new thing.

Albert ChengCould be your next act.

Lenny RachitskyIt could be. I could go the reverse, I could become a professional piano player. Oh man. No, it's so fun, so hard though. I'm just like, my fingers are like, how do you do four freaking keys at once? I'm just like "What is going on here?" Okay, so let's get into the meat of it. I want to talk about growth.

There's a very specific framework that as we were chatting that I think would be really helpful for people to hear and learn from you. You call it explore and exploit. I think there's a bunch of different ways to think about this. Talk about this framework and how that informs the way you think about growth.

Albert ChengYeah, I initially came up or heard with, heard about explore and exploit through my engineering partner at Grammarly, Nermal, and I think he actually had taken some reforged classes. So maybe the original inventor of it might be Brian Balfour, who I know has been on your pod. But anyway, it's a great concept.

The gist of it is that when you're in exploratory mode, think of it as finding the right mountain to climb. And then when you're in exploitation mode, it's like focusing your resources on climbing that mountain effectively. And certain companies, I think the warning is to basically spend too much of your time on one end of the spectrum. If you do too much exploration, you can have your team feel a little bit too scattershot, just trying a hundred different random ideas.
What's the through line? What's the strategy? How do you pattern match successes across them? And if you do too much in exploitation, which is often the MO of growth teams, it can lead to this saturation and stagnation where you're just locally maximizing a thing. And even though this principle of explore and exploit, it's typically thought of as a macro thing. I like to work with my teams more on the insight level. So I'll give you a concrete example.
So I work at chess.com and one of our priorities is to encourage chess players to improve, to learn and improve. So one of the PMs that we have, Dylan, he works on all the learning features. The most used learning feature in our product is called game review. So you play a game of chess, after the game is over, we have this virtual coach that teaches you about your worst moves, best moves, et cetera. And his job is to improve user engagement and retention.
And so he's in this exploratory phase trying to figure out how do I drive more of that type of activity? And what he observes is that 80% of people that review their games actually do so after a win. And that's really counterintuitive to when we initially built the feature. We thought that people would want to use it after losses or to see their mistakes such they could work on their mistakes. That turned out not to be the truth when it came to the human psychology and the actual data of it. And so we made some changes in the product experience.
When you lose a game now as opposed to surfacing your blunders and your horrible stuff that you did, we flip it on its head and so we show you your brilliant moves, your best moves, and we have coach say something encouraging, "Losing, just part of learning, keep it up." That type of thing. That change alone was pretty dramatic for us.
It grew game reviews by 25%, subscriptions by 20%, user retention by a lot as well. So that was fantastic, but the point is that it doesn't just stop there. You have to take that insight, share it broadly across the company. Now, adjacent product managers like the PM working on puzzles can now think about, "Okay, how do I audit these cold patterns in my product and think about making them more positive?"
I can change the success rating, I could tweak some copy, change the color of some buttons, and so you now can take this experiment win and expand it out 10X across your organization and that's the kind of exploitation phase of it. So when done right, you can oscillate between the two until you saturate out of exploitation mode and then you encourage the teams to brainstorm and get more creative again.

Lenny RachitskyAmazing. Okay, so there's a lot here to follow up on. One is the core piece of advice when you find something that works really well, find ways to build on that learning. One is here's an insight, it can apply to other parts of the product. "Hey teams, here's something we learned unexpected. Maybe this can help you. Also, just keep find more, run more experiments in the same zone." I imagine is a part of that.

Albert ChengYeah, exactly right. In my experience, the typical win rate, and I hate to use that term for experiments, is often something like 30 to 50%. Usually you're trying a bunch of things, a lot of hypotheses turn out not to be true, consumer products are very unpredictable like that, but when you do find a thing that breaks through the noise, and it could actually be a hugely losing experiment too, those are also super valuable.

Surfacing those across the company, the original PM running that experiment doesn't necessarily need to be the person that figures out what you should do for all the other parts of your product experience, but the onus is on them to clearly articulate what their hypothesis is, what they found such that then as a growth leader, I can encourage people to swarm around that and try a bunch of different ideas such that the success rate is up and the impact is up. So it's just oscillating back and forth between the two. That is the magic bullet.

Lenny RachitskyI think another takeaway here/something that I think about when I hear what you're saying is there's often a lot more wins in an area than people expect that you can continue to find wins and growth in something for a long time.

Albert ChengExactly right. Yes. At the end of the day, users, I think within a company sometimes you can have this siloed approach where you break apart the product experience in 50 different ways and distribute them across different teams, and you assume that users interact with each of the different features with a different mentality, but oftentimes that's actually not necessarily the case. And so sometimes, you can surface an insight that's more human psychology based that can resonate across the entire product experience. And so I think when you can find that, you can double down.

Lenny RachitskyPeople hearing this might feel like, "Okay, yes, find big wins and then find more." Is there something you find that helps you figure out when to explore versus when to exploit when you've exploited too far? Just like any heuristics or I don't know, ways of helping people guide them along this process of exploring and exploiting?

Albert ChengOne thing that I try to focus on at a company of our scale of a chess.com, right? We're running roughly 250 experiments a year. So we're not the highest in the industry, but we run a decent volume. And so when that happens, I invest in these experiment explorer tools and we can talk about AI as well as another way to uncover and pick out these nuggets of wisdom, but basically, these explorer tools can allow me to look across the spectrum of experiments that are going on.

Try to figure out if there are patterns between the hypotheses and the learnings that are happening. And if I'm starting to see more and more experiments that are not statistically significant, that may be a signal to me to say, "Okay, we might've tried to exploit a little bit too far. There might not be as much juice to squeeze. Hey guys, let's get back to the table and brainstorm and be a little bit more divergent with our thinking."

Lenny RachitskyWell, let me follow this thread on AI and how you're using AI to help you figure this out. That is very cool. Talk about that.

Albert ChengI think one of the latest things that we've been tinkering around with is this text to SQL capability. It's actually pretty powerful. We have this data request Slack channel where for the longest time, and this is still true today, people will toss in all sorts of just one-off questions. How many subscribers do we have in South Africa? Or how long did somebody play puzzles last month or something?

And these ad hoc questions, they often take a lot of human time to just go in and a data analyst needs to prioritize it and find time to go run the query. And yes, you can invest in self-serve tooling to improve at this, but also I found that AI is quite good at doing that first pass answer as well. And so we're working on training some of these Slack bots to essentially be the first party provider of a lot of these answers, which makes the company as a whole lot more data informed, I guess.
And I think what's also kind of interesting is that just human nature is that if you have a question that you feel like you might be a bit embarrassed to ask or you don't want to bother someone, you just don't ask the question. And so by the nature of having these tools, you get actually a pretty large explosion of questions being asked. And I think you see this in ChatGPT too, right? It's like just having a thing that you can converse with that you feel comfortable in makes a huge difference.

Lenny RachitskyOkay, this is extremely cool. So is this something you build basically it's a Slack bot that gives you the SQL query or does it actually do the analysis for you?

Albert ChengNo, it does the analysis. Yeah.

Lenny RachitskyWhoa, so cool. Okay. Is this something you guys are going to release or is this just like somebody, you guys should just build this at every company?

Albert ChengWe should. It's a good idea.

Lenny RachitskyOkay. Okay. Well, there's an episode where everyone in the comments is like, "Open source this." So we'll see if that happens again. That is very cool. Are there other examples of that kind of stuff that you've done or seen?

Albert ChengAn adjacent example is a lot of the product managers, we're tinkering around with all sorts of different prototyping tools right now. It's just like go from an idea to a representative solution. Today, there's a lot of humans involved in taking an idea, writing up a spec, doing a review, doing design, et cetera. I'm sure you've interviewed plenty of people that have talked about this specific problem.

And so for us, we've invested a bit in at least carving out the main screens of our product experience, things like our onboarding flow, our home screen, our chessboard as an example, and building essentially AI prototypes of those using tools like a V0 or a Lovable. And when you have those foundational pieces, you can then share them with the rest of the company and they can use that as a starting point and then they can try to put their ideas on top of that and then they become a lot more discussable and hopefully testable relatively soon.

Lenny RachitskyWhat's in your AI stack along those lines?

Albert ChengThe PMs are mostly using V0. The designers love Figmas, they're using Figma Make. The engineers are using a combination of tools right now. So Cursor, Cloud Code, GitHub, Copilot. Marketing teams use all sorts of tools for translation, subtitles, content adaptations, et cetera. Customers support uses Intercom then. So there's quite a lot of tools that are used across the company.

I would say though that something that is annoying to me is that we haven't yet figured out the bridging from the tinkering to the workflow quite as seamlessly as I would like. And so each sub-function, even though the common I guess wisdom now is that AI is going to strip away these functional titles. It is true that based on your experience, you may gravitate to using a type of tool more. And if that tool isn't as interoperable with some of the other tools that you need to pass down the chain to actually ship it into production, at least at our scale.
I think for smaller startups, sure, PMs should just go ship it, but for us, we are still doing some handoffs between functions. I expect that to change over time and we are investing in some of design system components and MCPs and stuff to make it a little bit easier. But yeah, it's an investment and it takes time to smooth things out.

Lenny RachitskyI want to come back to this topic of how things have changed and how you work as a product person, as a growth person across the companies you've been at. But first of all, I want to talk about another example of finding growth wins and monetization wins. Noam Levinsky, who is Chief Product Officer at Grammarly, you worked with him for a while while you were at Grammarly. He said that I need to ask you about the biggest monetization win that you found at Grammarly and how you discovered the opportunity.

Albert ChengI had the pleasure of working with Noam and his product team at Grammarly. Some context first for those that don't use Grammarly. So Grammarly is an AI-powered writing assistant. And so typically, people will use it as a Chrome extension or a downloadable desktop client. And basically what it does is it overlays your writing with a bunch of different-

Lenny RachitskyI use it. I'm a big fan. I use it-

Albert ChengCorrection, so you're a big fan.

Lenny Rachitsky... And it saves my life.

Albert ChengFantastic. Glad to hear that. Grammarly is a freemium business model, which means that over 90% of our users are on the free service and the rest of it pay for subscriptions essentially, right? And so one of the teams, they work on subscriber conversion, PM there is Kayla, that team is great and their job is to figure out the free to paid subscription path.

And so one of the realizations, one, is that we weren't actually tracking the events that well for the types of essentially suggestions that people were getting and how often were users seeing paywalls and stuff like that. That's kind of step number one. We have to put that instrumentation in. Step number two is that, "Hey, we noticed, actually first let me explain some of the logic."
So as a free user, you basically get these underlines across your writing and if you accept all of them, then you see the paywall and that encourages you to subscribe for more nuanced features. As a free user, the main things you get are spelling, grammar, they're basically correctness things. And as a paid user you get that, how do you improve your tone to be more empathetic? How do you improve your writing to be more clear?
How can you rewrite entire sentences, that type of thing. And so the observed behavior from all that tracking and data was that actually a very small percentage of our free users was deciding to accept all of their suggestions. They were more picking and choosing as they go, and I wonder if your experience is kind of similar too.

Lenny RachitskyDefinitely, yeah. I'm always like, "Wait, stop rewriting everything." Just like this part is wrong. I will fix it. Yeah, I'm very much a pick and choose.

Albert ChengThat's right.

Lenny RachitskyCorrection person.

Albert ChengAnd then the second thing, which is I think equally if not more interesting is that I was at this company during this generative AI transformation, which is obviously still going on. And quite frankly, both the company brand as well as the lived product experience for most of the free users was that Grammarly was just a product to fix your spelling and grammar because those were the free suggestions we were showing people.

And so we decided to flip that on its head entirely and we said, "Okay, what if we actually sampled a number of different paid suggestions and interspersed them to free users across their writing?" Such that they were intermingled and we would provide a limited taste of what the paid offering had to provide. And on the surface, even though it's rational, the concern is that if we give too much of this away, then will people want to subscribe?
And we found completely that was not the case all of a sudden, people were seeing Grammarly as a much more powerful tool than they were before and our upgrade rates nearly doubled just through this change. And so I think this is interesting, just modernization learning that especially if you work on a freemium product, try to have your free product be a reflection of everything that your product can offer you. Obviously to an extent there's some costs involved with some of the paid features and things like that, but it generally will pay for itself if you're able to put your best foot forward and go do that. So that really worked well for us there.

Lenny RachitskyI think this is what converted me to being a paid Grammarly subscriber. Wow, what a genius move. So essentially, it's here's a bunch of improvements, but you get three, I think max, and then it's like, "Okay, now you get upgrade."

Albert ChengIt's basically a reverse free trial but in real time while you're writing as opposed to a time-based one. So we adopted some patterns that are in the industry, but molded it to Grammarly's specific use case.

Lenny RachitskyRight. I was going to ask, so it's not like a full trial, it's like a capped trial where you get a certain number of things and then you run out and then they get refreshed. I think once a day or something like that is what I found.

Albert ChengYeah, you got it.

Lenny RachitskyYeah. Grammarly is the best/most devious at their upsells. I'm always just like, "God damn it, I'm so close to seeing an improvement, I just have to upgrade." And it's right there, it's right there where my mouse is.

Albert ChengYeah, well, I'm not proud of being devious, but.

Lenny RachitskyIn really getting me to buy the thing. Good job. What was it? Kayla? Okay, nice job Kayla. It's very effective. I love that. Okay, so in terms of the free trial, I don't know, is there anything there of just, there's always this question of freemium, give things away and then there's pro account, there's like trial versus time. Some features are limited. I don't know, do you have for consumer subscription products like here's the way to go?

Albert ChengYeah, I think first of all, why do freemium subscription in the first place is a common question that I've joined all these companies that are freemium subscription. What do I like about it I guess? Well one, I think it ties really nicely to mission orientation of a lot of these companies. It's often like you want to spread the product as wide as possible because that's why the founders built the thing, right?

You're trying to improve education with Duolingo or Grammarly or Chess.com, these are meant to be widespread products with a really wide value proposition that fits globally. And so obviously, the lowest friction to that is going to be a free product. So that alone is part of it. Another part of it is that a lot of these products primarily grow through word of mouth and especially if you can build network effects in the product, like Duolingo has a bunch of social features or with Grammarly, they have a bit of a B2C2B play as well.
So you see Grammarly being used by teams and by companies and whatnot, and even if users are on the free plan, they still provide quite a lot of value in making sure that Grammarly can be purchased by a coworker or by a team member or whatever. So I think these things are usually why I lean toward make sure that the core value proposition that you're providing users is free and is permanently free and then you layer on a sampling or a taste of some of the premium features that are on top of it. That's usually the sweet spot that I've seen.
As to the trials, reverse trials type of thing, I think it largely depends. I think if you have especially a B2B feature where you may have some lock-in, reverse trials can be super powerful. You just want to get people in there. You don't need to ask for their credit card because they're using your CRM or they're investing quite a lot of time in building out material and content. And so by the time that window drops, you actually feel, "Oh man, I probably should keep this and start paying." I think for a lot of consumer products it's a little bit harder for that to work. And so I've typically seen more just normal free trials be the norm.

Lenny RachitskyLet me follow this thread of just consumer subscription products. I feel like this is the category that every indie developer dreams of building a product in because it's easy to build. Cool, I'll build an app, I add a paywall, and then they realize this is a lot harder than I thought. From a perspective of distribution and CAx and growth like that, is that the biggest missing piece that people don't get about building a successful consumer subscription product?

Albert ChengYeah, user retention is gold for consumer subscription companies. If you don't retain your users, then a lot of the onus is on getting them to pay on day one, that's super hard. Then you're dealing with totally different business models where you're paying for users, you're trying to aggressively upsell them before they hit any habitual usage patterns with your product.

A lot of apps naturally do that because that's how they break the mold and get their first users to do it, but I don't know, I've been fortunate to join companies after that initial phase, but especially take Duolingo and Chess.com, these are organic word of mouth driven businesses and in both ways, they grew the market from a much smaller market and as opposed to it being a very competitive space where you're competing and taking market share from others and bidding for higher terms and stuff like that. So I don't know, there's something to that.

Lenny RachitskySo what I'm hearing here is you need to find a way to grow through word of mouth for this to have any chance of success and also retention needs to be very high. Do you have a heuristic of what retention needs to be for you to have a chance building a successful consumer subscription business?

Albert ChengI think consumer companies tend to track essentially two main types of user retention. There's more of the new user, one, D1, D7, et cetera. I think when you have your D one retention somewhere around the 30 or 40% mark, that's quite solid I think for a consumer app. If it's much lower than that, then sometimes I might question the intent of the user or the ability for that, you to I guess acquire just mathematically acquire enough users such that you can grow a big enough daily active user base.

Lenny RachitskyThat's surprisingly low.

Albert ChengYeah.

Lenny RachitskySo it feels achievable in theory.

Albert ChengIt's achievable. It's achievable in theory, but there are so many options out there in the market and people are feeling a lot of app and product bloat.

Lenny RachitskyAnd so just to be clear, you're saying 20 to 30% of people come back the next day?

Albert ChengYeah, 30 to 40.

Lenny Rachitsky30 to 40.

Albert Cheng40%. I think you're an okay place. I think even more importantly, and you mentioned Jorge to kick this off, but he wrote that very, very popular article about the growth model and how current user retention rate was the biggest thing for them. And I think especially if you have a product that has daily frequency, that's actually the retention that matters the most is that of your existing user base that has developed a habitual pattern, how sticky is your product? And it's that retention rate that really compounds and builds that daily habit.

So over time, especially when companies mature a little bit, you actually focus most of your energy on the existing user retention mechanics. You find that that's a much, much bigger lever. One exception is that Grammarly was a different type of product and that you install it and you don't proactively open it every day. So that was interesting to me because I assumed that you should always just focus on existing user retention, but for a product like Grammarly, it's actually the activation installation aha moment that's really, really critical and will carry the user for a very, very long time.

Lenny RachitskyThat makes sense. Yeah, the stats would show someone's a daily active user because they're typing things and that's not an accurate step for Grammarly. The other interesting trend I've noticed across successful consumer subscription products is they always start very scrappy and very cost-efficient and spend efficient because I think it's because it takes them a long time to find something that's working and they're surviving on that margin of retention to growth cost essentially.

Albert ChengYeah, that's right.
Yeah, and I think just to take Chess.com example, I think probably 80% of our daily or weekly active users, I'll check the numbers, but something like that would be a current user or an existing user and then a new and a reactivated or resurrected user. Those are actually about similar size for a company of our sale. So even though there's a lot of attention on that new user experience, it's actually pretty interesting that the components of your active user base are actually not heavily weighed in the new user set after you mature to a certain degree.

Lenny RachitskyCan you explain that a little bit more?

Albert ChengYes. So after some period of time, you stack up a lot of inactive users in your product and you also stack up sporadic users, people that may not have a daily habit, but they will use it once or twice a week or once or twice a month type of thing. And so eventually that math adds up where you have, let's say hundreds of millions of dormant users that are coming back and it's actually worth spending some time making sure that that resurrected, for lack of a better word, experience inside the product is really excellent and that you find novel ways to try to bring them back.

Duolingo as an example, they did a good job of using social notifications. And so if people would use contact sync or something, you might get a push notification that one of your best friends just started using Duolingo and that might encourage you to come back and resurrect into the product. And whether you resurrected in the product, it might be the case that your proficiency of the language you were learning, you were learning French three years ago, but now you for forgot most of it. And so when you open the app again, it encourages you to essentially replace yourself, do another placement test and put you in the right spot. And so some of these types of mechanics for a more mature company can lead to pretty good ROI guess is what I'm trying to say.

Lenny RachitskyGot it. Essentially, so many people have already tried in the past that to grow, you need to resurrect people that have been there. And so thinking through, it's almost like a user experience for resurrected users.

Albert ChengExactly.

Lenny RachitskyOkay. Let's zoom out a little bit. You've worked at three of the most successful consumer subscription products in the world. What is the difference between how these three operate? I think there's many ways to be successful. It feels like these companies are very different. What's the gist of each of these, how they operate?

Albert ChengWell, first of all, there's obviously a lot of similarities, but I'll just focus my answer on the differences. So I think Duolingo, what struck me most working there is they're very particular, they have an approach of product development that is infused across everyone in the company. And they actually wrote a playbook about this. It's called the Green Machine if you look it up. That was one of my most successful tweets ever really.

Lenny RachitskyI just tweeted something about Duolingo just released their playbook and I screenshotted the owl's butt and screened like a page and it was like 5,000 likes.

Albert ChengThat's hilarious.

Lenny RachitskyYeah. So yeah, keep going. Sorry.

Albert ChengBut yeah, the ethos of the company. They hire a lot of intelligent, energetic people out of college basically, and they give them a lot of amazing experimentation, tooling, and they care a lot about the clock speed of the company. So it's a lot of creativity, a lot of ideation.

The product experience of dual legal actually changes multiple times per day for each user, which is pretty shocking. And so I'd never worked in a place like that before, but it really struck me about how consistently the company operated and they had specs and processes for doing each of those steps in their product development cycle and they were really, really tight about it.

Lenny RachitskyOkay, so that's still lingo.

Albert ChengYeah, that's still lingo. Grammarly. This is an interesting company because they started as a paid product oriented at students. Then they expanded into more of a freemium model tailored to everyone gradually focusing more on the professional base. And then as they accumulate a lot more professionals, they realize, "Hey, there's patterns." We're seeing that a bunch of marketing teams or a bunch of sales teams or a bunch of customer support teams or whatever, particular functions within particular companies were really adopting Grammarly at scale.

And so they were able to then layer on much more of a managed enterprisey motion. And while I was there, I was focused on the consumer self-serve motion, but they weren't siloed. They were intermixed with each other. And so a big part of my job was not just to grow the self-serve revenue and self-serve active users, but it was also how do you uncover the right teams, the right functions, the right companies for demand gen and sales to go reach out to?
So that was a very interesting, it's a product-led sales work, and it's really fascinating thing for me to learn. And then on top of that, with all the transformation going on with generative AI, and even recently with them acquiring CODA and Superhuman and becoming more of a productivity suite, the company is just evolving pretty rapidly. It's a really exciting thing for me to be a part of and to see from the sidelines, but that just made it at its core of a different growth job than Duolingo for sure.

Lenny RachitskyEssentially a B2B business versus a very consumer business?

Albert ChengYeah, and a lot more meaningful strategic decisions as well.

Lenny RachitskyMm-hmm.

Albert ChengAnd then the core product team also, I'm used to in growth, laying out the entire user journey that a user go through acquisition, activation, engagement, so on and so forth. And typically, growth teams, if they're well-resourced, they can do enough to move each one of these various levers. And it's just a matter of the sequencing of them and what you want to prioritize first. But Grammarly was unique in that the core product experience itself was what drove repeated activity.

It's that I previously mentioned that current user retention thing, what most drives that is the frequency and the quality of the suggestions that you get every day. And so it was an interesting learning in that I staffed up a growth team, tried to work on this metric, and then I realized actually I'm just getting in the way. This is really a thing that the core product team most influences. Let me have a conversation with the core product leader and then shift that over to them. So yeah, just a super interesting experience.

Lenny RachitskyAnd then Chess.com.

Albert ChengThe thing that's most unique about chess.com is that they're super fanatical about chess.

Lenny RachitskyMakes sense.

Albert ChengCrazy. You shouldn't be surprised. Obviously the name of the company is like this, but they've always hired people from around the world. The company's always been globally remote. They just hire people that love chess. They play all day, they watch the streams. Our Slack is always blowing up with people's chess moves and games and whatnot. I think I want to say this a little bit delicately, like Duolingo, even though the product they're providing is around language learning, I think the original ethos of how to start the company was really around motivation.

The hardest thing to its habits, it's how do you build that daily habit? And I actually in many ways see language learning as their first vehicle. And what they have a superpower in is that, again, the motivation, the habits, et cetera. So that's Duolingo, and Grammarly actually similarly. People know them for the spelling and grammar corrections, but what's really unique about them is they're integrated across tons and tons and tons of applications.
There's not many products that work like that, that's really unique. And so now if you hear Shishir, their new CEO talk about the AI super highway and all that type of stuff, they can now use that technology to provide a lot more than just grammar writing. And so my point is just that Chess is about chess 100%. It's in the ethos. People are crazy passionate. That just means we're always dogfooding the product. There's just an amazing energy in the company to just use the product all the time, come up with ideas, and I love that environment. I think that's fun for me.

Lenny RachitskyThat is so cool. What I love about what you're saying is there's no right or wrong answer. All of these companies are killing it. I think Duolingo is worth like $10 billion, something like that, and keeps growing. I'll look it up in a second. And Grammarly is worth a ton, and then Chess.com is doing super well. So I think that's a really interesting takeaway here is you can succeed in a lot of different ways.

Albert ChengYeah.

Lenny RachitskyWhat's really cool about Duolingo, I was just thinking as you were talking, is yeah, it's just interesting that this very structured, methodical way of building is working so well because you could listen to that and be like, "Oh, I don't want to work." This is rigid way. But the fact that it is killing, it tells us this actually works really well. If you find something that works, lead into it.

Albert ChengYeah, that's right. Yeah, the structure is rigid, but the ideas are the farthest away from rigid as possible. You have seen their, I don't know, Superbowl commercials, they're memes, gamification, tactics. It's a super fun creative environment. So rigid is the farthest possible word to use, but what I just mean is they're consistent. They have for everything, and their product reviews are 10 or 15 minutes. It's just people go in and out. So it's just this kind of a surreal environment about how rapidly and consistently they work.

Lenny RachitskyAwesome. They're worth $12 billion, and they were much higher actually, not too long ago. They're coming down a little bit. So speaking of Duolingo, when people think Duolingo, they think of the brand and the owl and the success they had on TikTok and things like that. I'm curious to get your take on as a very growth-oriented person watching that work and your take on growth, experimentation data versus marketing, viral TikTok videos, mascots, things like that.

Albert ChengYeah, I used to think it was versus, but now I realize that they combine really well. It could be rocket fuel for your growth. Yeah, being a product person. I joined a lot of these companies literally on the home screen on my phone, and I like using them. And I consider myself someone that's not easily swayed by ads or TV commercials telling me what to buy.

So I always had an element of skepticism on the marketing side for much of my career. But then, yeah, you join a place like Duolingo and you see how Duo the owl has developed a personality through the push notifications and the product experience, and then seeing the marketing team leverage that personality in their TikTok and in their YouTube and all throughout social media and just feed into those memes. And then we would track back in the product experience, how did you hear about us?
And put all those channels in there. And some days, it would be like, holy, it's bringing in 20, 30% of our new users and any given day. So those two things really go hand in hand, and that feeling has only been reinforced by Chess.com over the last five years. The first 15-ish years of this company was really under the radar. 800 million people play chess around the world, but most of that is over the board.
Until recently, there wasn't actually that much online, but five years ago, everything changed. You had the pandemic, you had Queen's Gambit, you had a lot of YouTube and Twitch streamers, you had a bunch of kids playing it in school, et cetera. And so it's really the combination of those two things that make it take off. And it's like the growth experimentation is more the slow and steady or fast and steady, I should say, approach where you're just continually iterating, you're making the product experience better, but then every so often, there's a big wave that comes in. You can quadruple your registrations overnight and you'd be a fool not to take advantage of that.

Lenny RachitskyI was actually speaking at Chess.com and playing chess. I was at a coffee shop this weekend. There's a family, a dad and mom and a daughter ordering, and the dad's sitting at the table and he's just on his phone, just opened up Chess.com secretly and just plain while he is waiting. Oh man.

Albert ChengI will not admit or deny that I've done that before.

Lenny RachitskyBut if I can think of anything more wholesome, I can't. That's an amazing thing to be doing while you're just sitting.

Albert ChengMy 4-year-old can actually set up the pieces, which is pretty great. So he enjoys the game quite a bit.

Lenny RachitskyOh man, this 4-year-old already a pianist, playing chess.

Albert ChengThat's right.

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You don't have to be an AI master or to toggle yet another tool. The work you're already doing in Miro's canvas is the prompt. Help your teams get great work done with Miro. Check it out at miro.com/lenny, that's M-I-R-O.com/lenny. Okay, you talked about AI a little bit here and there.
I want to follow that thread. As a growth person, imagine AI informs chess.com in a lot of ways, so there's kind of two buckets here. How is AI changing the product, say chess and other places you've worked? And then how is AI impacting your work as a growth person? So pick one or both buckets and share there.

Albert ChengYeah, I'll tackle them in sequence. I'll start with the chess one just because I have maybe a slightly unique take on that one. So chess and AI, they've been intertwined for almost a century. Some of the early computing pioneers, they just figured, "Yeah, chess is an interesting game. We can test machine intelligence and write some algorithms or not." And then fast-forward to 1997, and you had IBM, they had their DeepBlue application who actually beat the world champion back then, which was Garry Kasparov.

And that was a huge moment of shock and reckoning of like, "Oh man, is AI going to take over? Humans are, we're going to have jobs and all this stuff." And this is 30 years ago, and thankfully we're all still here and more people are playing chess than ever. And so the game of chess and chess.com specifically have learned how to augment, I guess the human playing experience with the power of chess engines, which are definitely a powerful form of AI. It's not LLMs to be clear, but there's engines like Stockfish these days that are just dramatically better than the top grand masters in the world.

Lenny RachitskyIs that where we're at? I remember when it beat humans and now it's just dramatically better.

Albert ChengIt's dramatically better.

Lenny RachitskyWow.

Albert ChengYeah, I think there's a rating system that compares relative skill level and an average chess player somewhere like a thousand, maybe 1,500 on the high end, a top grandmaster like Magnus Carlsen, it's like a 2,800 and then Stockfish and similar engines are like 3,600.

Lenny RachitskyWow.

Albert ChengAnd so to put that in comparison, yeah.

Lenny RachitskyAt least it's not 10,000 or a million. I don't even know if that's possible.

Albert ChengNo, it's not 10,000. But it's similar to if the chess engine was playing without a major piece like a rook or something, they would still be competitive against the best players.

Lenny RachitskyAnd this is the Elo score? Is that the term?

Albert ChengYeah, the Elo score, Elo rating.

Lenny RachitskyMagnus is what you said about 2,800, and then the Stockfish is would you say 3,600?

Albert ChengYeah, and really it's because computing power is so amazing and there's so many techniques for how to do deep evaluation on specific chess lines. They can calculate tens of millions per second. So it's not realistic for a human to compete against that. But yet, watching some of these chess engines played has opened up a lot of creativity, new strategies, new lines, new appreciation for the game. And our chess.com approach is that we can bring this technology for every user.

Even people that have never moved a piece before. I talked earlier about that game review product, that's exactly what this does. So behind the scenes, we're running chess engines to basically spit out evaluations for every move that you make. And then we translate that and make that approachable to the user using their native language and plain approachable style, and even with audio and things like that as well. And that part of it, the personality, the speech back to the user, that part is LLMs.
And so I guess my point is that, again, chess and AI have been intertwined forever, but for us, what's most important is that we keep the customer at the North Star of it. We're not just applying LLMs just because the new hot thing, you've got to apply the right technology for the right feature to provide value to the user. And so we try not to ever lose sight of that and let hype get us too carried away.

Lenny RachitskyIt's just really surprising. I think people would not have expected AI and cannot beat every human alive ever. And chess is at an all-time high. People want to keep playing and are playing more and more than ever played, not unexpected.

Albert ChengInterestingly, LLMs themselves are quite bad at playing chess. They hallucinate moves, they look at patterns. They're very good at pattern recognition, but not so good at going super, super, super deep on a specific chest thing. And if you've even tried to create or look at chessboard images on ChatGPT, a lot of them have the wrong number of squares. They're not set up properly, and so I don't want to be too dismissive.

I'm sure it's going to get much stronger at reasoning. And actually, Google recently sponsored a tournament where all the top LLMs played a tournament against each other. So that was pretty fun to watch. They're improving, but chess is specifically a game that having a trained deep, deep computing engine is just going to be much, much, much more powerful than LLMs.

Lenny RachitskyAnd not to go down this track too far, but AlphaZero famous for beating the Top Go player. Was that trained specifically for Go? Obviously not in LLM, but that was a Go specific model.

Albert ChengYeah. My understanding is that the one, that documentary is incredible, by the way. I don't know if you've watched AlphaGo, it's amazing how they took something so technically deep and made it so emotional and human. But I think that's the crux of how we feel, I guess, about AIs and the products that we build, actually. But to your point, my understanding is that the way AlphaZero is primarily trained is that it just plays a bunch of games against itself. And so through the neural network, it just gets smarter every time. And because it can have that repetition times a billion or a trillion, I don't know exactly what number, but it's going to get pretty damn good.

Lenny RachitskyOkay. Let's go back on track to where we were going. So this was how AI is impacting chess.com. How is AI changing just the work of a growth person?

Albert ChengI like to describe growth as the job is to connect users to the value of your product. And in order to do that, what I like to do is think about that user journey again, and essentially, staff teams that are oriented around each element of that user journey. And those teams have specific metric goals, they have roadmaps, et cetera. And then they go run against them.

So that's how it's structured. AI, I think can be applied to speed up some elements of that essentially experiment cycle that you get through. So one example is in product discovery. As opposed to core product, which tends to have longer timeframes, and you might do thorough user research or market research. It's more foundational, more for first principles, et cetera. Growth is a little bit less like that.
It's like you're running a lot of experiments and the output of any given experiment is the input to your next idea. And so historically, I don't even mean historically, but just a few months ago, we were operating in a, that's history, I suppose, but there would be a lot of manual writing of these analysis docs. You'd have to read them, you'd have to understand what insight you want to grab from them and then write another spec to translate that idea. That's still happening to some degree, but I think that's a spot where even tools like ChatGPT are super helpful.
You can just plug in like an analysis that another person wrote and just have it summarized for you and give you advice on ideas to go try. And so that ideation, that research cycle was much, much faster. I talked a little bit about prototyping also just becoming much, much faster than before. We have not yet gotten to the point where product managers themselves are actually shipping the code into production, but it's dramatically shortened the amount of time it takes to conceive of especially a bolder idea that you might have.
And so when I talked earlier about explore and exploit, a lot of the explore was harder to do, but now it's a little bit easier to do. You can take a broader concept and visualize it, and when you can visualize it, send it around the team, get people to click around it, that makes a world of difference. So those are just a couple examples that come to mind.

Lenny RachitskyAwesome. I want to go back to this phrase right at the beginning of this answer that you shared that I think is really helpful that you see growth as simply your job is to connect users to the value of your product.

Albert ChengYeah.

Lenny RachitskyCan you speak more to that? Because I think that's such a nice way clarifying what is growth's role?

Albert ChengYeah, it resonates deeply with me because I feel like growth sometimes gets this reputation I guess that it's just pure metrics hacking, like we're cold people that just are trying to move a particular metric up and we're going to do whatever it can to throw walls and pay walls and add friction in all these spots. And even though that could theoretically work at a micro level on a specific feature or a specific metric, I think what's most healthy for a company, and I want to work at durable companies is to think about the user holistically.

And when you take that framing of connecting users to the value of your product, that value can change for a user over time, and that also lines up really nicely to the journey. What someone that's not even a user yet needs to understand about the value proposition is super different than what a habitual user of three plus years might need. And so the teams working on them should think from that perspective and then from there, then ladder into specific problems to solve hypotheses, et cetera.

Lenny RachitskyFollowing that thread a little bit more, people listening to this are imagining, "How do I get better at experimentation? How do I run more experiments? How do we do this better?" What are two or three tips and best practices that you think people need to hear maybe are not totally aware of when they think about getting better at experimentation on our teams?

Albert ChengI think the first thing is just start somewhere. I just read this Atlassian state of product report and it was like 40% of product teams basically don't run experimentation at all. And there may be some good reasons for it. It could be philosophical or maybe you're more B2B oriented or whatever. So I get it, but I think for a lot of, especially if you work on a consumer product that has some degree of scale, some degree of frequency with your product, you can collect enough data.

And also I have found I can pattern match all day long. I've worked a lot of companies, right? But I'm wrong all the time. And I think consumer behavior can be very fickle and especially when you work at a company, you become a power user naturally. So sometimes you may forget what the actual user experience is for a brand new user, and so you leave a lot of opportunities on the table if you don't even try to experiment.
So I just encourage taking that first step, just run an A/B test, find a third-party tool or something that you can integrate quickly or even just work with your engineers to spin something up. Just get in the practice of crawl then walk then run type of thing.

Lenny RachitskyDo you have a favorite tool, by the way? Just to throw out? Is there a go-to tool for you?

Albert ChengWe used Statsig at Grammarly and I saw that they recently got acquired, so that was exciting news. Duolingo and Chess.com both have an in-house experimentation approach.

Lenny RachitskySweet.

Albert ChengPros and cons to either. Obviously Duolingo is an experimentation machine, and so it's been a huge accelerant to have our own thing specifically tailored to be excellent at that. But no, I typically don't encourage companies to build experimentation in-house from day one. At a certain scale it can make sense. And some of these companies, they were started 15 years ago when these tools weren't out. So it was just something they had to do.

Lenny RachitskySomething that you mentioned to me at Chess.com, your goal is to run a thousand experiments a year. You said you were at 250. Talk about just that as a North Star.

Albert ChengYeah, so part of having team members that are fanatical about Chess is that the company can get pretty far just building for themselves, building for the community, and not actually being very experimentation and data oriented. The problem with that is that you can have relatively lumpy growth. And so part of the excitement of me joining the company was to help smooth that out and bring in that experimentation mindset.

So prior to 2023, the company practically didn't experiment at all. Last year they did about 50, this year they're on pace for about 250. And then next year we have that ambitious target of a thousand. Did I make it up? Yes, absolutely, I made it up, but it's still a target and a thing for the teams to think about and a thousand experiments by itself. If you just did that but you didn't learn, you didn't make an impact, that's kind of a waste of time.
The whole point of setting a goal is that you can have conversations about what would need to be true to actually hit that goal, and so that leads to insights. Actually we need not just product management or engineering to be running these experiments. We can experiment with lifecycle marketing, changing copy of push notifications and emails. We can experiment with app store screenshots and keywords and stuff like that. We have all sorts of content marketing teams, et cetera. We could have engineering enable no code for specific screens.
Think about our home screen or our pricing screen where we might want to do a lot of just tests that are configurable without engineering support. We might want to just track our progress and look at it from time to time and make sure that we have the right observability around this. So anyway, that's the stuff that really matters as opposed to the hitting that goal itself. So don't tell the team, but I don't actually care that much if we actually hit a thousand, but I think if we get pretty close and we accomplish some of these things, we'll be in really good shape.

Lenny RachitskyOkay, we'll make sure none of them watch this. I think chess.com is in, this is just such a cool example of a culture shifting dramatically from zero experiments to sounds like two years later, a thousand, which is three a day. There's many teams running experiments in parallel, but that's a lot. What has helped you most shift that culture? Is it just the CEO being like, "This is the way we're going to go." What have you learned about helping shift to culture from No, we're not doing experiments to a thousand experiments a year.

Albert ChengYeah, definitely a lot of credit to the CEO and co-founders like Erik and Danny, they're amazing. It's not their intuitive way of thinking about growing companies, but their mental flexibility and encouragement to evolve and add this as a tool for the company has been awesome, and they've been on the front lines preaching product-led growth and experimentation just as much as I have.

So I'm glad that you brought that up because I think that is critically important for me, joining a company to not be at odds with the co-founders and the existing approach of the company. I think that's absolutely, absolutely critical. I think I started this podcast with the example of the game review and the positivity and how that was shared. I think those types of things are really what motivate people. They need to see this working in practice.

Lenny RachitskyWins.

Albert ChengYeah, you need wins, you got to celebrate them. People feel good about the learning. It's applied across the board. Who's not going to be energized by that, I think, right? So you can't just set goals in a vacuum and create it from top, right? People have to see it working and when it works, the metrics move and you learn faster and you ship faster, and that's a great environment to be part of.

Lenny RachitskyWhat was the first experiment you guys ran? Do you remember?

Albert ChengI don't know, before my time actually.

Lenny RachitskyOkay. Okay. Got it. So they're already going down this track before they brought you in?

Albert ChengThey had run some.

Lenny RachitskyOkay, sweet. Are there any other key lessons that you think people need to know to be successful running experiments at scale?

Albert ChengThe system matters just as much as any given experiment, probably even more, right? I think starting with a growth model, so you have an understanding of how your company grows in the first place and which channels you're going to leverage is critical. You need to make sure that you are instrumenting your product in and out. Otherwise, you're going to run experiments and have wonky results.

I won't name which company, but I was part of a company that had an in-house experimentation tool. It's about three months into the company, we're running some experiments and we realized that user retention was actually configured backwards. So all positive results were negative results.

Lenny RachitskyGeez.

Albert ChengSo that was kind of embarrassing and that will never happen again.

Lenny RachitskyYou just go through and undo all those experiments and just drive up retention.

Albert ChengIt's kind of weird. We're seeing people use the features a lot more. Why is user retention going negative? So I have plenty of horror stories around that type of stuff, but yeah.

Lenny RachitskyOh my God. On the flip side of horror stories, you've shared a bunch of cool examples of experiment wins. Is there another that comes to mind of one you're really proud of or that was really trajectory changing either at Duolingo or Grammarly or Chess?

Albert ChengSo I already shared one of Chess.com and one of Grammarly. I could talk a bit about Duolingo as well. Duolingo and you had Jackson on the podcast, right? Where you talked about the streaks.

Lenny RachitskyYes, talked about the streaks.

Albert ChengSo I also don't want to steal his thunder because I was going to think about that, but the amount of learning through commitment and putting streaks on a calendar and just getting people started as opposed to achieving some large milestone, that was huge. I think we did something interesting. We spun up a virality team and virality is this really amorphous thing to me.

I think it's really hard to generate virality in your product, but Duolingo is a product that is shared quite a bit. And so we invested actually in some time to essentially add screenshot tracking for a brief period of time in the app just so we could find out the hotspots of where users were doing screenshots. And you see this in other apps too, it's not necessarily some horrible thing, but we did this for some period of time and we were able to basically articulate and say, "Okay, streak milestones is the obvious one."
Really funny challenges that you get in the Duolingo experience is also super highly shared. Advancing in the top three of a leaderboard is another thing. Anyway, so you can find these different moments where that's the case. And then we staffed those moments with illustrators and animators and created these really delightful experiences around them, and that worked amazingly well.
So as opposed to going against I guess human intuition and trying to get them to share stuff that they otherwise wouldn't on the margins want to share, lean into it more, actually grab the moments where users are already organically screenshotting and make those much, much, much better. And you can 5X or 10X and drive a lot of growth that way too. So that's not so much an experiment, it's more a core product thing, but it just resonated with me that that was interesting.

Lenny RachitskyWell, it connects to your explore and exploit methodology. Just find or explore where things are happening and then try to exploit in a nice positive way.

Albert ChengYou got it.

Lenny RachitskySpeaking of that, you mentioned this with Duolingo is just very good at habit formation and motivation behavior. It feels like chess is good at this too. You've worked at both these companies. What have you learned about how to motivate people? How to create habits?

Albert ChengAgain, Duolingo would not have started without this insight from day one. They aim to focus on motivation and build a lot of these tactics. Jorge actually had this model of gamification patterns having essentially three pillars to it. You have the core loop, you have the metagame, and then you have the profile. And so we actually thought about it that way too, where your core loop is your lesson that you go through. You do a lesson, you get some rewards, you extend your streak, and then the next day you get a push notification.

It's the core loop of the product and making that really tight is super important because people need a habit to stick to. Then you need a metagame, which for Duolingo is the path, but it's also the leaderboard achievements. It's long-term things that you're going to strive to such that you have long-term, I guess, motivation to continue doing the thing. And then the profile is also critical because you build up a profile over time.
It's a reflection of your investment inside the product experience. And so when you nail those three things, you can end up with a long-term learning journey that can be quite successful. And then to flip over to the Chess.com side, what we see is that over 75% of our new users, they classify themselves as like, "I'm completely new to chess." Or, "I'm a beginner." And unfortunately, if you're new to chess and you're a beginner, you're not going to have that fun of a time playing live games, and we see this in the data. It's like less than a third of those users actually win their first game. And when you lose a game, user retention is 10% worse than when you win a game.

Lenny RachitskyThat's not so bad, but at scale, that's bad.

Albert ChengYeah, and it could be worse. That's true. And so typically what a lot of mobile games will do is they'll just create a super simplified version of the game. It's harder for us to do at chess, and so without changing the rules of that, I think that's, I don't know, it's just very eye-opening to me when you're trying to learn something, whether that be language learning or chess or whatever, usually those first steps are fraught with a lot of self-doubt and reinforcement that you're not good at the thing. And so it pays to be very intentional to craft experiences that guide the user around that.

Lenny RachitskyWell, I can't help but ask, is there anything that helped that along?

Albert ChengYeah, so something we're experimenting right now is just like purely if you say that you're new to chess, we're going to craft a more delightful learn how to play experience as opposed to dropping into a live game, that's an example. Another is hiding your ratings for the first five times such that you're not seeing your rating plummet. So there's a lot of tips and tricks you can do.

Lenny RachitskyI'm just imagining a little guide that's like, "Here's how you win."

Albert ChengYeah, or play against a coach, play against a friend, play against a bot. There's a bunch of different avenues you could take.

Lenny RachitskyWell, what I'd love is play against someone real and here's where you should move. Just like, "Hey, here's we're going to help you win."

Albert ChengLike a hint in real-time?

Lenny RachitskyYeah, yeah, yeah.

Albert ChengI don't want to be playing with you then.

Lenny RachitskyOkay. Let me ask you a couple more questions. One is just zooming out a little bit, what's the most counterintuitive lesson you've learned about building products or building teams across the many companies you've worked at?

Albert ChengYeah, I've talked a lot about products. So maybe I'll flip to the team side for a bit. I think the standard way to hire and build a team is you fill out a JD, it's got a whole bunch of different characteristics that you're looking for. You typically will find a short list of companies that are kind of similar to yours, and then you try to hire for that, right? I think that's the typical default path that a lot of companies take.

And I was really struck by my experience working at some smaller startups or take Duolingo as an example, where over and over and over, I saw some of the highest performers just being people that had very high agency, had that clock speed, had that energy. Yes, they cared about the mission, but they didn't necessarily need to have deep experience on that matter. And in fact, sometimes that experience could be a crutch in certain ways, especially in this world where the grounds are shifting so fast with AI, a lot of your learned habits actually need to be intentionally discarded.
You need to have a beginner's mind on this type of stuff. So I think this is more true than ever, looking for people that respond and move quickly and think just faster and move faster. I think the fastest speed of learning, those types of companies are the ones that I want to bet on. I think those will end up surviving and thriving.

Lenny RachitskySo just to double click on this idea of high agency is very trending these days of just higher high agency people. To unpack that a little bit, you mentioned a few of these traits, so let's just help people see what you see. So one is clock speed, just they think fast, they move fast, they learn fast. What else? What else do you look for that helps you see that there are high agency people?

Albert ChengYeah, a lot of it actually happens outside of the interview process interestingly. So a lot of it is the types of questions they asked, "Have they actually tried your product and gone deep into it?" A lot of it is, it's the references, it's the communication that they have to even set up your interview, it's the energy they bring into the conversation.

You can actually pick up a lot of soft signals on some of these traits over time. You've got to pick up on some of these patterns. I don't know that I'm perfect at it, but I've learned to balance those things quite a bit more than I did in the past when I would just purely read from my questions and my rubric and not care about anything else.

Lenny RachitskyYeah, there's like a vibes component to it. This is also support for the work trial way of interviewing versus just a talk interview where you have them actually work with you for a week or whatever.

Albert ChengThat's a great point.

Lenny RachitskyOkay. One other question I wanted to ask you. You've worked at a bunch of different sizes of companies from startup to Grammarly, I don't know, you call it a big company, bigger company. Duolingo, I don't know how big is Duolingo?

Albert ChengThere are about a thousand people.

Lenny RachitskyOkay, cool.

Albert ChengBut I worked at Google too to start my career.

Lenny RachitskyOh, right, okay. What have you learned about just the size of company that makes you happy? What have you learned about just helping other people that you talk to decide what size of company is good for them?

Albert ChengI definitely believe that everyone has a company stage that they shine best at. I've personally gone through this journey of big tech to tiny, tiny, tiny startup, then landed in the middle, which I consider my own goal lock zone. I talked earlier about what actually gives me personally a lot of energy is seeing across a company's efforts, but also the company being small enough that I can get into the details, I can work with the specific teams.

I can read experiment results, I can look at the pixels. And so I find that the balance of those two things tends to fit best with medium-sized companies, but that's me, right? I think at big companies like a Google, you're dealing with immense scale, which is interesting by itself. You learn a lot of best practices from your peers. They have all the tools and functions that you would possibly want to go learn from, but they can tend to move slower and it's harder to ship things and get them out the door, which eventually drove me nuts a little bit.
On the flip end of the spectrum, these tiny startups, they move incredibly fast, but I grew all my gray hair from those tiny startups because no one knows about your company, and so you're recruiting people one by one. You're trying to get users one by one. So yeah, you can learn fast and ship a lot of things, but if you're trying to make a big impact on the world, it can be actually pretty grueling to do so at really, really, really small startups.
Now, some of them do hyperscale and make it out, and obviously, I am not one to trash that because the path that I tried for quite a while. But for me, I really like the zone where I can contribute at scale, but also execute at a pace that's more on the daily and weekly scale as opposed to monthly and quarterly.

Lenny RachitskyAnd when you say medium, what size of company is that roughly?

Albert ChengYeah, so these companies that we've talked about in the podcast are about 500 to a thousand people. Typically, these companies who have been around let's say 10 to 20 years. They're durable, ideally profitable, have a good leadership team, but there's still a lot of dimensions to go figure out. A lot of them are in key inflection points, so they're certainly not stagnant. You need to find a place that's dynamic too.

Lenny RachitskyInteresting, 10 to 20 years old, I don't know if that's a, not many people would feel like that's where I want to be. I love that you found a number of companies like that that you enjoyed working at. The last question, and this is going to be taking us to a recurring segment on the podcast that I call Failed Corner.

People hear all these stories of all these experiments and all these companies that worked at, they're all killing it up into the right. In reality, you've touched on this, a lot of things don't work out great. So can you share a story when something went wrong, when you failed and what that taught you?

Albert ChengFirst of all, in the growth world, you're failing all the time. So I'm not going to pick a specific growth story because those don't actually hit my ego too much. But earlier in my career I did a lot of core product work. I worked for this startup called Chariot. I don't know if you ever lived in San Francisco, but.

Lenny RachitskyYes, it was like the bus super thing.

Albert ChengThe blue commuter shuttles, like 15-person shuttles, they would essentially drive from various neighborhoods into downtown San Francisco. It's a commuting use case across between the public bus system and an Uber and Lyft. So I was there for some time. I led product there and the core service was really loved by its users. It was reliable and fast and affordable enough, but we got pretty interested in this idea that maybe we can improve utilization, maybe we can make the service a little bit more innovative if we offer dynamic routes more similar to Uber and Lyft.

How could the drivers are driving these fixed routes? But if they have spare time, they can go out of their way, go pick up somebody at their house or something and keep going. So we tried this, we called the chair direct, really interesting attempt, but I learned a lot of lessons there because ultimately it didn't work out. One lesson is like this was kind of a solution searching for a problem. You never just purely want to chase A, it wouldn't it be nice if we did this as opposed to this is our user and this is the problem that we're solving, this is why it's going to delight them, et cetera, that's one.
Second is you got to consider, especially in these more marketplace type businesses, there's more than just one end user and we focus so much of our attention on the writer app without realizing, oh yeah, the drivers are carrying a lot of the brunt of this experience and our operations team is as well. And so when the drivers are confused or disgruntled, that can lead to a challenging overall experience for the product. So that's definitely another one.
And the third one is we did a lot of actually PR, prior to the service going out just to get the word out. And PR has its time in place, but I think doing it before you have validation that customers definitely want, the thing is quite risky and it can lead to a lot of sun cost once you get it out because you need to see it through, you want to see it succeed. So yeah, this is a decade ago, honestly, I had a great time at that company, but I still remember that vividly because it contained three or more key lessons that carried forward as I have built many products since then.

Lenny RachitskyYeah, it feels like you went to the complete other end run experiments of everything before you tell anyone about it.

Albert ChengThat's right.

Lenny RachitskyYeah, I remember the chariot bus showing up at the Airbnb office and people getting, I'm like, "What the hell is this?"

Albert ChengThat's right.

Lenny RachitskyVery cool. I didn't know you worked there. Albert, we've covered so much ground everything I was hoping we'd cover. Is there anything else that you wanted to cover, anything else you want to leave listeners with before we get to a very exciting lightning round?

Albert ChengNo, this is great. I hope it was useful for your listeners. I will say over the last few days, as I was prepping for this, I was honestly a little bit anxious about do I have enough deep independent frameworks that I need to come up with? But just being authentic to my actual experience at these companies, a lot of my lessons learned have been off of the backs of other people that have tried similar things and have succeeded or failed.

And I think what's important is that you have that your mental sponge. You can try a bunch of different things, you can absorb them and then put them in practice right away, discard the things that don't work and evolve them for yourself and for the company's needs. And so I don't know, I think that was just a realization that I had as I was thinking through this podcast, and I think that's partly why I haven't done too much public speaking.

Lenny RachitskyI know exactly what you mean. When I left Airbnb, I was just like, and that was the first time I ever took a break in my career of 30 years of just working straight in school. I was just like, what have I actually learned? I've never just sat down and thought about, here's the thing I've learned. And that led me to writing this medium post that did really well what I learned at Airbnb, and then that basically led to what I do now. So there's a lot of power and I love that this is the excuse to make you think through what have I learned concretely that I can share.

Albert ChengThat's right. Thank you for that.

Lenny RachitskyYeah, and so at the beginning of this podcast, before I started recording, I always like to ask guests, what is your goal? What do you want to get out of this conversation? And usually, it's like we're hiring. We want to make sure people know about our company or we want to get the users. And your answer is just, I just want to give back things I've learned, which I love.

Albert ChengThat's it.

Lenny RachitskyAnd you've done that. With that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready?

Albert ChengI'm ready.

Lenny RachitskyWhat are two or three books that you find yourself recommending most to other people?

Albert ChengYeah, so the truth of it is I have a, not just the four-year-old, but I also have a one-year-old. So most of the books that I'm reading these days are kids' books, trying to make them laugh in all.

Lenny RachitskyWait, any favorite kids books? Because I have three or two year olds already.

Albert ChengWell, you said that you started singing. There's a book called Snuggle Puppy that has a song in it that just makes my daughter crack up.

Lenny RachitskyOh my God.

Albert ChengThat is heartwarming for me. But no, a book that I recommended recently at work is Ogilvy on Advertising. Do you know this book?

Lenny RachitskyI don't know the book. I've seen these tenants of marketing or whatever.

Albert ChengYeah, it's interesting. So it's 40 years old, but it's just packed with a bunch of different practical examples about copy and creative that work in, these are old school ads, but he took a very experimentation-oriented approach to just try a lot of things.

I think in the book, it makes a good reminder that what ultimately matters is to compel your users to some action for him as buying a product, right? It's not about just creating clever ads or sexy creatives, it's to do things that compel that action. I think that's very true for many of our product and life cycle teams. And so I shared that around as an interesting recommendation.

Lenny RachitskyIs there a movie or TV show? Sorry, were you going to share another book?

Albert ChengYeah, actually.

Lenny RachitskyOh yes, please.

Albert ChengOur co-founder at Chess.com, his name's Danny Rensch, and he is quite well known in the chess circles. He's releasing a memoir called Dark Squares, and it is super fascinating. He grew up in an abusive cult and was a chess prodigy. And so it is just this unbelievable story and I'm about halfway through it, it's a reminder that sometimes the people that you work with, you don't realize how deep their pasts go, but this is something else, and I think it should be out by the time this podcast releases.

Lenny RachitskyAnd it's called Dark Squares?

Albert ChengDark Squares.

Lenny RachitskyWhich is a reference to the chess board and also I imagine the difficult past.

Albert ChengExactly.

Lenny RachitskyWow. How cool. Okay. Are there movie or TV shows you really enjoyed that you've recently watched?

Albert ChengThese days it's football season, so I'm consumed by all the hot takes of my favorite teams that I love and the teams I love to hate as well, so.

Lenny RachitskyWho's your team?

Albert ChengThe 49ers. I have season tickets and I go all the time. We had a rough season last year, so hoping to turn around.

Lenny RachitskyOkay, very cool. Okay. Is there a product you've recently discovered that you really love?

Albert ChengYeah, so last 20 years of my life roughly, I've moved around a lot, but I've always been within walking distance of a coffee shop. It's just like a ritual that I go and get coffee and it starts my day, right? Two years ago, I bought a house and for the first time ever in my life I'm like not buy a coffee shop, and I was so depressed about this for a little while.

So my favorite product is the bread bowl barista, and it just starts my day off. I like making horrible latte art with it, and I think it's just a reminder. I don't know. The products that most impact me, I guess are the ones that I use all the time, and it's a daily habit-

Lenny RachitskyAnd have the most caffeine.

Albert ChengThen the most caffeine. You got it.

Lenny RachitskyAmazing. Do you have a favorite life motto that you find yourself using in work or in life?

Albert ChengAs I was thinking about my piano stories, I also remember that my mom used to have a quote. She just said, "Nothing is more important than your reputation." And she used to say this, and I think the charitable understanding of this is that a lot of the small decisions that you make each day, how do you treat people? How do you show up? What's your character, et cetera. They can compound and they open doors for you in many surprising and amazing ways.

A lot of these companies that have actually joined have come through relatively light connections. And even just being on this podcast, I think I've seen a number of folks that I've worked with before beyond the show. And so I think doing the right thing, building a good reputation, they can carry you a long way. And the flip side of that is reputations are fragile too, right? So if you do the wrong thing, take a long time to repair that. So I don't know, it just stuck with me my entire life. I thought that was an interesting life motto.

Lenny RachitskyLast question. You work at Chess.com, how's your chess?

Albert ChengTerrible compared to serious, serious players, but quite compared to the casual ones, yeah. My yellow rating is about 1,800 for a rabbit games.

Lenny RachitskyIt sounds really-

Albert ChengAnd about 1,500 for blitz. Yeah, but I play many times every day.

Lenny RachitskyBlitz is like fast chess?

Albert ChengBlitz is like faster chess, three minute games. Rapid is more like a 10-minute game, which is still pretty fast.

Lenny RachitskyAnd you say you play multiple times a day? Do they make time? Is this like-

Albert ChengThey do.

Lenny RachitskyOkay. At Patagonia, there's a famous book, the founder wrote called Let My People Go Surfing, and the rule at Patagonia is you can go surfing if the waves are great. Is that how it works at Chess.com?

Albert ChengAbsolutely.

Lenny RachitskyOkay.

Albert ChengChess is always fun. So we play all the time and they even have chess coaches on staff.

Lenny RachitskyStaff, just like you can book to do?

Albert ChengYou can book. So I get bi-weekly lessons and it's helping me improve.

Lenny RachitskyWow. Okay. This is going to drive a lot of hiring for you guys. Saved it for the end. Albert, this was awesome. Thank you so much for doing this. Thanks so much for giving back and sharing all these stories. Two final questions, work and folks find you if they want to follow up on some of this stuff, and how can listeners be useful to you?

Albert ChengYeah, thanks for having me. This was great. You can find me on LinkedIn or Twitter. Not a super active poster, but I read it all the time. If there's something that I said today that resonates with you and you just want to get in touch, trade notes, feel free to reach out.

Lenny RachitskyAnd can they play with you on, can they find you on Chess.com to play?

Albert ChengThey can.

Lenny RachitskyOkay. Do you want to share your username or you don't want that?

Albert ChengI am happy to.

Lenny RachitskyNo. Okay.

Albert ChengI just mentioned that I'm a 49ers fan, so my username is Go9ers, so.

Lenny RachitskyWow.

Albert ChengI'm sure I'll get a lot of game requests now.

Lenny RachitskyHere we go. Here we go. 1,800. Okay. Albert, thank you so much for being here.

Albert ChengYeah, thank you so much.

Lenny RachitskyBye everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcast, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.

Albert Cheng增长这份工作的本质，是把用户和产品的价值连接起来。增长有时会被误解成纯粹的指标黑客。

Lenny Rachitsky你在全世界最成功的三款消费订阅产品里都做过。你觉得大家在做成功的消费订阅产品时，最容易忽略的关键点是什么？

Albert Cheng对消费订阅公司来说，用户留存就是黄金。留不住用户，很多压力就会落到第一天怎么让他们掏钱上。

Lenny RachitskyNoam Levinsky 让我一定要问你一个问题：你在 Grammarly 找到的最大商业化突破是什么？

Albert Cheng对大多数免费用户来说，Grammarly 的实际体验就是改拼写、改语法，因为他们看到的也主要是这些免费建议。那如果我们把一些不同的付费建议穿插着展示给免费用户呢？这样一来，大家对 Grammarly 的认知一下子就会从“一个改错工具”变成“一个强大得多的写作助手”。

Lenny Rachitsky你在组建团队这件事上，学到过最反直觉的一课是什么？

Albert Cheng我见过一些最厉害的人，往往不是那些在某个领域经验最深的人，而是那些自主性很强、节奏很快、能量很足的人。经验有时候反而会变成包袱，尤其在 AI 让环境变化这么快的时候，很多原来的习惯都得有意识地丢掉。

Lenny Rachitsky今天的嘉宾是 Albert Cheng。Albert 被认为是全世界最顶尖的消费增长高手之一。他先后负责过 Duolingo、Grammarly 和现在 Chess.com 的增长与变现。更早之前，他还在 YouTube 做过视频和游戏相关功能，服务过两千多万用户。

他的增长方法把营销、数据、策略和产品管理揉在一起。今天我们会聊很多，包括他用来寻找增长机会的 explore / exploit 框架，他在 Duolingo、Grammarly 和 Chess.com 做过的最有意思的增长战役，他怎么用 AI 提速增长工作，他对品牌和社区在增长中的作用有了什么新认识，他最重视的实验方法，以及为什么他每家公司都希望一年跑 1000 个实验，等等。
去 lennysnewsletter.com 点 Product Pass 就行。好了，下面把 Albert 交给大家。今晚我们会聊工艺、品味、自主性和 product-market fit。你知道我们最不爱聊什么吗？SOC 2。Vanta 就是干这个的。Vanta 帮各种规模的公司快速通过合规检查，并持续保持合规，靠的是行业领先的 AI 自动化和持续监控。不管你是创业公司，第一次做 SOC 2 或 ISO 27001，还是企业在管理供应商风险，Vanta 的信任管理平台都能让这件事更快、更简单，也更可扩展。
Vanta 还能把安全问卷的处理速度提高最多 5 倍，让你更快拿下更大的单子。根据一份 IDC 研究，Vanta 客户每年能省下超过 50 万美元，而且生产力高出三倍。建立信任不是可选项，Vanta 会把它变成自动流程。去 Vanta.com/lenny 可享受 1000 美元优惠。另一期节目由 Jira Product Discovery 赞助。做产品最难的，其实不是“做产品”，而是其他一切。
是证明这项工作值得做，是管理干系人，是提前规划。大多数团队花在反应和学习上的时间太少，花在追进度、解释路线图、不断帮别人解阻上的时间太多。Jira Product Discovery 能把你拉回正轨。它可以帮你收集洞察、优先排序高价值想法。
它很灵活，能适配你团队的工作方式，帮你做出一条推动共识而不是制造疑问的路线图。而且它建立在 Jira 之上，你可以把想法从策略一路跟到交付，全都放在同一个地方，少一点追着人跑，多一点时间去思考、学习，做真正对的事。去 Atlassian.com/lenny 可以免费试用 Jira Product Discovery。Albert，谢谢你今天来，欢迎做客。

Albert Cheng谢谢邀请，Lenny，很高兴来。
这评价太好了，谢谢 Jorge。我从他身上学到很多。我是那种怪人，会在孩子醒来之前起床，打开一堆浏览器标签页看实验数据。Jorge 把我带进 Duolingo 的增长世界特别合适，我学到了很多最佳实践，他本身也是个很棒的人。谢谢你，Jorge。

Lenny Rachitsky我们已经开始聊这些策略了，我很喜欢。先给这次对话一个框架。我想做的是，帮大家学会找到自己产品增长机会的工具和心智模型，本质上是学到你带进公司和产品里的那种增长思维。

我想先从你是怎么成为今天的你的说起。我在最近几位嘉宾身上发现一个有意思的模式，很多人年轻时钢琴都弹得特别好，而且都很认真。比如 ChatGPT 负责人 Nick Turley，差点就成了职业爵士钢琴家。你早年也是很认真的钢琴选手。你是怎么从钢琴家变成世界顶级增长高手之一的？

Albert Cheng这评价很高，不过我很感激。是的，我从小弹很多钢琴。我父母是从台湾移民过来的，我是家里的老大，所以他们对我有一种很强的期待，或者说鼓励吧，希望我多学点东西，认真对待、好好学习，我也确实这么做了。虽然他们自己不太懂音乐，但他们非常热爱古典音乐。

所以我小时候就是那种典型的宝宝，睡觉的时候都在听莫扎特之类的。我到现在都还记得，我们家有一台立式雅马哈钢琴，钢琴最上面放着一个从 90 分钟倒计时的计时器。我整个童年几乎每天都在练，练得非常非常规律。
一开始我真的很烦那个东西，但随着年纪变大，我对音乐的感受也越来越深。不过真正让我在钢琴上进步更快的，是我觉得自己中了彩票，因为我有绝对音感，所以我能很快听出来自己弹对了还是弹错了，学起音乐来非常快。

Lenny Rachitsky绝对音感到底是什么意思？是指你能分辨正在响的是哪个音吗？

Albert Cheng对，没错。

Lenny Rachitsky明白。

Albert Cheng对。

Lenny Rachitsky哇。

Albert Cheng所以我听一首歌时，能非常清楚地知道应该从哪个音开始，如果我弹错了也马上能听出来。这个能力很有帮助。

Lenny Rachitsky这也太不公平了。

Albert Cheng确实不公平，绝对是。总之，我在高中那会儿已经弹得相当不错了，甚至考虑过去音乐学院读书。不过那时候我对音乐的内在驱动力没那么强了，所以最后决定去工程学院。要是走那条路，我的人生会完全不同。顺着你刚才说的音乐和增长的关系，我其实最近才开始认真反思这件事。

我现在有个四岁的孩子，正开始教他随便在琴键上敲一敲。不过有两点特别明显。第一，我觉得音乐和增长都很依赖持续重复。你会一直犯错，有一个非常紧的反馈回路，你必须对“老是犯错”这件事变得足够有韧性，而且你知道学习就是从这些错误里来的。这是我很早就学到的一点。第二点是，它们都有一个结构性的底层支撑。
在增长里，你有增长模型、指标、实验、渠道这些东西。但你每天还是得有创造力，想出有趣的方案或者可以验证的假设。音乐也是一样。你有音阶、乐理这些理论基础，但要做出美妙的音乐，你还是需要激情、情感和流动感。所以我觉得，这两个世界最美的地方就在于它们都把结构和创造力结合在了一起。

Lenny Rachitsky说个有意思的事，我太太最近送了我钢琴和唱歌课当父亲节礼物，我现在还挺上头的。我现在在学非常基础的钢琴，也在学怎么辨认音高、用嗓子唱准音。

Albert Cheng不错啊。

Lenny Rachitsky这真是个很奇怪的新爱好。

Albert Cheng说不定就是你的下一段表演。

Lenny Rachitsky有可能。我可以走相反的路线，变成职业钢琴演奏者。天啊。真的太好玩了，但也太难了。我就一直在想：我手指怎么才能一次按四个键啊？我整个人都在想，这到底怎么回事。好，我们进入正题，聊增长。

有一个非常具体的框架，我觉得我们刚刚聊到的内容很值得大家听听。你把它叫做 explore 和 exploit。我觉得这个概念有很多种理解方式。你来讲讲这个框架，以及它怎么影响你思考增长。

Albert Cheng对，我最早是在 Grammarly 时，从我的工程搭档 Nermal 那儿听到或者说自己琢磨出这个 explore / exploit 框架的。其实他好像还上过一些 reforged 的课。所以它的原始发明人也许是 Brian Balfour，我知道他上过你的播客。不过不管怎样，这是个很棒的概念。

大意是，当你处在探索模式时，可以把它理解成：你在找哪座山值得爬。到了利用模式时，就像是把资源集中到那座山上，真正把它爬好。对一些公司来说，警告就在于，不要把太多时间都花在光谱的一端。如果你过度探索，团队就会显得太散，什么都想试一点，结果试了上百个随机想法。
那主线是什么？策略是什么？怎么把这些成功模式串起来？如果你过度利用，也就是很多增长团队常见的做法，就会变成饱和和停滞，你只是在局部把某个东西榨到极致。虽然 explore / exploit 通常被看作是宏观层面的原则，但我更喜欢和团队在“洞察”层面一起工作。所以我讲个具体例子。
我在 Chess.com 工作，我们的优先事项之一是鼓励下棋的人去提升、去学习、去进步。我们有个 PM 叫 Dylan，负责所有学习功能。我们产品里用得最多的学习功能叫 game review。你下一盘棋，结束后会有一个虚拟教练，告诉你哪几步走得最差、哪几步走得最好，等等。他的任务就是提升用户参与度和留存。
所以他正处在探索阶段，想弄清楚：我该怎么推动更多这种活动？他观察到一个很反直觉的事实：会去复盘棋局的人，80% 都是在赢了之后才复盘。这跟我们最初做这个功能时的预期完全相反。我们原本以为，人们会更想在输棋后用它，去看自己哪里下错了，好改进错误。但从人类心理和真实数据来看，事实并不是这样。所以我们就调整了产品体验。
现在你输棋之后，我们不再把你的失误和糟糕操作直接摆到最前面，而是反过来展示你的妙手、你的最佳走法，并让教练说一些鼓励的话，比如“输棋本来就是学习的一部分，继续加油。”类似这样。光这一项改动，对我们来说就已经很显著了。
game review 的使用量提升了 25%，订阅提升了 20%，用户留存也提升了不少。所以这当然很棒，但重点是，它不能只停在这里。你得把这个洞察带回公司，广泛分享出去。现在，旁边做其他产品的 PM，比如负责 puzzles 的 PM，也能开始想：“好，我怎么审视我产品里的这些冷冰冰的模式，把它们变得更积极？”
我可以改成功反馈的评分，我可以微调文案，我可以改按钮颜色。这样，你就能把一次实验的胜利扩展成公司里 10 倍的影响，这就是利用阶段的意义。做得好的时候，你就能在两种模式之间来回切换，直到利用空间被榨得差不多了，再鼓励团队重新发散、回到脑暴，变得更有创造力。

Lenny Rachitsky太棒了。这里有很多可以继续追问的点。一个核心建议是，当你发现某个东西特别有效时，要想办法基于这个学习继续扩展。一个是这个洞察可以迁移到产品的其他部分。“嘿，团队们，我们学到了一个意外的东西，也许对你们有帮助。顺手再多找找，在同一个方向里多做点实验。”我想这也是其中一部分。

Albert Cheng对，完全没错。按我的经验，实验的常见胜率，虽然我不太喜欢用这个词，但大概就是 30% 到 50% 左右。通常你会试很多东西，很多假设最后都不成立。消费产品就是这么不可预测。但一旦你找到一个穿透噪音的点，哪怕它其实是个大失败的实验，也一样很有价值。

把这些发现横向带到公司里，原来跑这个实验的 PM 不一定非得亲自去想产品其他部分该怎么做，但他们有责任把自己的假设、发现讲清楚。这样作为增长负责人，我就能鼓励大家围绕这个点集结，试更多不同想法，让成功率和影响力一起上升。所以，本质上就是在这两端来回摆动。这就是那个关键解法。

Lenny Rachitsky我听你这么说，另一个感受是：一个领域里能拿到的胜利，往往比人们想的多得多。你完全可以在同一个东西里持续找到增长和胜利，而且能找很久。

Albert Cheng完全对。用户这件事上，我觉得公司内部有时候会把产品体验切成五十个不同的块，分发给不同团队，大家就默认用户在每个功能上的心态都不一样。但很多时候，其实并不是这样。有时你能提炼出一个更基于人类心理的洞察，它可以贯穿整个产品体验。所以我觉得，只要你找到了这种东西，就值得重仓。

Lenny Rachitsky听到这些的人可能会想：“好，先找到大胜利，再找到更多。”你有没有什么办法，能帮助判断什么时候该 explore，什么时候该 exploit？或者说，什么时候 exploit 得太过了？有没有什么经验法则，或者你会怎么带别人走这条路？

Albert Cheng我在 Chess.com 这种规模的公司里会重点关注的一件事是，我们一年大概跑 250 个实验。这个数量不是行业里最高的，但也不算少。所以在这种情况下，我会投资一些实验探索工具，我们也可以聊聊 AI，它是发现和提取这些知识点的另一种方式。总之，这类探索工具能让我横向看整个实验谱系，看看不同假设和不同学习之间有没有模式。

如果我开始看到越来越多的实验都没有统计显著性，那可能就是一个信号，说明我们在 exploit 上走得有点太远了，剩下的空间可能没那么多了。伙计们，该回到桌子前再脑暴一下了，思路得更发散一点。

Lenny Rachitsky那我们顺着 AI 这条线聊聊吧。你刚才说到你怎么用 AI 帮自己判断这些东西，这很酷。展开讲讲。

Albert Cheng我最近最常折腾的一件事，是 text to SQL 能力。它真的很强。我们有一个数据请求 Slack 频道，长期以来到现在也还是这样，大家会往里丢各种临时问题：我们在南非有多少订阅用户？上个月某个人下了多久的棋类题目？之类的。

这些临时问题通常会吃掉大量人力时间。数据分析师要排优先级，抽时间去跑查询。当然，你也可以投资自助工具来改善这件事。但我发现 AI 在做第一轮回答这件事上也相当强。所以我们正在训练一些 Slack bot，让它们基本上成为这类问题的第一响应者，这样整个公司就会更数据驱动一些。
我觉得还有个挺有意思的点是，人通常会因为害羞，或者不想麻烦别人，就干脆不问问题。但只要你有这些工具，大家会问的问题量会一下子爆发出来。我觉得在 ChatGPT 上你也能看到这一点。只要有一个你愿意对话、觉得舒服的东西，差别就会非常大。

Lenny Rachitsky这太酷了。所以这东西本质上是个 Slack bot，给你 SQL 查询，还是它会直接帮你做分析？

Albert Cheng不，它会直接做分析。

Lenny Rachitsky哇，太厉害了。那这个你们会发布出来吗，还是说只是“大家都应该在每家公司做一个”？

Albert Cheng我们应该做。这是个好主意。

Lenny Rachitsky懂了。那大概会有一期节目，评论区里全在说“开源它”。我们看看会不会又变成这样。这个真的很酷。你见过或者做过类似的其他东西吗？

Albert Cheng另一个类似例子是，现在很多产品经理都在折腾各种原型工具。目标就是把一个想法快速变成一个代表性的解决方案。今天，很多人要先把想法写成 spec，做评审，再走设计流程，等等。我猜你也采访过很多人聊过这个具体问题。

所以对我们来说，我们投入了一点精力，至少把产品体验里几个核心页面先拆出来，比如 onboarding 流程、首页、棋盘这些，然后用 V0 或 Lovable 这类工具做成 AI 原型。把这些底层部件搭好以后，你就可以分享给公司其他人，他们可以把这些东西当成起点，在上面叠自己的想法，这样它们就更容易被讨论，也更快能被测试。

Lenny Rachitsky按这条线说，你的 AI 技术栈里都有哪些？

Albert ChengPM 主要在用 V0。设计师最爱 Figma，所以他们在用 Figma Make。工程师现在则在混着用好几个工具，比如 Cursor、Cloud Code、GitHub、Copilot。市场团队会用各种翻译、字幕、内容改写工具。客服那边则用 Intercom。所以公司里会用到的工具还挺多的。

不过让我有点烦的是，我们还没把“从折腾到工作流”这一步衔接得像我想象中那么顺。也就是说，虽然现在大家普遍都觉得 AI 会打散这些职能标签，但从经验看，你还是会更偏向某一类工具。如果这些工具跟你后续真正要交付、要推到生产环境里的其他工具不够互通，至少在我们这个规模上，衔接还是会有一些手工环节。
小公司当然可以，PM 直接上手做完发出去就行。但对我们来说，不同职能之间还是有一些交接。我预计这件事以后会变，但我们现在也在投入一些设计系统组件、MCP 之类的东西，希望把这条链路打通得更顺一点。不过是的，这是一项投资，而且把这些东西磨顺确实要时间。

Albert Cheng对，我最早是在 Grammarly 时，从我的工程搭档 Nermal 那儿听到或者说自己琢磨出这个 explore / exploit 框架的。其实他好像还上过一些 reforged 的课。所以它的原始发明人也许是 Brian Balfour，我知道他上过你的播客。不过不管怎样，这是个很棒的概念。

大意是，当你处在探索模式时，可以把它理解成：你在找哪座山值得爬。到了利用模式时，就像是把资源集中到那座山上，真正把它爬好。对一些公司来说，警告就在于，不要把太多时间都花在光谱的一端。如果你过度探索，团队就会显得太散，什么都想试一点，结果试了上百个随机想法。
那主线是什么？策略是什么？怎么把这些成功模式串起来？如果你过度利用，也就是很多增长团队常见的做法，就会变成饱和和停滞，你只是在局部把某个东西榨到极致。虽然 explore / exploit 通常被看作是宏观层面的原则，但我更喜欢和团队在“洞察”层面一起工作。所以我讲个具体例子。
我在 Chess.com 工作，我们的优先事项之一是鼓励下棋的人去提升、去学习、去进步。我们有个 PM 叫 Dylan，负责所有学习功能。我们产品里用得最多的学习功能叫 game review。你下一盘棋，结束后会有一个虚拟教练，告诉你哪几步走得最差、哪几步走得最好，等等。他的任务就是提升用户参与度和留存。
所以他正处在探索阶段，想弄清楚：我该怎么推动更多这种活动？他观察到一个很反直觉的事实：会去复盘棋局的人，80% 都是在赢了之后才复盘。这跟我们最初做这个功能时的预期完全相反。我们原本以为，人们会更想在输棋后用它，去看自己哪里下错了，好改进错误。但从人类心理和真实数据来看，事实并不是这样。所以我们就调整了产品体验。
现在你输棋之后，我们不再把你的失误和糟糕操作直接摆到最前面，而是反过来展示你的妙手、你的最佳走法，并让教练说一些鼓励的话，比如“输棋本来就是学习的一部分，继续加油。”类似这样。光这一项改动，对我们来说就已经很显著了。
game review 的使用量提升了 25%，订阅提升了 20%，用户留存也提升了不少。所以这当然很棒，但重点是，它不能只停在这里。你得把这个洞察带回公司，广泛分享出去。现在，旁边做其他产品的 PM，比如负责 puzzles 的 PM，也能开始想：“好，我怎么审视我产品里的这些冷冰冰的模式，把它们变得更积极？”
我可以改成功反馈的评分，我可以微调文案，我可以改按钮颜色。这样，你就能把一次实验的胜利扩展成公司里 10 倍的影响，这就是利用阶段的意义。做得好的时候，你就能在两种模式之间来回切换，直到利用空间被榨得差不多了，再鼓励团队重新发散、回到脑暴，变得更有创造力。

Lenny Rachitsky太棒了。这里有很多可以继续追问的点。一个核心建议是，当你发现某个东西特别有效时，要想办法基于这个学习继续扩展。一个是这个洞察可以迁移到产品的其他部分。“嘿，团队们，我们学到了一个意外的东西，也许对你们有帮助。顺手再多找找，在同一个方向里多做点实验。”我想这也是其中一部分。

Albert Cheng对，完全没错。按我的经验，实验的常见胜率，虽然我不太喜欢用这个词，但大概就是 30% 到 50% 左右。通常你会试很多东西，很多假设最后都不成立。消费产品就是这么不可预测。但一旦你找到一个穿透噪音的点，哪怕它其实是个大失败的实验，也一样很有价值。

把这些发现横向带到公司里，原来跑这个实验的 PM 不一定非得亲自去想产品其他部分该怎么做，但他们有责任把自己的假设、发现讲清楚。这样作为增长负责人，我就能鼓励大家围绕这个点集结，试更多不同想法，让成功率和影响力一起上升。所以，本质上就是在这两端来回摆动。这就是那个关键解法。

Lenny Rachitsky我听你这么说，另一个感受是：一个领域里能拿到的胜利，往往比人们想的多得多。你完全可以在同一个东西里持续找到增长和胜利，而且能找很久。

Albert Cheng完全对。用户这件事上，我觉得公司内部有时候会把产品体验切成五十个不同的块，分发给不同团队，大家就默认用户在每个功能上的心态都不一样。但很多时候，其实并不是这样。有时你能提炼出一个更基于人类心理的洞察，它可以贯穿整个产品体验。所以我觉得，只要你找到了这种东西，就值得重仓。

Lenny Rachitsky听到这些的人可能会想：“好，先找到大胜利，再找到更多。”你有没有什么办法，能帮助判断什么时候该 explore，什么时候该 exploit？或者说，什么时候 exploit 得太过了？有没有什么经验法则，或者你会怎么带别人走这条路？

Albert Cheng我在 Chess.com 这种规模的公司里会重点关注的一件事是，我们一年大概跑 250 个实验。这个数量不是行业里最高的，但也不算少。所以在这种情况下，我会投资一些实验探索工具，我们也可以聊聊 AI，它是发现和提取这些知识点的另一种方式。总之，这类探索工具能让我横向看整个实验谱系，看看不同假设和不同学习之间有没有模式。

如果我开始看到越来越多的实验都没有统计显著性，那可能就是一个信号，说明我们在 exploit 上走得有点太远了，剩下的空间可能没那么多了。伙计们，该回到桌子前再脑暴一下了，思路得更发散一点。

Lenny Rachitsky那我们顺着 AI 这条线聊聊吧。你刚才说到你怎么用 AI 帮自己判断这些东西，这很酷。展开讲讲。

Albert Cheng我最近最常折腾的一件事，是 text to SQL 能力。它真的很强。我们有一个数据请求 Slack 频道，长期以来到现在也还是这样，大家会往里丢各种临时问题：我们在南非有多少订阅用户？上个月某个人下了多久的棋类题目？之类的。

这些临时问题通常会吃掉大量人力时间。数据分析师要排优先级，抽时间去跑查询。当然，你也可以投资自助工具来改善这件事。但我发现 AI 在做第一轮回答这件事上也相当强。所以我们正在训练一些 Slack bot，让它们基本上成为这类问题的第一响应者，这样整个公司就会更数据驱动一些。
我觉得还有个挺有意思的点是，人通常会因为害羞，或者不想麻烦别人，就干脆不问问题。但只要你有这些工具，大家会问的问题量会一下子爆发出来。我觉得在 ChatGPT 上你也能看到这一点。只要有一个你愿意对话、觉得舒服的东西，差别就会非常大。

Lenny Rachitsky这太酷了。所以这东西本质上是个 Slack bot，给你 SQL 查询，还是它会直接帮你做分析？

Albert Cheng不，它会直接做分析。

Lenny Rachitsky哇，太厉害了。那这个你们会发布出来吗，还是说只是“大家都应该在每家公司做一个”？

Albert Cheng我们应该做。这是个好主意。

Lenny Rachitsky懂了。那大概会有一期节目，评论区里全在说“开源它”。我们看看会不会又变成这样。这个真的很酷。你见过或者做过类似的其他东西吗？

Albert Cheng另一个类似例子是，现在很多产品经理都在折腾各种原型工具。目标就是把一个想法快速变成一个代表性的解决方案。今天，很多人要先把想法写成 spec，做评审，再走设计流程，等等。我猜你也采访过很多人聊过这个具体问题。

所以对我们来说，我们投入了一点精力，至少把产品体验里几个核心页面先拆出来，比如 onboarding 流程、首页、棋盘这些，然后用 V0 或 Lovable 这类工具做成 AI 原型。把这些底层部件搭好以后，你就可以分享给公司其他人，他们可以把这些东西当成起点，在上面叠自己的想法，这样它们就更容易被讨论，也更快能被测试。

Lenny Rachitsky按这条线说，你的 AI 技术栈里都有哪些？

Albert ChengPM 主要在用 V0。设计师最爱 Figma，所以他们在用 Figma Make。工程师现在则在混着用好几个工具，比如 Cursor、Cloud Code、GitHub、Copilot。市场团队会用各种翻译、字幕、内容改写工具。客服那边则用 Intercom。所以公司里会用到的工具还挺多的。

不过让我有点烦的是，我们还没把“从折腾到工作流”这一步衔接得像我想象中那么顺。也就是说，虽然现在大家普遍都觉得 AI 会打散这些职能标签，但从经验看，你还是会更偏向某一类工具。如果这些工具跟你后续真正要交付、要推到生产环境里的其他工具不够互通，至少在我们这个规模上，衔接还是会有一些手工环节。
小公司当然可以，PM 直接上手做完发出去就行。但对我们来说，不同职能之间还是有一些交接。我预计这件事以后会变，但我们现在也在投入一些设计系统组件、MCP 之类的东西，希望把这条链路打通得更顺一点。不过是的，这是一项投资，而且把这些东西磨顺确实要时间。

我想先回到你在不同公司里作为产品人、增长人的工作方式是怎么变化的。不过先说另一个增长和变现的例子。Noam Levinsky 现在是 Grammarly 的首席产品官，你在 Grammarly 时和他共事过。他让我一定要问你：你在 Grammarly 找到的最大变现突破是什么，又是怎么发现这个机会的？

Lenny Rachitsky我想把话题拉回到你在不同公司里做产品、做增长时，工作方式是怎么变化的。不过在这之前，我想先聊一个增长和变现的例子。Noam Levinsky 现在是 Grammarly 的首席产品官，你在 Grammarly 的时候跟他共事过。他让我一定要问你：你在 Grammarly 找到的最大变现突破是什么，又是怎么发现这个机会的？

Albert Cheng我很高兴当时能和 Noam 以及他的产品团队一起在 Grammarly 工作。先给没用过 Grammarly 的人补个背景。Grammarly 是一款 AI 写作助手，通常大家会把它当成 Chrome 扩展，或者下载安装到桌面端使用。它的核心作用，就是在你的写作里实时叠加各种不同的建议。

Lenny Rachitsky我在用，我是它的铁粉。

Albert Cheng纠正一下，那你就是铁粉了。

Lenny Rachitsky……而且它真的救过我很多次。

Albert Cheng太好了，听你这么说我很开心。Grammarly 的商业模式是 freemium，也就是超过 90% 的用户在用免费服务，剩下的人才会为订阅付费。我们有一支专门做订阅转化的团队，PM 是 Kayla，那支团队很强，他们的工作就是把免费到付费的路径摸清楚。

我们先意识到一件事：对于用户收到的建议类型、以及他们看到付费墙的频率，我们其实没有把事件埋点记得足够清楚。第一步，就是先把这些基础数据补上。第二步，我们开始想：“等等，先把这个逻辑讲明白。”
作为免费用户，你会看到写作里到处都是下划线；如果你把这些建议全都接受了，就会看到付费墙，这会推动你去订阅更细致、更高级的功能。免费版主要给的是拼写、语法这些东西，本质上就是 correctness 相关的能力；而付费版会更进一步，比如怎么把语气改得更有同理心，怎么让表达更清晰。
你还可以重写整句，甚至重写整个句子结构，这类能力等等。跑完数据之后我们发现，真正会把所有建议一股脑全接受的免费用户其实非常少。大家更多是在写的过程中自己挑着用，我猜你自己的体验也差不多。

Lenny Rachitsky完全是。对，我经常会想：“等等，别把整句都改了。”这句有问题的地方我自己会改。对，我就是那种会挑着接受的人。

Albert Cheng没错。

Lenny Rachitsky就是纠错型用户。

Albert Cheng第二件我觉得同样、甚至更有意思的事，是我正好在这家公司经历了生成式 AI 的转型，而这场转型显然到现在还在继续。说得直白一点，公司品牌，以及大多数免费用户实际感受到的产品体验，当时都把 Grammarly 认成一个只负责帮你改拼写和语法的工具，因为我们展示给他们看的也正是这些免费建议。

所以我们决定彻底把这件事翻过来：如果我们把一些付费建议，穿插着展示给免费用户看，会发生什么？也就是说，让它们交织在一起，给用户尝一小口付费版真正能提供的价值。表面上看，这样做是合理的，但担心也很直接：如果我们给太多出去，用户还会想订阅吗？
结果完全不是这么回事。突然之间，大家开始把 Grammarly 看成一个强得多的工具，而不是以前那样了。只靠这个改动，我们的升级率就几乎翻倍了。所以我觉得这件事挺有意思的。尤其是做 freemium 产品的时候，尽量让免费产品本身就能反映出产品的全部能力。当然，某些付费功能会有一些成本，但只要你把最好的东西亮出来，通常还是划算的。对我们来说，这个改动确实非常有效。

Lenny Rachitsky我觉得我就是被这个改动转成 Grammarly 付费用户的。太聪明了。说白了，就是一堆改进建议先给你看，但你最多只能用三个，然后就会提示你升级。

Albert Cheng本质上，这就是一个“逆向免费试用”，只不过它是在你写作的时候实时发生的，而不是按时间来算。所以我们借用了行业里一些常见模式，但把它改造成了 Grammarly 自己的用法。

Lenny Rachitsky对。我正想问的就是，这不是那种完整试用，而是一个有上限的试用：你能用一定次数，用完就没了，然后再刷新。我记得好像是每天刷新一次，对吧？

Albert Cheng对，就是这样。

Lenny Rachitsky对。Grammarly 在促销转化这件事上，真的是最会、也最“狡猾”的。我总会想：“天哪，我离看到一个更好的改写只差一步了，我只能升级。”它就摆在那儿，鼠标旁边就是升级按钮。

Albert Cheng对，我倒不太想说自己“狡猾”，但你这么理解也行。

Lenny Rachitsky但确实很厉害地让我掏钱了。干得漂亮。是 Kayla 对吧？Kayla，做得好。这招真的非常有效。我很喜欢。那回到免费试用这件事，我也不确定，freemium、直接送、pro 账号、试用按时间算还是按功能算、某些功能限制次数……你对消费订阅产品有没有什么通用建议？

Albert Cheng有，我觉得首先要回答一个问题：为什么一开始就要做 freemium 订阅？我加入过的这些公司里，很多都是 freemium 模式。那我为什么喜欢它？第一，我觉得这跟很多公司的使命感非常契合。很多时候，你就是想尽可能把产品传播出去，因为这本来就是创始人做这件事的初衷。

你是在用 Duolingo、Grammarly 或 Chess.com 这类产品改善教育，或者更广义地说，提供一个全球都适用、价值主张很宽的产品。那最小的使用门槛，显然就是免费。所以这本身就是原因之一。另一个原因是，这些产品很多主要靠口碑增长；如果你还能在产品里做出网络效应，那就更强了。比如 Duolingo 有不少社交功能，Grammarly 也带一点 B2C2B 的味道。
也就是说，用户即使在免费计划里，依然能给 Grammarly 带来不少价值，因为它最终可能会被同事、团队成员，或者某个团队买单。所以我通常会倾向于这样做：让你提供给用户的核心价值是免费、而且是永久免费的，然后再在上面叠加一点对高级功能的采样或“尝鲜”。这通常就是我见过的最佳平衡点。
至于试用，尤其是 reverse trial 这种方式，我觉得要看情况。如果你做的是 B2B 功能，而且用户一旦进去就会有一定锁定效应，那 reverse trial 会非常强。你只要把人先拉进来就行，不必急着要信用卡，因为他们可能已经在你的 CRM 里工作，或者已经投入了大量时间去搭内容、搭素材。等窗口一过，他们就会真的觉得：“糟了，这东西我可能还是得留着、得付钱。”但对很多消费级产品来说，这种方式会更难奏效，所以我通常看到的还是标准的免费试用更常见。

Lenny Rachitsky我想顺着消费订阅产品这条线继续聊。我觉得这类产品是每个独立开发者都梦想做的，因为看起来很简单：做个 app，加个付费墙就行。然后大家才发现，这比想象中难太多了。从分发、获客成本、增长这些角度看，做成功的消费订阅产品，大家最容易忽略的，是不是就是这块？

Albert Cheng对。对消费订阅公司来说，用户留存就是金子。如果你留不住用户，那很多压力就会落到第一天就让他付费上，这非常难。接下来你面对的，其实就是完全不同的商业模式：你要花钱买用户，还得在他们还没形成使用习惯之前，尽可能激进地把他们往上卖。

很多 app 在早期确实会这么做，因为那样才能打破常规、拿到第一批用户。不过我自己比较幸运，加入的大多是已经过了最初那个阶段的公司。像 Duolingo 和 Chess.com 这种，都是靠自然口碑驱动的生意；而且它们不是在一个特别拥挤的红海里靠抢别人的市场份额、拼更高 bid 起量，而是把市场本身做大了不少。所以我觉得这里面确实有点门道。

Lenny Rachitsky所以我听下来是，你必须想办法通过口碑增长，不然这事儿几乎没有成功机会；同时留存也必须非常高。你有没有一个大概的经验值，达到什么样的留存，才算有机会把一个消费订阅业务做起来？

Albert Cheng我觉得消费公司通常会看两类留存。第一类是新用户留存，比如 D1、D7 之类。我觉得如果你的 D1 留存能到 30% 或 40% 左右，那对消费级 app 来说已经挺不错了。如果更低，有时候我就会怀疑用户的意图，或者你能不能在数学上凑到足够多的用户，撑起一个足够大的日活盘子。

Lenny Rachitsky这个数字比我想象中低不少。

Albert Cheng对。

Lenny Rachitsky所以理论上感觉还是可实现的。

Albert Cheng理论上是可实现的。理论上确实可行，但市场上的选择太多了，大家也越来越有“app 太多、产品太多”的疲劳感。

Lenny Rachitsky那我确认一下，你说的是有 20% 到 30% 的人第二天会回来？

Albert Cheng对，30% 到 40%。

Lenny Rachitsky30% 到 40%。

Albert Cheng40% 的话，我觉得已经不错了。更重要的是，你一开始也提到了 Jorge，他写过一篇特别火的文章，讲增长模型，以及当前用户留存率对他们最重要。我觉得尤其是那种每天都会用的产品，真正最重要的留存，其实是已经形成习惯的老用户留存，也就是你的存量用户到底有多黏。这个留存率才会真正累积起来，慢慢养成日常习惯。

Lenny Rachitsky这很合理。是啊，数据上会显示某个人是日活，因为他在打字，但这对 Grammarly 来说其实不是准确的口径。我在很多成功的消费订阅产品里还看到一个趋势：它们一开始都特别简陋、特别省钱、特别讲究投放效率。我觉得原因是，它们通常要花很久才能找到真正有效的东西，于是只能靠那点留存带来的增长回报，勉强撑着往前走。

Albert Cheng对，没错。
对。我拿 Chess.com 举个例子，大概能有 80% 左右的日活或周活用户，应该是老用户、现有用户。我回头再看一下数据，但大概就是这个量级。新用户和重新激活、被“唤醒”的用户，加起来其实和它差不多大。对于我们这种规模的公司来说，情况就是这样。所以虽然大家都很关注新用户体验，但公司成熟到一定程度后，你会发现，活跃用户的构成里，真正的新用户占比并没有大家想象得那么重。

Lenny Rachitsky你能再解释一下吗？

Albert Cheng可以。公司做了一段时间之后，产品里会积累很多不活跃用户，也会积累很多零散用户，他们可能没有每天使用的习惯，但一周会用一两次，或者一个月用一两次。时间一长，这个盘子就会越来越大。最后你会有几亿级别的沉默用户在回来，这时候就非常值得花时间去打磨“被唤醒后”的产品体验，并且想办法用一些新的方式把他们拉回来。

Duolingo 就做得很好，他们很会用社交通知。比如你同步了通讯录，系统可能就会推送：你最好的朋友刚刚开始用 Duolingo。这个提醒很容易把你拉回来，让你重新回到产品里。就算你重新回来了，也可能发现自己以前学的语言已经忘了大半，比如你三年前学的是法语，现在几乎忘光了。所以你再次打开 App 的时候，它会引导你重新做一次分班测试，把你放到正确的位置上。像这种机制，对成熟公司来说，ROI 往往都挺不错。

Lenny Rachitsky懂了。说白了，就是过去已经有那么多人试过了，所以要想继续增长，你就得把那些离开过的人再拉回来。某种意义上，这几乎是在为“回流用户”设计一整套用户体验。

Albert Cheng没错。

Lenny Rachitsky好，我们再往外看一点。你做过世界上三个最成功的消费订阅产品。它们之间到底有什么不同？我觉得成功的路径有很多种，这几家公司看起来也非常不一样。各自最核心的运作方式是什么？

Albert Cheng当然，它们之间有很多相似点，不过我这里就专门讲差异。先说 Duolingo。最打动我的地方是，他们的产品开发方法几乎渗透到了公司里每一个人。他们甚至专门写过一本 playbook，叫 Green Machine，你搜一下就能找到。这大概也是我发得最成功的一条推文之一。

Lenny Rachitsky我之前也发过一条，说 Duolingo 刚放出他们的 playbook，我截了个 owl 屁股的图，再配上一页内容，结果有五千多个赞。

Albert Cheng太好笑了。

Lenny Rachitsky是吧。继续继续，抱歉打断了。

Albert Cheng不过对，就是这家公司本身的气质。他们会招很多聪明、精力旺盛的年轻人，主要是刚毕业的那种，然后给他们很强的实验能力、工具支持，而且特别在意公司的 clock speed，也就是节奏和速度。所以你会看到大量的创造力和想法。

Duolingo 的产品体验，用户每天甚至会发生好几次变化，这其实挺惊人的。我以前从来没在这样的地方工作过，但最让我印象深刻的，就是他们做事的连贯性。他们对产品开发流程里的每一步都有清晰的规格和流程，而且非常严格。

Lenny Rachitsky哦，所以还是 Duolingo。

Albert Cheng对，还是 Duolingo。再说 Grammarly。这个公司很有意思，因为它最初是一个面向学生的付费产品，后来逐渐扩展成更偏 freemium 的模式，面向所有人，再慢慢把重心转向专业用户。等他们积累了更多专业用户之后，就发现了一些规律。比如很多营销团队、销售团队、客服团队，或者某些公司里的特定职能，都在大规模使用 Grammarly。

于是他们就开始叠加更明显的企业化、可管理的销售路径。而我在那里的时候，主要负责的是消费端自助增长，但两边并不是割裂的，它们是交织在一起的。所以我工作里很大一部分，不只是拉动自助收入和自助活跃用户，还要去识别哪些团队、哪些职能、哪些公司，值得让 demand gen 和 sales 去重点跟进。
这是一种很典型的 product-led sales 工作方式，对我来说特别有意思。再加上生成式 AI 的转型，以及最近他们收购了 Coda 和 Superhuman、开始往 productivity suite 方向走，这家公司变化非常快。能参与其中，或者哪怕站在旁边看，都很让人兴奋。但也正因为这样，它本质上就是一份跟 Duolingo 完全不同的增长工作。

Lenny Rachitsky也就是说，这是一个更偏 B2B 的业务，而不是很纯的消费业务？

Albert Cheng对，而且要做的战略决策也更重、更关键。

Lenny Rachitsky嗯。

Albert Cheng还有核心产品团队这件事。我以前在增长里习惯做的是，把用户完整路径拆出来：获客、激活、参与、留存，等等。通常情况下，只要增长团队资源够，基本能把这些杠杆都推动一点，剩下就是你想先排什么顺序的问题。但 Grammarly 很特别，因为真正驱动反复使用的，是核心产品体验本身。

我前面说过，当前用户留存那件事，最主要的驱动因素就是你每天收到的建议频率和质量。所以当时我组了一支增长团队，想专门盯这个指标，后来才意识到，实际上我是在挡路。真正影响这件事的，是核心产品团队。于是我就去跟核心产品负责人沟通，把这件事移交给他们。对我来说，这是一段特别有意思的经历。

Lenny Rachitsky那 Chess.com 呢？

Albert ChengChess.com 最独特的地方，就是他们对国际象棋真的到了狂热的程度。

Lenny Rachitsky很合理。

Albert Cheng一点都不夸张，你不该惊讶。公司名字都已经说明一切了。他们一直都在全球远程招聘，招的就是热爱国际象棋的人。大家白天都在下棋、看直播，我们的 Slack 里天天都是别人的棋步、对局和讨论。我想稍微委婉地说，像 Duolingo 虽然做的是语言学习，但它最初的公司气质，其实更像是在做“动机”和“习惯”。

最难的是习惯这件事，怎么把日常习惯建立起来？从很多角度看，我都把语言学习看作他们的第一载体。而他们真正的超能力，其实也是动机、习惯这些东西。Grammarly 也类似。大家都知道他们是做拼写和语法纠错的，但真正独特的地方，是它能跨越无数应用场景进行集成。
这种产品并不多见，非常独特。现在你再听他们的新 CEO Shishir 讲什么 AI super highway 之类的东西，就知道他们可以借助这项技术提供远不止语法写作的能力。所以我的意思是，Chess 就是 100% 围绕 chess 本身。那是他们的 ethos。大家真的很痴迷，这就意味着我们一直在自家产品上 dogfood，整个公司都充满了把产品天天拿来用、不断冒新点子的能量。我很喜欢这种环境，我觉得这很有趣。

Lenny Rachitsky太酷了。我喜欢你刚刚说的这一点：这件事没有对错答案。所有这些公司都做得很好。Duolingo 可能值一百亿美元左右，而且还在继续增长。我一会儿去查一下。Grammarly 也很值钱，Chess.com 也做得特别好。所以我觉得这个很重要的 takeaway 是，你可以用很多不同的方式成功。

Albert Cheng对。

Lenny Rachitsky我刚刚听你讲 Duolingo 的时候就在想，最有意思的是，这种非常结构化、方法论很强的做法，居然能运转得这么好。因为你要是只听描述，可能会觉得：“我不想在这种很死板的方式里工作。”但它确实跑通了，说明这套办法真的有效。只要你找到有效的方法，就应该顺着它继续做。

Albert Cheng对，就是这样。结构是很 rigid，但他们的想法却是离 rigid 最远的。你看过他们的超级碗广告吧，都是 meme、游戏化、各种战术，特别有创意。rigid 这个词完全不适合形容他们，我只是想说他们很一致。每件事都有明确流程，而且产品评审会只开 10 到 15 分钟，大家进进出出。整个环境很超现实，但他们就是能又快又稳地推进。

Lenny Rachitsky太厉害了。Duolingo 现在大概值 120 亿美元，而且前阵子其实还更高一点，最近回落了一些。说到 Duolingo，大家想到的往往是品牌、那只猫头鹰、以及他们在 TikTok 上的成功之类的东西。我想听听你作为一个很重视增长的人，对这类“增长实验数据”和“营销、病毒式短视频、吉祥物”之间关系的看法。

Albert Cheng以前我也觉得这是非此即彼，但现在我发现它们其实配合得非常好，甚至能成为增长的火箭燃料。作为产品人，我加入过的很多公司，手机首页上本来就有它们，我自己也确实爱用。我一直觉得自己不是那种很容易被广告或电视购物左右的人。

所以在职业生涯里，我对营销这件事一直多少有点怀疑。但在 Duolingo，你会看到 Duo 这只猫头鹰是怎么通过推送通知和产品体验慢慢长出人格的，再看到市场团队怎么把这种人格放到 TikTok、YouTube 和各种社媒里去放大，最后把这些梗继续喂回产品里。我们还会在产品里追问用户“你是怎么知道我们的”，把这些渠道都记进去。有些日子，单靠这些渠道就能贡献新用户的 20% 到 30%。所以这两件事真的高度互补。
而这个感觉，在过去五年里也被 Chess.com 再次强化了。这个公司前十五年其实一直比较低调。全球有 8 亿人下国际象棋，但大多数还是线下对弈。直到最近几年，网上的增长才真正起来。五年前情况开始变化：疫情、后翼弃兵、YouTube 和 Twitch 主播、学校里大量孩子开始下棋，等等。真正让它起飞的，就是这些因素叠加在一起。
从增长实验的角度看，它更像是“慢而稳”或者“快而稳”的节奏：你不停迭代，把产品体验做得更好；但隔一阵子就会有一股大浪冲进来。某一天注册量直接翻四倍，你要是不赶紧接住，那就太可惜了。

Lenny Rachitsky我前阵子其实在 Chess.com 下棋。上周末我在咖啡店里看到一家三口，爸爸、妈妈和女儿在点单，爸爸坐在桌边，偷偷掏出手机打开 Chess.com，边等边下，太有意思了。

Albert Cheng这个我既不会承认，也不会否认自己干过。

Lenny Rachitsky但如果让我想一个更健康、更温和的消遣方式，我还真想不出来。坐着的时候能做这个，已经很棒了。

Albert Cheng我四岁的儿子现在已经会摆棋子了，这点还挺厉害的，所以他也挺喜欢这项游戏。

Lenny Rachitsky天啊，这个四岁小朋友已经会摆棋子了，还是个钢琴小天才，又会下棋。

Albert Cheng没错。

Lenny Rachitsky真是个小神童。这个节目由 Miro 赞助。每天都有新的头条在吓唬我们，说 AI 要来抢工作了，让人很焦虑、很不安，但 Miro 最近的一项调查给出了另一种答案：76% 的人认为 AI 能帮助自己的工作，而超过 50% 的人不知道什么时候该用它。于是就轮到 Miro 的 Innovation Workspace 出场了，这是一个把人和 AI 放在同一个空间里协作的智能平台，帮助团队把活真正做成。

Miro 十多年来一直在帮助团队把大胆的想法变成下一个大东西。现在，它正站在把产品更快推向市场的最前沿，把 AI 和人的能力结合起来。我在这档播客里经常分享 Miro 模板，自己也一直拿它跟团队一起头脑风暴。团队尤其可以用 Miro AI，把便利贴、截图这类非结构化内容，快速变成可用的图表、产品 brief、数据表和原型。
你不需要是 AI 高手，也不用再多切换一个工具。你在 Miro 画布里正在做的事，本身就是 prompt。去 Miro.com/lenny 看看吧，链接是 M-I-R-O.com/lenny。好，刚才你也零零散散提到了一些 AI。
我想顺着这条线问下去。作为增长人，你可以想象 AI 会在很多层面影响 Chess.com，所以这里其实有两个方向：AI 是怎么改变产品的，比如 Chess.com，以及你之前待过的其他地方；还有 AI 是怎么影响你作为增长人的工作。你可以选其中一个，也可以两个都讲。

Albert Cheng好，我按顺序来。先说国际象棋这边，因为我对这一块可能有一点点独特的看法。国际象棋和 AI 几乎已经纠缠了快一个世纪了。早期的计算机先驱们就觉得：“国际象棋很适合拿来测试机器智能，顺便写点算法。”然后到了 1997 年，IBM 的 Deep Blue 打败了当时的世界冠军卡斯帕罗夫，那是个非常震撼的时刻。

当时大家都在想：“完了，AI 要接管世界了？人类会不会没工作了？”那是三十年前了，好在我们今天都还在，而且下棋的人比以前更多了。国际象棋，尤其是 Chess.com，已经学会了怎么借助棋类引擎来增强人的对弈体验。要说明白一点，这不等同于 LLM，而是像 Stockfish 这样的引擎，它们现在已经比世界顶级特级大师强得多。

Lenny Rachitsky已经到这一步了？我记得它是先打败人类，现在居然已经强这么多了？

Albert Cheng对，强很多。

Lenny Rachitsky哇。

Albert Cheng对。一般来说，人类棋手的分数大概在 1000 左右，顶尖特级大师像 Magnus Carlsen，大概 2800，而 Stockfish 之类的引擎能到 3600 左右。

Lenny Rachitsky哇。

Albert Cheng拿这个做个对比就很直观了。

Lenny Rachitsky至少还没夸张到 10000 或 100 万。我甚至都不知道那是不是可能。

Albert Cheng不是 10000。你可以把它理解成：哪怕让引擎少一枚车之类的大子，它依然能和最强棋手打得有来有回。

Lenny Rachitsky这是 Elo 分吧？是这个叫法吗？

Albert Cheng对，就是 Elo 分，Elo rating。

Lenny Rachitsky你刚刚说 Magnus 大概 2800，Stockfish 大概 3600？

Albert Cheng对。说到底，这还是因为算力太强了，而且它们可以对具体棋线做非常深的评估，一秒能算几千万步。人类根本没法跟这个级别竞争。但反过来，这些引擎也确实打开了很多新思路、新战术、新线路，让大家对这项游戏有了更多欣赏。Chess.com 的思路就是把这种技术带给每一个用户。

哪怕是一个从来没碰过棋子的人也一样。前面我提到的那个 game review 产品，就是这么工作的：后台跑棋类引擎，把你每一步都评估出来，然后我们再把这些结果翻译成用户自己的语言，用更容易理解的方式讲出来，甚至加上音频之类的交互。而其中“说话的风格”“回话的个性”这一部分，才是 LLM 发挥作用的地方。
我的意思是，国际象棋和 AI 一直就是绑在一起的，但对我们来说，最重要的是始终把用户放在北极星的位置上。我们不会因为 LLM 很新很热，就无脑往里塞；必须用对的技术，去做对的功能，真正给用户带来价值。所以我们尽量不被 hype 带着跑。

Lenny Rachitsky这真的挺意外的。我想很多人都不会想到，AI 居然没能“打败所有人类”，但国际象棋现在反而更火了，大家想继续下，而且下得比以往更多了，这其实也不奇怪。

Albert Cheng有意思的是，LLM 本身其实不太擅长下棋。它们会幻觉走法，很擅长模式识别，但在具体某一盘棋上做非常深的推演就没那么强了。你甚至如果在 ChatGPT 里生成国际象棋棋盘图，很多时候棋盘格子数量都不对，摆放也不对。所以我不想把它说得太轻蔑。

当然，推理能力以后肯定会越来越强。其实 Google 最近还赞助了一个比赛，让各家顶尖 LLM 互相对弈，挺好玩的。它们在进步，但就棋类这个具体任务来说，训练过的深度引擎还是会比 LLM 强得多。

Lenny Rachitsky我不想把话题拽太远，不过 AlphaZero 因为打败了顶级围棋选手而出名。它是不是专门针对围棋训练的？显然不是 LLM，但它确实是一个围棋专用模型。

Albert Cheng对。我的理解是，那个纪录片特别棒，不知道你有没有看过《AlphaGo》，它把这么技术向的东西拍得非常情绪化、非常有人味。我觉得这某种程度上也是我们对 AI、以及我们做出来的产品的感受来源。回到你的问题，我理解 AlphaZero 的主要训练方式，就是不断和自己对弈。通过神经网络，它每一次都会变得更聪明。因为它可以重复十亿次、甚至万亿次，我也不确定准确数字，但反正会变得非常强。

Lenny Rachitsky好，我们回到正轨。刚才讲的是 AI 怎么影响 Chess.com。那 AI 又是怎么改变增长人的工作本身的？

Albert Cheng我通常把增长理解成：把用户连接到产品价值的工作。为了做到这点，我会先看用户旅程，然后围绕旅程的每个环节配对应的团队。每个团队都有自己的指标目标、路线图，然后去推进。

这就是它的结构。AI 我觉得可以用来加速实验循环里的某些环节。比如产品发现这块。核心产品通常时间周期更长，你会做很系统的用户研究、市场研究，更偏基础、偏 first principles。增长则没那么“厚重”。

Albert Cheng这就像你在跑一连串实验，每一次实验的结果，都会变成下一轮想法的输入。以前，或者说就在几个月前，我们还处在一种需要大量手写分析文档的状态。你得自己读这些文档，提炼出想抓住的洞察，然后再写一份新的 spec，把这个想法翻译出来。现在这件事虽然还在发生，但我觉得像 ChatGPT 这样的工具已经非常有帮助了。

你可以直接把别人写好的分析丢进去，让它帮你总结，还能顺手给你一些下一步可以试的点子。这样一来，构思和研究的循环就快了很多。我前面也提到过，原型设计的速度现在也比以前快很多。我们还没有走到 PM 自己把代码直接推上生产的程度，但从“想到一个更大胆的点子”到真的把它讲清楚，这中间的时间已经被大幅缩短了。
所以我前面讲 explore / exploit 的时候，explore 那部分以前更难做，但现在容易了一点。你可以先把一个更大的概念可视化出来，而一旦可视化了，你就能把它发给团队，大家点进去看，这种差别会非常大。大概就是我脑子里会冒出来的几个例子。

Lenny Rachitsky太棒了。我想回到你开头那句我觉得特别有帮助的话：你把 growth 看成“把用户连接到产品价值”的工作。

Albert Cheng对。

Lenny Rachitsky你能再展开说说吗？因为我觉得这真的很清楚地定义了 growth 的角色。

Albert Cheng能，这个说法对我来说很有共鸣，因为 growth 有时会被贴上“只会刷指标”的标签，好像我们就是一群冷冰冰的人，只想着把某个数字往上推，不断加墙、加付费墙、加摩擦。就算这些做法在某个具体功能、某个具体指标上微观层面上可能成立，但我觉得对公司最健康、而且我自己也更想待的，是那些能从整体上看待用户的公司。

而“把用户连接到产品价值”这个框架，会随着时间变化。一个用户刚接触产品时，需要理解的价值主张，和一个已经用了三年多的老用户需要理解的价值主张，差别非常大。负责这些部分的团队，也应该从这个角度出发，再往下拆具体问题、假设等等。

Lenny Rachitsky顺着这个话题再问一点。听到这里的人大概都会想：“怎么才能更会做实验？怎么才能多做实验？怎么把这件事做得更好？”你觉得人们在团队里想提升实验能力时，最需要知道的两三条建议是什么？

Albert Cheng第一条其实很简单：先从某个地方开始。我刚看了 Atlassian 的产品状态报告，里面说大概有 40% 的产品团队根本不做实验。这可能有合理原因，比如理念不同，或者你们更偏 B2B 等等。所以我能理解。但如果你在做的是带一点规模、而且用户使用频率也不低的消费产品，其实你是能收集到足够数据的。

而且我发现，我的模式识别能力虽然一直在线，我也做过很多公司，但我还是经常判断错。消费者行为很容易变，尤其当你在公司里待久了，你自然会变成一个 power user，有时就会忘记一个新用户到底在经历什么。所以如果你连实验都不愿意试，就会漏掉很多机会。
所以我会鼓励大家先跨出第一步。先做一个 A/B 测试，找个第三方工具，或者直接跟工程师合作搭一个最小可行版本。先练 crawl，再 walk，再 run。

Lenny Rachitsky顺便问一句，你有没有自己最喜欢的工具？有没有什么常用的？

Albert Cheng我们在 Grammarly 用的是 Statsig，我看到他们最近被收购了，那是个很棒的消息。Duolingo 和 Chess.com 都是自己做实验系统的。

Lenny Rachitsky不错。

Albert Cheng这两种方式各有利弊。Duolingo 显然就是一台实验机器，所以有一套专门为实验打造的内部系统，效果非常强。但我一般不建议公司从第一天就自己造实验平台。到了某个规模之后，这事儿可能有意义。只是像这些公司很多是 15 年前起步的，那时候这类工具还没那么成熟，所以他们只能自己做。

Lenny Rachitsky你之前跟我提过，在 Chess.com 你的目标是一年做 1000 个实验，你那时候已经到 250 个了。能讲讲这个北极星目标吗？

Albert Cheng当然。公司里有很多对国际象棋特别狂热的人，所以他们其实已经能靠自己、靠社区做很多事，不怎么依赖实验和数据驱动。问题是，这样增长会比较“块状”，忽快忽慢。所以我加入这家公司的一部分动力，就是帮助把增长变平滑，把实验思维带进来。

2023 年之前，这家公司几乎不做实验。去年大概做了 50 个，今年预计能到 250 个。然后明年我们定了一个很激进的目标：1000 个。这个数字是我拍脑袋想出来的，没错，完全是我拍的，但它至少能让团队开始思考：要真想达到这个目标，必须满足什么条件。1000 个实验本身并不重要，如果你只是做了 1000 个，但没学到东西，也没有产生影响，那其实是浪费时间。
设目标的意义，在于你可以围绕“要达到这个目标，哪些条件必须成立”来展开讨论，而这会反过来带来洞察。比如我们不只是 product manager 或 engineering 才能做实验。生命周期营销也能实验，比如改 push notification 和 email 的文案。App Store 截图、关键词也能实验。我们还有各种内容营销团队。工程也可以为某些页面做 no-code 支持。
比如首页、定价页这种地方，我们可能想做很多不需要工程介入、直接可配置的测试。我们还想定期看一看进展，确保有合适的观测能力。总之，真正重要的是这些能力，而不是那个数字本身。所以别告诉团队，但我其实并不太在乎最后是不是一定到 1000；我更在乎我们是不是足够接近，并且把这些该做的事情都做了。

Lenny Rachitsky好，我们会确保没人看这期节目。我觉得 Chess.com 这个例子太酷了：一个文化可以从完全不做实验，短短两年内变成一年一千个实验，也就是平均每天三四个。虽然很多团队会并行跑实验，但这还是很多。你最主要是怎么推动这种文化变化的？只是 CEO 说“我们就这么干”吗？你从“完全不做实验”走到“一年一千个实验”学到了什么？

Albert Cheng当然，CEO 和联合创始人 Erik、Danny 的功劳特别大。他们非常厉害。对公司成长的直觉方式和他们原本的想法不一样，但他们愿意调整、愿意把实验当成工具加进来，这一点特别棒。而且他们也站在一线，跟我一样不断强调 product-led growth 和 experimentation。

我很高兴你问到这一点，因为对我来说，这个真的很关键：我加入一家公司的时候，不能和创始人、也不能和公司的既有做法站到对立面。我觉得这点绝对重要。刚才我讲了 game review 和积极反馈的例子，我觉得这种东西最能激励人。人们得看到这事真的在运转。

Lenny Rachitsky赢面。

Albert Cheng对，你得有胜利，还得庆祝。人们会因为学到东西而感觉很好。这一套是可以推广到各个方向的。谁不想被这种东西点燃呢？所以你不能只是关起门来定目标、从上往下硬推。人们必须真的看到它在发生，而一旦发生了，指标会动，学习会更快，发版也会更快。能处在这种环境里，真的很棒。

Lenny Rachitsky你还记得第一个实验是什么吗？

Albert Cheng不记得了，那是在我来之前做的。

Lenny Rachitsky明白。也就是说，他们在你加入前就已经开始走这条路了？

Albert Cheng对，之前已经做过一些了。

Lenny Rachitsky好，明白。你觉得还有哪些关键经验，是大家在规模化做实验时必须知道的？

Albert Cheng我觉得系统本身和任何一个单独实验一样重要，甚至可能更重要。首先你得有 growth model，也就是理解公司到底是怎么增长的、会用哪些渠道，这很关键。然后你必须把产品的进出流量都埋点好，不然你做出来的实验结果就会很怪。

我不会说是哪家公司，但我曾经待过一家有自研实验工具的公司。入职大概三个月左右，我们在跑实验时突然发现，用户留存的配置方向居然是反的。于是所有“正向”的结果其实都是负向结果。

Lenny Rachitsky天哪。

Albert Cheng这就挺尴尬的，而且这种事以后绝不会再发生了。

Lenny Rachitsky那你不就是把之前所有实验都推翻，然后把留存往回拉吗？

Albert Cheng很怪。我们当时还在想：“咦，用户怎么更频繁地用这些功能了，怎么留存反而变负了？” 所以这种事我手里有不少恐怖故事，但也算经验吧。

Lenny Rachitsky我的天。那反过来说，除了这些恐怖故事，你提过不少很棒的实验案例。有没有另一个你特别自豪、或者真正改变了轨迹的例子，来自 Duolingo、Grammarly 或 Chess？

Albert Cheng我前面已经讲了 Chess.com 和 Grammarly 的例子。我也可以稍微讲讲 Duolingo。Duolingo 的那个 streaks，你之前不是也请过 Jackson 吗？当时就聊过 streaks。

Lenny Rachitsky对，聊过 streaks。

Albert Cheng我也不想抢他的风头，所以当时想了一下。其实最重要的学习，就是通过承诺机制，让人把 streak 写进日历里，让他们先开始，而不是先追求某个巨大里程碑。这个方向非常大。我觉得我们做过一个挺有意思的事：我们成立过一个 virality 团队，而“病毒性”对我来说其实很难定义。

我觉得很难直接在产品里“造出”病毒性。但 Duolingo 本身又是一个天然容易被分享的产品。所以我们当时花了一段时间，在 App 里短暂加了截图追踪，只是为了找出用户最常截图的热点。别的 App 也会这样做，这不一定是什么坏事。我们做完之后，基本就能说清楚：最明显的当然是 streak milestone。
还有 Duolingo 里那些特别好笑的挑战，也很容易被分享。Leaderboard 排名前三也是一个点。总之，你能找到很多这样的时刻。然后我们就给这些时刻配上插画师和动画师，围绕它们做出特别讨喜的体验，效果非常好。
与其逆着人的直觉，逼他们分享原本不太想分享的东西，不如顺着来，抓住那些用户本来就会自然截图、自然分享的瞬间，把它们做得更好。这样你完全可以把效果放大 5 倍、10 倍，增长也能因此起来。这严格来说不算实验，更像是核心产品的工作，但它让我印象很深。

Lenny Rachitsky这正好跟你说的 explore / exploit 方法论对上了。先去探索哪里已经在发生，然后想办法用一种正向、友好的方式去放大。

Albert Cheng对，就是这个意思。

Lenny Rachitsky顺着这个说，你前面提到 Duolingo 特别擅长习惯形成和动机行为。Chess.com 也很像。你又在这两家公司都待过，你从“怎么激励人、怎么培养习惯”这件事上学到了什么？

Albert Cheng再说一次，Duolingo 从第一天起就不是“顺便”做这些的，他们一开始就是冲着动机和各种激励机制来的。Jorge 其实有个模型，把游戏化模式分成三个支柱：核心循环、元游戏，以及个人档案。我们当时也差不多是按这个思路来想的。核心循环就是用户的 lesson：做一节课、拿奖励、延续 streak，第二天再收到推送。

这就是产品的核心循环。把这个循环做紧非常重要，因为人们需要一个能坚持的习惯。然后你还需要一个元游戏，对 Duolingo 来说就是 path，另外还有 leaderboard 成就这些长期目标。它们是你会持续努力的东西，让你有长期动机继续做下去。最后，profile 也很关键，因为它会随着时间累积。
它是你在产品里投入的一个体现。只要这三样都做对了，你就能拥有一条很成功的长期学习旅程。再说 Chess.com 那边，我们看到超过 75% 的新用户会把自己归类成“我是完全新手”或者“我是初学者”。但如果你是新手，直接去打 live game，通常不会很好玩，数据也证明了这一点。第一局能赢的人不到三分之一。而输掉一局的人，留存会比赢的人低 10%。

Lenny Rachitsky这不算太糟，但放大到整体就很糟了。

Albert Cheng对，也可以更糟。很多手机游戏会直接做一个简化版玩法，让新手更容易上手。但在国际象棋里，我们没法改规则。所以对我来说，这件事特别提醒我：无论是学语言还是下棋，或者学别的东西，最开始的几步通常都伴随着大量自我怀疑和“我不擅长”的反馈。所以你得非常刻意地设计体验，帮用户绕过这一段。

Lenny Rachitsky我忍不住想问，有什么办法能改善这件事吗？

Albert Cheng有。我们现在正在尝试的一件事是：如果你说自己是新手，我们就给你一个更愉快的“学会怎么玩”流程，而不是直接把你丢进实战里，这是一个例子。另一个例子是，前五次都先把评分藏起来，这样你就不会一直盯着自己的分数往下掉。能做的技巧其实很多。

Lenny Rachitsky我脑子里已经浮现出一个小向导在旁边说：“这是怎么赢的。”

Albert Cheng对，或者你可以先跟教练下、跟朋友下、跟机器人下。路径有很多种。

Lenny Rachitsky我更想要的是：跟真人下，但系统会告诉你现在该走哪一步。就是“我们来帮你赢”。

Albert Cheng实时给提示？

Lenny Rachitsky对对对。

Albert Cheng那我可不想跟你下棋了。

Lenny Rachitsky好，我再问你几个问题。其中一个就是稍微拉远一点看：你在这么多公司里做过产品和团队建设，学到的最反直觉的一条教训是什么？

Albert Cheng嗯，我前面讲了很多产品，那我换到团队这边说。我觉得大家通常招人、搭团队的方式，是先写好 JD，列一堆特征，然后找一批和自己公司相似的公司去对标，再按那个方向招人。这是很多公司的默认路径。

但我在一些小公司，或者拿 Duolingo 举例的时候，反复看到一些表现最好的人，往往不是“经验最深”的那种，而是 agency 非常强、节奏很快、能量很高的人。对，使命感他们也在乎，但不一定非要在那个领域有很深的经验。事实上，在 AI 变化这么快的今天，过去学来的很多习惯都得有意识地丢掉。
你得保持一种初学者心态。所以我现在越来越相信：要找那些反应快、行动快、思考快的人。那些学习速度最快的公司，才是我愿意押注的。我觉得它们最后更有可能活下来，也更有可能越做越好。

Lenny Rachitsky顺着“高 agency”这个现在很流行的话题再展开一点。你刚刚提到了一些特质，我们帮大家把它拆开看。一个是 clock speed，也就是他们想得快、动得快、学得快。还有什么？你还会看什么，来判断一个人是不是高 agency？

Albert Cheng有意思的是，这里面很多信息其实不是在面试里出现的。比如他们会问什么问题，他们有没有真的用过你的产品、还深入研究过；参考人怎么说；他们为了安排面试时的沟通方式；他们进来时带来的能量。这些都能看出来。

很多这类软信号，其实你慢慢就能捕捉到。得学会识别这些模式。我不敢说自己已经很完美了，但我确实比以前更会平衡这些东西了。以前我会完全照着问题和评分表来，别的都不看。现在不会了。

Lenny Rachitsky对，这里面确实有种“感觉”成分。这个也支持一种工作试用式的面试方法，而不只是坐着聊一聊，让人真的跟你一起干一周之类的。

Albert Cheng这个观点很好。

Lenny Rachitsky再问一个问题。你待过不同规模的公司，从创业公司到 Grammarly，再到我不知道你会不会把它叫大公司，反正是更大的公司。Duolingo 我也不确定算多大？

Albert Cheng大概一千人左右。

Lenny Rachitsky好，明白。

Albert Cheng不过我职业生涯一开始还在 Google。

Lenny Rachitsky对，对。那你学到的，关于什么样的公司规模最适合你，或者你怎么帮别人判断哪种规模更适合他们，是什么？

Albert Cheng我非常相信，每个人都有自己最能发光的公司阶段。我自己一路经历了大厂、超小创业公司，最后落在中间这个区间，我把它当成自己的舒适区。我前面说过，真正让我有能量的，是能看到公司各条线的整体推进，同时公司又小到我可以深入细节、跟具体团队一起干活。

我可以读实验结果，也可以看像素。综合这两点，我发现中型公司最适合我。不过这只是我个人的情况。像 Google 这种大公司，你会接触到极大的规模，这本身就很有意思。你能从很多同事身上学到最佳实践，工具和职能也非常齐全，可以学的东西很多。但它们通常更慢，产品更难真正推出来，这后来确实让我有点抓狂。
反过来，小创业公司速度非常快，但我在那些小公司长了很多白头发，因为没人认识你公司，所以招人要一个一个招，拉用户也得一个一个来。你确实能学得很快，也能做很多东西，但如果你想对世界产生真正的大影响，在特别特别小的创业公司里会非常累。
当然，有些公司最后会超高速成长，冲出来了。我不是来贬低这条路的，因为我自己也走过很久。但对我来说，我喜欢那种既能在规模上做贡献，又能以日常、周度节奏推进，而不是按月度、季度节奏推进的地方。
你说的中型公司，大概是什么规模？
就是我们在播客里聊到的这些公司，通常大概 500 到 1000 人。一般来说，它们已经运作了 10 到 20 年，比较稳健，最好也有盈利，领导层也不错，但还有很多维度值得继续探索。很多公司都正处在关键拐点上，所以也不会停滞不前。你还是得找一个有活力的地方。

Lenny Rachitsky大家听到这些实验和这些公司，看到的都是一路向上、一路成功。现实里你也提到过，很多事情并不会那么顺利。你能分享一个真正出过问题、失败过的故事吗？那次经历教会了你什么？

Albert Cheng先说，我在增长领域基本一直都在失败，所以我不太想挑某个具体的增长故事，因为那种失败对我的 ego 影响不大。但我职业早期做过很多核心产品工作。我待过一家叫 Chariot 的创业公司。你以前如果住过旧金山，可能见过它。

Lenny Rachitsky对，就是那个像巴士接驳服务的公司。

Albert Cheng对，就是那种蓝色通勤班车，大概 15 个座位，会从不同社区开到旧金山市中心。它介于公共巴士系统和 Uber、Lyft 之间，是一种通勤场景。我在那儿待过一段时间，负责产品。核心服务其实很受用户喜欢，稳定、速度快、价格也算可负担。但我们开始认真琢磨：如果能做一些更像 Uber、Lyft 的动态路线，是不是可以提高利用率，让服务更有新意？

司机本来是按固定路线开车的，但如果车上有空闲时间，是不是可以绕一下路，去用户家门口接人再继续往前开？于是我们试了这个方案，叫 Chariot Direct。这个尝试很有意思，但最后没有成功。我也从里面学到了不少东西。第一点是，这其实有点像“先找方案，再找问题”。你不能只因为“如果这么做会不会很酷”就上头，还是得先明确用户是谁、我们要解决什么问题、为什么这会让他们真的开心。
第二点尤其适用于 marketplace 这类业务，因为你面对的不只是一个终端用户。我们当时太把注意力放在 rider app 上了，却没有意识到司机承担了很多体验压力，我们的运营团队也同样承压。所以当司机感到困惑或者不爽时，最后会把整个产品体验拖得很辛苦。这是另一个教训。
第三点是，我们在产品正式推出前做了很多 PR，只为了先把声量打出去。PR 当然有它的用处，但如果你还没验证用户真的想要这个东西，就提前做宣传，风险其实很大。因为一旦声量起来了，你就会背上很重的沉没成本，反而会更想把事情硬做完。那已经是十年前的事了，说实话我在那家公司很开心，但我到现在还记得很清楚，因为它留下了三条以上非常关键的经验，后来我做很多产品时都一直带着。

Lenny Rachitsky对，感觉你当时是把“先实验，再告诉别人”这件事做到了另一个极端。

Albert Cheng没错。

Lenny Rachitsky对，我记得 Chariot 的车开到 Airbnb 办公室时，大家都在想：“这到底是什么？”

Albert Cheng没错。

Lenny Rachitsky太酷了。我都不知道你在那里待过。Albert，我们今天聊了这么多，基本上把我想聊的都聊到了。你在正式进入 lightning round 之前，还有什么想补充的吗？有没有什么你想留给听众的话？

Albert Cheng没有，这很棒。我希望这些内容对听众有帮助。过去几天我在准备这期播客时，说实话还有点焦虑，担心自己有没有足够多真正独立、足够深的框架可以拿出来讲。但后来我发现，老老实实讲这些公司里的真实经历就够了。我的很多经验，其实都建立在别人在类似问题上尝试成功或者失败的基础上。

我觉得重要的是，你得像一块海绵，能吸收各种不同做法，然后马上拿来实践，把不适合的丢掉，再根据自己和公司的需要去演化。我想，这就是我在准备这期节目时得到的一个新认识，也可能是我过去没有太多公开演讲的原因之一。

Lenny Rachitsky我太懂你的意思了。我离开 Airbnb 的时候也是这样，而且那是我 30 年职业生涯里第一次真正停下来休息。我突然在想：我到底学到了什么？我从来没有真正坐下来整理过“我学到了什么”。后来我写了那篇关于在 Airbnb 学到什么的 Medium 文，效果很好，然后这件事基本上就把我带到了现在。所以我很喜欢这次对话的意义，就是逼你把“我到底具体学到了什么”这件事说清楚。

Albert Cheng对，谢谢你给我这个机会。

Lenny Rachitsky是啊。在播客一开始、正式录制之前，我都会问嘉宾一个问题：你这次来的目标是什么？你想从这次对话里得到什么？通常大家会说，我们在招人，想让大家知道我们的公司，或者想拿到用户之类的。但你的回答只是：我想把我学到的东西回馈出去。我很喜欢这个答案。

Albert Cheng就是这样。

Lenny Rachitsky而且你也真的做到了。好了，我们进入很激动人心的 lightning round。我有五个问题给你，准备好了吗？

Albert Cheng准备好了。

Lenny Rachitsky你最常推荐给别人的两三本书是什么？

Albert Cheng老实说，我最近读的书不只是给我四岁的孩子读，也给我一岁的小孩读，所以我现在大部分时间都在读儿童绘本，努力逗他们笑。

Lenny Rachitsky等等，有没有特别喜欢的儿童书？我家现在也有两三岁的孩子。

Albert Cheng你刚才说你开始唱歌了。有一本叫《Snuggle Puppy》的书，里面有首歌，我女儿一听就笑得不行。

Lenny Rachitsky我的天。

Albert Cheng对我来说很暖心。不过如果要说我最近在工作里推荐过的一本书，那是《Ogilvy on Advertising》。你知道这本书吗？

Lenny Rachitsky这本我不太熟。我倒是听过一些营销原则之类的说法。

Albert Cheng对，很有意思。它虽然已经 40 年了，但里面满是 copy 和创意的实战例子，都是老派广告，不过 Ogilvy 用的是很偏实验的方式，去尝试很多东西。

我觉得这本书很好的一点，是它提醒我们：最终重要的，是促使用户采取行动，对他来说就是去买产品，对吧？重点不是做出多聪明的广告，或者多性感的创意，而是做出能推动行动的东西。我觉得这对很多产品和生命周期团队也同样适用。所以我会把它当成一个不错的推荐分享出去。

Lenny Rachitsky有没有电影或者电视剧？抱歉，你是不是还想分享另一本书？

Albert Cheng有，确实还有一本。

Lenny Rachitsky太好了，请说。

Albert Cheng我们 Chess.com 的联合创始人 Danny Rensch，在棋圈里很有名。他最近要出一本回忆录，叫《Dark Squares》，非常精彩。他小时候在一个有虐待性质的邪教里长大，后来又成了国际象棋神童。这个故事真的很不可思议。我现在读到一半，最大的感受是：有时候你以为你很了解一起工作的人，但你其实完全不知道他们的过去有多深。这本书应该会在这期播客发布前后出来。

Lenny Rachitsky书名叫《Dark Squares》？

Albert Cheng对，《Dark Squares》。

Lenny Rachitsky这个名字既指棋盘上的黑格，也让我猜到是在说那段艰难的过去。

Albert Cheng没错。

Lenny Rachitsky太厉害了。那最近有没有什么你特别喜欢的电影或电视剧？

Albert Cheng这阵子是橄榄球赛季，所以我都在看自己喜欢的球队的热评，也在看那些我又爱又恨的队伍的表现，挺忙的。

Lenny Rachitsky你支持哪支队？

Albert Cheng49 人队。我买了赛季票，经常去现场。上个赛季挺艰难的，希望今年能翻盘。

Lenny Rachitsky明白，很酷。那你最近发现过什么特别喜欢的产品吗？

Albert Cheng过去二十年里，我搬过很多次家，但一直都住在离咖啡店步行能到的地方。去喝咖啡已经成了我每天的仪式，算是我开始一天的方式。两年前我买了房，人生第一次住得离咖啡店不近，我为这事低落了好一阵子。

所以我最喜欢的产品就是我的那个意式浓缩咖啡机，它每天早上都能把我启动起来。我喜欢拿它做很糟糕的拉花，我觉得这件事本身就是一种提醒。怎么说呢，对我影响最大的产品，往往都是那些我每天都在用的东西，也都变成了日常习惯。

Lenny Rachitsky而且咖啡因最高。

Albert Cheng对，咖啡因最高，没错。

Lenny Rachitsky太棒了。你有没有一个经常会在工作或生活里反复想起的人生信条？

Albert Cheng我在想钢琴那段故事的时候，也想起我妈妈以前常说的一句话：没有什么比你的名声更重要。她经常这么说。我觉得这句话最宽厚的理解是：你每天做的那些小决定，你怎么对待别人，你怎么出现，你的品格是什么，等等，这些东西会慢慢累积，并在很多意想不到、也很美好的方式里给你打开机会。

我后来加入过的很多公司，其实都是通过相对轻微的关系链条连接上的。甚至今天上这档播客，我也重新见到了一些以前共事过的人。所以我觉得，做正确的事、建立好的名声，真的能带你走很远。反过来说，名声也很脆弱，对吧？如果你做错了事，修复起来会很久。所以这句话一直刻在我心里，我觉得这是一个很有意思的人生信条。

Lenny Rachitsky最后一个问题。你在 Chess.com 工作，你自己的棋下得怎么样？

Albert Cheng跟真正厉害的玩家比当然很糟，但和一般休闲玩家比还可以。我在 rapid 模式下的分数大概是 1800。

Lenny Rachitsky听起来挺厉害的。

Albert Cheng而 blitz 大概 1500 左右，不过我每天都会下很多盘。

Lenny Rachitskyblitz 是那种快棋吗？

Albert Cheng对，blitz 更快，一局大概三分钟。rapid 更像十分钟一局，也还是挺快的。

Lenny Rachitsky你说你一天会下好几次？公司允许你这么做吗？这就像……

Albert Cheng允许的。

Lenny Rachitsky哦，明白。在 Patagonia 有本很有名的书，创始人写的，叫《Let My People Go Surfing》。Patagonia 的规矩是，只要浪好，你就可以去冲浪。Chess.com 也是这样吗？

Albert Cheng完全是。

Lenny Rachitsky好。

Albert Cheng国际象棋本来就很有趣，所以我们一直都在下，公司里甚至还配有国际象棋教练。

Lenny Rachitsky教练是那种可以预约的吗？

Albert Cheng可以预约。我现在是每两周上一节课，确实帮我进步了不少。

Lenny Rachitsky哇，这应该会给你们带来很多招聘吸引力。专门留到最后说。Albert，这期太棒了，真的非常感谢你来。也谢谢你愿意把这些经验讲出来，回馈给大家。最后两个问题：大家如果想继续跟进这些话题，怎么找到你？听众又怎么能帮到你？

Albert Cheng谢谢邀请，这次聊得很开心。你可以在 LinkedIn 或 Twitter 上找到我。我发帖不算特别频繁，但我会经常看。如果今天我说的某些内容让你有共鸣，或者你只是想联系一下、交换些笔记，欢迎来找我。

Lenny Rachitsky那大家能不能在 Chess.com 上找到你来下棋？

Albert Cheng可以。

Lenny Rachitsky好，你愿意分享你的用户名吗，还是不想？

Albert Cheng我愿意分享。

Lenny Rachitsky不用，不用。

Albert Cheng我刚才不是说了我是 49 人队球迷吗？所以我的用户名就是 Go9ers。

Lenny Rachitsky哇。

Albert Cheng我估计接下来会收到很多对局请求。

Lenny Rachitsky这就来了，这就来了。1800。Albert，再次非常感谢你来到这里。

Albert Cheng谢谢你。

Lenny Rachitsky各位再见，非常感谢收听。如果你觉得这期节目有帮助，欢迎在 Apple Podcast、Spotify 或你常用的播客 App 里订阅节目。也请考虑给我们打个分或者留个评论，这样更容易让其他听众找到这档播客。你可以在 lennyspodcast.com 找到往期所有节目，也能了解更多节目内容。我们下期见。

Lenny Rachitsky你说你一天会下好几次？公司允许你这么做吗？这就像……

Albert Cheng允许的。

Lenny Rachitsky哦，明白。在 Patagonia 有本很有名的书，创始人写的，叫《Let My People Go Surfing》。Patagonia 的规矩是，只要浪好，你就可以去冲浪。Chess.com 也是这样吗？

Albert Cheng完全是。

Lenny Rachitsky好。

Albert Cheng国际象棋本来就很有趣，所以我们一直都在下，公司里甚至还配有国际象棋教练。

Lenny Rachitsky教练是那种可以预约的吗？

Albert Cheng可以预约。我现在是每两周上一节课，确实帮我进步了不少。

Lenny Rachitsky哇，这应该会给你们带来很多招聘吸引力。专门留到最后说。Albert，这期太棒了，真的非常感谢你来。也谢谢你愿意把这些经验讲出来，回馈给大家。最后两个问题：大家如果想继续跟进这些话题，怎么找到你？听众又怎么能帮到你？

Albert Cheng谢谢邀请，这次聊得很开心。你可以在 LinkedIn 或 Twitter 上找到我。我发帖不算特别频繁，但我会经常看。如果今天我说的某些内容让你有共鸣，或者你只是想联系一下、交换些笔记，欢迎来找我。

Lenny Rachitsky那大家能不能在 Chess.com 上找到你来下棋？

Albert Cheng可以。

Lenny Rachitsky好，你愿意分享你的用户名吗，还是不想？

Albert Cheng我愿意分享。

Lenny Rachitsky不用，不用。

Albert Cheng我刚才不是说了我是 49 人队球迷吗？所以我的用户名就是 Go9ers。

Lenny Rachitsky哇。

Albert Cheng我估计接下来会收到很多对局请求。

Lenny Rachitsky这就来了，这就来了。1800。Albert，再次非常感谢你来到这里。

Albert Cheng谢谢你。

Lenny Rachitsky各位再见，非常感谢收听。如果你觉得这期节目有帮助，欢迎在 Apple Podcast、Spotify 或你常用的播客 App 里订阅节目。也请考虑给我们打个分或者留个评论，这样更容易让其他听众找到这档播客。你可以在 lennyspodcast.com 找到往期所有节目，也能了解更多节目内容。我们下期见。