How Anthropic Runs Growth From Inside a 10x-a-Year Curve: Amol Avasare on Big Bets, Automated Experiments, and the Squeezed PM
Lenny's Podcast
Amol Avasare leads growth at Anthropic. On this podcast, host Lenny Rachitsky put the company's trajectory at roughly $1 billion in annual recurring revenue at the start of 2025, about $4 billion by mid-year, $9 billion by year's end, and $19 billion shortly after. That is 1x to 19x in about 14 months. Lenny's central question is what a growth team does at a company whose product seems to sell itself, and how that work changes when the models can start doing parts of it. Avasare's answer mixes modesty with specifics. He says the growth team deserves only a small share of the credit. He also says the job is the hardest he has had, that it forces a different balance between big bets and small optimizations, and that Anthropic is already using Claude to automate pieces of growth experimentation, product management, and management itself.
Getting the job by cold email
Avasare says his path into Anthropic matched none of the categories shown at employee onboarding: referral, website application, or recruiter sourcing. He was a heavy Claude user who concluded that the company "obviously" had no growth team. He sent a cold email to Mike Krieger, then chief product officer, saying he loved the product, thought Anthropic badly needed a growth team, and wanted to talk. No growth roles were listed, but Anthropic was just starting to think about hiring for one, so the timing worked. Avasare says Krieger told him he is the only PM Krieger has hired from a cold email.
Avasare says he refined cold email over years as a founder. He tested subject lines until he had one with a "very, very high open rate," and declined to share it. He also tries to reach people through channels that are less crowded than LinkedIn or work email, which in this case meant finding Krieger's personal email. The message itself stayed short: who he is, why he'd be a good fit, and a request to chat. His rule is to keep following up until the person asks him to stop. Here, Krieger replied to the first email.
What the growth team actually does
Avasare begins by limiting how much credit his team can claim. He describes Anthropic as "a model company and an intelligence company first," and says most of its success comes from research, inference and compute, and teams such as Claude Code and marketing. He notes the roughly 10x yearly revenue pattern has held since the start: zero to about $100 million in 2023, $100 million to $1 billion in 2024, and $1 billion to roughly $10 billion in 2025.
He recalls joining in 2024, when revenue was in the hundreds of millions. In his second week, the company was planning 2025 revenue with base and aggressive scenarios. He says Dario Amodei pushed the aggressive case, people asked how they could possibly hit it, and Dario said he thought they could go much higher. Avasare was sure it couldn't happen, and it did. By late 2025 he expected growth to slow simply because the base had become so large, and he says it hasn't. He adds that the $19 billion figure dates from the end of February and is already stale. Internally, he jokes, "linear charts are just not cool." People want everything on a log-linear scale.
The categories of work look like any growth team's: acquisition and the intent of incoming users, activation (sign-up flow and routing people to the right product), and monetization (free-to-paid conversion, pricing, packaging). The difference is how the time splits. Avasare estimates about 70% of his time goes to what Anthropic calls "success disasters," where things have gone so well that other things break. He compares it to early Facebook, Uber, or DoorDash. The work is constant firefighting across all three categories, and he says it can be emotionally tough even while "all the charts are green." The remaining 30% is proactive: deciding which of many products deserve growth investment, working out long-term pricing and packaging while technology and engagement patterns shift, and judging when a new product like Cowork is ready for the growth team to optimize its adoption funnel.
Why activation is the hardest problem in AI
Asked about the feature that let users import their memory from ChatGPT, Avasare framed it as one example of a broader effort on the cold-start problem. The goal is to make it easy for Claude to understand who a new user is and how it can help them. He calls activation "a really big challenge in AI."
He says early activation, the day-zero and day-one experience, has always been among the highest levers for long-term retention, and that its importance has grown "exponentially." The industry-wide problem he describes is a "capability overhang": models improve faster than people can absorb. Even inside Anthropic, he says, busy employees have to set aside time with each new model to update their assumptions about what it can do. For most people, a model might be capable of remarkable things, but if their instinct is to ask "what's the weather in SF?", they won't get much from it.
This makes onboarding a moving target. He walks through the cycle. A model like Opus 4 has a set of capabilities, and Opus 4.5 unlocked a new set. By the time the team has tested on-ramps for one model's capabilities, learned from the results, and shipped a new flow, the next model may have arrived and made those learnings irrelevant.
Some old principles still hold for him. The highest leverage comes from matching the right product or feature to the right user. The right kind of friction helps.
Mercury: quality as a growth lever
Lenny mentioned that Anthropic co-founder Ben Mann had pointed to Avasare's onboarding work at Mercury. Avasare explains that Mercury's core value proposition is simply a better banking experience, and the company holds that ethos deeply. Onboarding for a regulated financial institution, though, is complicated. He recalls how much time he spent on the differences between a registered agent address, a legal address, and a physical address.
The team noticed it had invested heavily in quality across the product but not in the flow that is everyone's first experience. So for one quarter, the conversion-focused growth team set metrics aside and worked only on the quality of that flow. That included fixing problems like moving back between fields and entering beneficial ownership details. Avasare says that until he joined Anthropic, it was the single most impactful quarter he had had on a growth team, with a significant lift in onboarding completion. He took away the lesson that "quality drives growth," and says he has tried to bring it to Anthropic.
Good friction versus bad friction
Anthropic's onboarding asks users who they are and what they're interested in, then uses the answers to recommend products and features. Avasare says people look at it and complain about the friction and length. His reply is that the team has the data and is happy with how it performs.
He says that at every growth job he has held, adding the right steps increased conversion and funnel completion. The common instinct to cut every step and minimize time to value "doesn't work most times" when flows are tested thoroughly. His examples are MasterClass, whose purchase flow includes a quiz about why you came, which he says was thoroughly tested and was a significant revenue driver because it makes users feel the product is for them. Calm, where a former growth PM from his team went, also uses a quiz. At Mercury, splitting a screen with five or six form fields into two screens reduced cognitive load and performed well. His rule: cut friction that doesn't help users understand why the product is for them, and don't shy away from friction that does, but test it for your own business.
He adds that knowing who the user is pays off further down the funnel. It informs lifecycle messaging, and in more sophisticated businesses it enables lookalike targeting at the ad layer to reach people who dropped off. On competitor teardowns, he suggests Cowork with the Chrome extension can browse other companies' flows and report what works.
Org structure and the 70/30 flip toward big bets
The growth team is about 40 people, a mix of engineers, designers, PMs, and data. It has horizontal teams, growth platform and monetization, that work across all products, plus audience-focused pods such as B2B growth, Claude Code growth, knowledge-worker growth, and API growth. Avasare says a single funnel-stage team works when there is one product. With many products serving different audiences, and each with different internal partners, audience focus matters more. The Claude Code growth team, for example, works very closely with Cat and Boris and others on that product. He calls the structure imperfect and right "for a point in time."
The biggest difference from a traditional growth team is the balance of bets. At past companies he would have spent 60–70% of his time on small and medium bets and 20–30% on large swings. At Anthropic it is roughly flipped, 70/30 or closer to 50/50 in favor of bigger bets. Lenny pointed out that at Anthropic's scale a 1% win is enormous. Avasare agreed the team could stack small optimizations and tally up impressive quarterly impact, but said the company's fixation on "the exponential" pushes it the other way.
His reasoning: as model capabilities rise exponentially and the surrounding tools get better at turning them into useful applications, new markets keep opening that dwarf earlier ones. Agentic coding, he says, didn't exist a year and a half ago and is now bigger than the previous AI-coding market. He contrasts this with a typical grocery delivery or trading app, where he guesses a user might get 30–50% more value two years from now if the company executes well. A growth team there can capture much of that gap through small, high-conviction optimizations. For Anthropic, he estimates the product value two years out is "a hundred to a thousand X" today's, so missing the forest for the trees is the bigger risk. The team still does small optimizations, because their compounding matters and no one else will do them.
His example is the Claude Chrome extension, which he says now underpins a number of use cases in Cowork and Claude Code. The growth team built it, driven by one engineer who was bullish on a research-heavy, AI-native product that no one else was pursuing. He says he wouldn't have made that bet at another company.
He limits the lesson to products whose core value comes from AI, naming Lovable and Cursor as examples. For products with AI features on the side, he isn't sure this approach applies. It would depend on how the rest of the product and growth functions are staffed.
CASH: automating growth experiments with Claude
The development Avasare seemed most interested in is an effort to automate growth itself. The growth platform team, led in this effort by Alexey Komissarouk, who teaches growth engineering at Reforge, runs a project called CASH: "Claude Accelerates Sustainable Hypergrowth." Avasare calls the name "a little cringey" and says he didn't come up with it.
He stresses that it is very small and very early. It started a couple of months ago. He says it wasn't really possible before Opus 4.5, and with Opus 4.6 the team felt it was "headed in the right direction." He thinks growth is a natural early target because so much of the work consists of small optimizations.
The team breaks the shipping lifecycle into four stages and scores Claude on each, so each can be evaluated and improved:
- Identifying opportunities from trends and past patterns.
- Building the feature and getting it ready to ship.
- Testing that it meets the quality and brand bar.
- Analyzing results and gathering learnings after launch.
So far it has mostly produced copy changes and minor UI tweaks. Avasare says it is delivering results and "ultimately prints money." He puts its win rate at what he'd expect from a junior PM two or three years into the job, not yet a senior PM. He notes this wasn't possible at all a few months earlier and expects it to extend to larger experiments over time.
Right now a human approves experiments. Avasare says he tracks progress week over week: whether results are improving in each stage and whether people are spending less time on each. He expects much of the human review to become unnecessary. Brand review, for example, could be handled by a skill containing brand guidelines and clear do's and don'ts, which models will get better at using.
He named a fifth piece that the four stages leave out: cross-functional stakeholder management. This is why he doesn't think PM work is going away soon, at least for larger projects. He recalled debriefing a difficult meeting with his head of design, Joel, who said that even with AGI it will still be impossible to get six people in a room to align. Lenny noted that AI started in the middle of product development, with writing code, and is now spreading outward to deciding what to build. He suggested growth, being data-driven and loop-shaped, is where that starts.
Why the PM-to-engineer ratio may flip
Avasare says the question of how the PM–engineering–design triad changes comes up constantly at Anthropic, and the picture shifts quickly. At a 15–20-person startup, he expects roles to blend heavily, with the PM designing and shipping. At larger organizations he calls it undecided, and says people inside Anthropic disagree.
His current view is that all three roles are gaining leverage from AI, but engineering is gaining the most, especially from Claude Code. Take a default team of five engineers, one designer, and one PM. If the engineers are two to three times more productive, the team effectively has 15–20 engineers of output with the equivalent of one and a half to two PMs and designers. He says this is putting a lot of strain on PM and design. Claude Code is an exception, because the product is so technical that its PMs are essentially engineers. At a recent PM leads offsite, he says, the shared feeling was that PM and design are "absolutely squeezed," and the group discussed whether the answer is to hire many more PMs. He thinks that could be where things end up. The growth team is hiring PMs.
The other response is to lean on product-minded engineers. The growth team uses a rule: if a project takes two weeks of engineering time or less, the engineer acts as PM. That means talking to security, legal, and other stakeholders, with the PM advising and stepping in only if things go badly off track. Above two weeks, the PM stays accountable while delegating more. It isn't strict. A one-week project that is highly controversial should still be driven by a PM. He expects more companies to deputize engineers as "mini PMs," and says product-minded engineers' value has gone up by "an order of magnitude."
That shapes how he thinks PMs should spend their time. At small or budget-constrained companies, he says PMs should ship code, and PMs everywhere should build things to learn the tools. At scaled companies with 20 engineers per PM, he questions whether shipping the "21st feature" is the best use of a PM's time compared with improving the team's "why and what" by even 5%, which he calls extremely high leverage. When Lenny added that prototyping is also a way to form and communicate opinions, Avasare agreed and said he often prototypes to show an idea instead of describing it.
Skipping the PRD, keeping the kickoff
Avasare says Anthropic is "extremely scrappy" despite its size and that he is "averse to PRDs." He estimates 60–80% of what the team ships has no PRD. Small changes, such as an upsell for an upcoming launch, are worked out in Slack messages with capable engineers who push back on audience questions. The two-week rule serves as a filter for when more thinking is warranted.
For larger projects, he insists on a proper cross-functional kickoff. It is a 30-minute meeting with legal, safeguards, and others, where the team says what it plans to do and asks each group what it cares about. He considers this important because "no one knows what's going on" at a company moving this fast. Sometimes he skips the document entirely. Sometimes he asks Claude to draft a basic doc five minutes before the meeting. When he does write a PRD, he uses a skill he built, plus a project containing past PRDs, and gives Claude the why, the problem, and key considerations to expand. More and more, he goes straight to a prototype.
Using Cowork to find misalignment and read the metrics
Avasare described several ways he uses Claude day to day. One he finds most valuable is spotting misalignment. With Claude connected to Slack through MCP, he tells it which projects he's working on and what matters to him, and asks it to find potential misalignments. The task runs every week on a schedule. He says it does "a really, really good job," and imagines a version that warns someone before a launch about who they need to talk to. He says Scott, who leads Anthropic's enterprise team, found a few major misalignments this way that would have led teams to waste effort or duplicate work. He thinks cross-functional coordination is often the constraint on shipping at a large company, and that using AI to reduce that toil wasn't possible six months ago.
For metrics, a scheduled task in the Cowork desktop app reviews 20–25 charts each morning. It uses Hex links, the Chrome extension, and MCP connections, then tells him what needs attention, what is concerning, and what is interesting. He still looks at a few charts himself because he likes charts. The value is in covering the long and medium tail he wouldn't check daily, and his confidence grows as false positives and false negatives decline. Lenny floated the idea of a "strategy bot" that watches metrics, the market, and the roadmap and recommends pivots. Avasare guessed, calling it his "gut," that this will become very effective later this year.
He also hands off administrative work: booking meeting rooms, a first pass at archiving email, and filing reimbursements and expenses in Brex.
An AI version of your manager
The management uses surprised Lenny most. Each week, Avasare has Claude review what each direct report did, the team's goals and OKRs, and transcripts of their conversations, then suggest observations and feedback. He calls the quality "hit or miss": sometimes decent, sometimes wrong in ways that make him wonder why it raised something, and sometimes catching something he's very glad he noticed. He compares it to a coach who is "kind of drunk at times."
He runs the same process on himself. His manager, Ami Vora, has written a lot publicly about product. He asks Claude to act as her, drawing on her public writing, internal material, and their discussions, and to give him feedback based on what he did or didn't do that week. Another option is asking Claude to read everything a manager said in Slack in the past week and infer priorities he isn't aware of. He calls this layer "soft coaching" and considers it already usable. To set it up, he says you download the Cowork desktop app, connect the Slack MCP (which may require a team or enterprise admin to enable), and ask Claude.
Focus on coding and B2B as strategy and necessity
Lenny noted that Anthropic has focused narrowly on B2B and coding. Avasare says that focus goes back to the company's founding and comes from leadership. He mentions recently seeing a 2021 document by co-founder Ben Mann, written a few months after the company started, arguing that Anthropic should focus on AI coding. That was long before anyone knew how big the market would be.
He gives two reasons. One is commercial. The other is research acceleration: better coding models speed up the research loop that produces better models. He says this is now a common view across labs, but Dario has seen it clearly for years and has discussed it publicly.
The second driver, he says, was necessity. Anthropic was "the smallest, least well-funded player in this space," without the free cash flow or distribution of Meta or Google and without OpenAI's first-mover advantage. He calls where the company is now "a complete miracle." He ties this to a personal principle he calls "freedom through constraints": constraints remove excess choice and make the path clear. He also offers a counterfactual. Before his time, he says, Anthropic had a chatbot before ChatGPT launched but chose not to release it for safety reasons, because the team didn't want to start an AI arms race. ChatGPT's traction then pulled OpenAI toward consumer. If Anthropic had launched first, he says, things might have gone the other way. "It's always hard to say looking back."
Growth under a safety mission
Asked how a growth team fits into a company built around AI safety, Avasare pointed to Anthropic's structure as a public benefit corporation. He says that structure lets it legally state that maximizing shareholder value is not its overriding goal. He describes the mission as making sure the transition to powerful AI goes well for humanity, and says the company has repeatedly accepted significant commercial hits for it, with the unreleased early chatbot as an example.
For controversial growth tests, he uses two categories. The first is tests so controversial that the results don't matter because you would never ship them, for reasons of brand, customer friendliness, or values. For Anthropic, safety sits there. The second is tests he dislikes but that aren't red lines. He'll let someone with a strong hypothesis run those, but the more uncomfortable the idea, the bigger the return he wants to see.
He thinks a common mistake among hardcore growth practitioners is trying to squeeze out every last dollar. He compares it to founders who maximize a raise and lose investors' goodwill. His team is "very comfortable forgoing metric impact" to protect safety, brand, the quality bar, and user experience. He believes the best products work this way and that it drives more long-term growth. He predicts that as the stakes rise, Anthropic's safety stance will become a significant competitive advantage.
When Lenny raised criticism that Anthropic's warnings about AI risks and job losses are fear-mongering to raise money or get headlines, Avasare made three points. People reasoning linearly will underestimate how soon things arrive, while an exponential view makes them look closer. Internally, people believe these things more strongly than they say publicly, and external statements are sometimes softened so they don't sound over the top. Finally, echoing Ben Mann, he talks about a "race to the top": critics on the sidelines have no influence, while a leading, commercially successful player can push others in the game toward better practices. He adds that most people at the company are optimists who think the good outcome isn't guaranteed and too few informed people discuss the risks productively.
Advice for thriving as a PM or growth person
Avasare's first piece of advice is common but, he says, essential: use the tools, including Claude Code and Cowork, and retest with each model release. Something that failed on one model may work on the next, and if you don't go back, months can pass without you knowing. This also builds product sense for AI products.
Second, lean into where you have an unfair advantage and "almost forget the weaknesses." Some PMs excel at craft, others at getting a room full of strong-willed stakeholders moving the same way. Third, be interdisciplinary. A highly product-minded engineer is "an absolute unicorn," and so is a PM who can design when designers are stretched, and those people are much harder for a company to let go. He credits his own mix of founder, investment banking, and near-sales experience. He almost became an account executive instead of going into product. He also cites Nick Lin, who runs Anthropic's financial services products, including Claude for Excel, and came from investment banking and private equity.
Finally, be adaptable. He tells people joining Anthropic that "50, 60, 70% of how you operated in the past" should be thrown out, and that clinging to old playbooks creates a lot of friction.
Culture: notebook channels and talent density
Avasare calls Anthropic's culture its "secret sauce" and the hardest thing to replicate. He credits deliberate investment by Daniela and Dario Amodei. He admits he was skeptical when he joined, since he knew no one at the company, and says he found people were even more serious about the mission internally than externally. He says he hasn't met a single employee who is checked out, which is different from every previous job.
He describes an open Slack culture built around "notebook channels," which are personal feeds, something like an internal Twitter, where everyone shares their thinking. You can follow researchers' channels and learn about almost anything. People are encouraged to challenge leadership publicly. He recalled someone who disagreed with how Dario said something at an all-hands, posted about it in Dario's notebook channel, and started a big debate. For leaders, the channels also help spread principles as the company grows quickly. He cited his own recent post on the importance of leaving money on the table, which new growth engineers read and learned from. These documents also feed Claude. He says some onboarding documents carry HR notes asking people to check before editing because Claude references them.
On talent, he says he sometimes feels like he plays for Real Madrid. He names Ami Vora, Mike Krieger, his engineering counterpart Johnny, and Alexey Komissarouk. At a company offsite in October he met a man walking around alone eating popcorn and recognized him as Jeff, the former U.S. ambassador to Avasare's home country of Australia, now an employee.
Lenny asked why a company capable of building nearly anything still uses Slack, Workday, and Figma. Avasare called it "a really complicated picture." Anthropic builds some things internally, and Claude's ability to do so is growing, but he uses those products heavily, doesn't expect that to change soon, and thinks claims that such SaaS products will be replaced are partly overblown.
Failure: shutting down a funded startup
For "failure corner," Avasare described shutting down his startup. He and his co-founders spent three years on it, raised a couple million dollars, and peaked at seven to ten employees. The company worked on quantifying mental health to find early predictors of conditions such as generalized anxiety and major depression. He says they were in their early twenties and had "no idea what we're doing," and that he would do many things differently.
His practical advice to founders is to send monthly investor updates even when things are going badly, because it avoids surprises, though he says the final call to announce the shutdown is still brutal. He says it took him years to get over it. Looking back, he credits the experience with teaching him the product skills and the cold emailing that made his later career possible, and says he is now grateful it failed the way it did.
The brain injury and "freedom through constraints"
In 2023, Avasare wrote a guest post for Lenny's newsletter about how a traumatic brain injury made him a better PM. In early 2022, after years of MMA and Muay Thai, he took a kick to the head during an ordinary sparring session. He was off work for nine months, and it took about half a year before he was comfortable walking. For the first two to three months, his wife did everything beyond showering and using the bathroom, including texting his friends. About 20 seconds of music made him nauseous, and he couldn't look at screens. For a while it wasn't clear he would work again, and they discussed what they would do if he couldn't. Recovery meant slowly raising his tolerance to each stimulus without pushing so hard that he had a setback.
He also shared something Lenny didn't know. About a month after the post was published, and a month into his job at Mercury, he was reinjured when bags hit his head while he was getting off a plane. He explains that until a brain injury is fully healed, the risk of another one stays elevated. That led to another long leave and recovery. He says he is still not 100% healed and sometimes has dizziness and headaches that he works around.
Even so, he calls the injury one of the best things that could have happened to him, while acknowledging that such a view can be taken to the point of denying reality. He doesn't drink alcohol or caffeine. He takes a short break every morning and afternoon, even on model launch days, often in the office meditation area. He does at least one meditation retreat a year, and Lenny mentioned both have attended Spirit Rock. He describes a gap between awareness and reality, and says "reality's insane" at Anthropic. Deep meditation, he says, taught him to find choice in that gap, which helps him keep a level head without unhealthy coping mechanisms.
He returned to the theme of freedom through constraints. During the injury he did everything he could, including diet and exercise, but faced a choice between fighting reality and suffering, or accepting it and not letting outcomes decide his happiness. He cited a meditation teacher who said true freedom is learning to be content when you don't get what you want. He says he isn't perfect at it, but calls it perhaps the biggest lesson of that period.
Lightning round
Avasare recommended The Joy of Living by Yongey Mingyur Rinpoche, Awareness by Anthony de Mello, and, for product work, Thinking in Bets by Annie Duke, whose habit of putting a probability on vague claims like "I don't know if it'll get done in time" he finds useful. His recent favorite movie was Marty Supreme, and his TV pick was the Olympics. His favorite product was a bead-filled pillow from a Japanese hotel whose height adjusts as he sleeps. He named it as a Maruhachi pro pillow, available in Japan and shipped to the U.S. His mottos are the Australian "she'll be right," and "sometimes in life you just have to go for it," a push he credits to Eros Resmini, former CMO of Discord and an advisor during his founder years. With little time for hobbies, he watches football as a Michigan Wolverines and 49ers fan, a habit that started when his wife took him to a game at the Big House.
He closed by saying the growth team is hiring across engineering, product, and design, and asked listeners for harsh feedback on Anthropic's products and referrals of strong candidates.
A lot of companies claim to be the fastest-growing companies of all time, and Anthropic actually is.
You guys were at a billion ARR at the start of 2025. The last number I've seen is 19 billion ARR. That's 1 to 19 billion dollars in 14 months.
Historically, we were very much the smallest, least well-funded player in this space. We didn't have the free cash flow or the distribution of a Meta or Google. We didn't have the first-mover advantage of an OpenAI. It's a complete miracle that we've gotten to the stage that we have.
Give us just a glimpse of what it's like to be leading growth inside of Anthropic.
It's the hardest job I've had in my life. You come into Anthropic, you need to understand that 50, 60, 70% of how you operate in the past, just throw it out the door.
One of the cleverest growth moves you all made was this idea of importing memory from ChatGPT.
Activation is a really big challenge in AI. We are starting to look at how do we automate growth? Our growth platform team is driving this effort called CASH, which is Claude Accelerates Sustainable Hypergrowth. How can we use Claude to automate growth experimentation? And it's delivering results.
You're basically living in the future.
We always talk about the exponential. The product value that we will deliver in 2 years' time is probably like a thousand X what it is today. The funniest thing is I've noticed internally, linear charts are just not cool. Everything is log-linear, so show me it log-linear scale.
Today, my guest is Amol Avasare. Amol is head of growth at Anthropic, which is on the most unprecedented growth run in history. In the past 14 months, they grew from 1 billion to over 19 billion in annual recurring revenue. Just in the past few months, their revenue doubled. They've been growing 10X year-over-year. This is unheard of at this scale. By the time this episode comes out, their revenue will be even higher. To put this scale in perspective, companies like Atlassian and Palantir and Snowflake, which have been around for 15 to 20 years, each do something like 4 and 1/2 to 6 billion in ARR. Anthropic is adding this much ARR every few months.
And if that isn't interesting enough to you, Amol, who leads growth at Anthropic, is an incredible human. He previously led growth at Mercury and MasterClass. Before that, he was a founder and an investment banker. And most interestingly, something that most people don't know about him is that Amol suffered a severe brain injury. He had to spend 9 months relearning how to walk and work and just not be nauseous all the time. He shared this story in a guest post in my newsletter a number of years ago. We actually chat about this during the conversation.
These are my favorite kind of conversations because Amol and his team are living in the future, and he's come to tell us where things are heading and what's going to change. And in this episode, Amol shares an unprecedented look at how a company like Anthropic operates and grows, including how they think about growth, what parts of the job they've automated, the future of the product and growth roles, how Amol got the job in the first place by cold emailing Mike Krieger, and so much more. Amol is wonderful, and just try to count the number of times that he blew my mind during this conversation.
Before we get into it, don't forget to check out lennysproductpass.com for an incredible set of deals available exclusively to Lenny's Newsletter subscribers. With that, I bring you Amol Avasare.
Amol, thank you so much for being here, and welcome to the podcast.
Glad to be here.
Head of growth at Anthropic. No big deal. I've had a lot of people come on this podcast from companies that claim to be the fastest growing companies of all time, and Anthropic actually is if you look at the trajectory. I just have some of the numbers here just so people understand how absurd this is. So, you guys were at a billion ARR at the start of 2025, then hit something like 4 billion mid-2025, then 9 billion ARR at the end of 2025. And the last number I've seen is you guys are at 19 billion ARR. Which, just to put a couple pieces of context here, one is that's from one to 19 billion dollars in 14 months. I have so many questions. First of all, the story of how you actually landed this role is really interesting. Talk about how you got this role.
Yeah, it's a little unorthodox. So, it's funny, when I did my onboarding they walked through what percentage of the cohort came through referrals, what percentage came through applying on the website, what percentage came through sourcing, and I was in none of those. And I was like, "Okay, this is interesting." Basically the way that I got to Anthropic was that I was actually a user of Claude, and I was using it a lot. I was like, "Man, these guys, great product, great company, but they obviously don't have a growth team." And what I did was I just sent Mike Krieger a cold email. He was the chief product officer. I sent him a cold email saying like, "Hey, love what you guys do, love the product. I think you guys badly need a growth team. Want to chat?" And I didn't expect he would respond. And, you know, he responds and says, "Hey, yeah, I'm interested. Let's talk."
And it's funny, I wouldn't have known they were not hiring for a growth team. There were no growth team roles listed. But they were just at that time starting to think about hiring a growth team. So, it was very good timing, but yeah, spoke to Mike, and one thing led to another. He said I'm the only PM that he's hired from cold email. And I feel very lucky that he decided to respond to my email.
I did not know the story. That is another absurd fact. Clearly you're good at cold email. What did you do in this cold email to get his attention?
I would say I've basically perfected cold email over the years. So, when I was a founder, I had to get really, really good at this. So, I sent a lot of cold emails out and just honed the subject lines and message and the tone. And so, basically, in the subject line, the first thing is, from a conversion standpoint, someone sees the email, they need to click on it. And so, I have a copy that I've tested that is very, very high open rate. And so,
Wait, what is this copy? Or is this a secret?
It's a secret. I think
Okay, we'll keep it. We'll kind of keep
Yeah, it's a secret. So, that's one, getting them to open. I think the second is then the tactics of, you need to understand where are people getting outreach. And if everyone's getting outreach in one area and then you reach out to them there, then you're not going to get as high of a response rate. So, you can think about LinkedIn, you can think about work email. These are things that everyone is emailing. So, there's ways to get people's personal emails out there. And so, that's one thing that I did. And so, okay, I've got his personal email, I know the copy that works. And then it's just keeping it very short on here's who I am, here's why I'd be a good fit, and we should chat. And, you know, these things typically don't work. And then you should always follow up a few times. I think my rule of thumb is if I really care about it, I should just keep reaching out to them until they tell me, "Please stop." And so, I would have kept doing that, but he responded the first time.
It makes sense that a talented growth person would be very good at cold email and getting people's attention. So, that's almost like an interview step, is just did I want to read this email?
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Okay. So, give us just a glimpse of what it's like to be leading growth inside of Anthropic right now, by far the fastest growing company in history. Just what is it like?
Yeah, I'd say it's very much a company-wide effort, right? So, I guess we are the growth team. We have done great. I think we've driven a lot of impact, but honestly, man, we can't claim too much credit for the success of the company. We as Anthropic are really a model company and an intelligence company first and foremost. And so, the lion's share of what has driven our success is our research team. We have, I think, the best research team in the world. We have great teams on inference and compute. And then there's many other teams like Claude Code, go-to-market, etc. who I think deserve much more credit than us.
And I think, zooming out, going to some of what you said earlier, the growth trajectory has just been insane. That 10x year-on-year revenue growth trend has been there since the beginning. I think 2023 was zero to 100 mil. 2024 was 100 to one. Last year was one to roughly 10. And then I look back to when I joined in 2024, revenue was in the hundreds of millions. And just that trajectory to the end of 2024 and 2025, like week two of when I joined, we're going into 2025 revenue planning and we have these base case and aggressive case scenarios and Dario's pushing the aggressive case scenario and people are freaking out being like, how the hell are we going to hit that? And Dario's like, I think we can actually go much higher than that. And I'm coming in like, this place is crazy, there's absolutely no way. And that happened, right?
And then you get to the end of 2025 and it's like, okay, law of large numbers, there's going to be a pretty big slowdown here based on, you know, your baseline rate of 10 billion, how are you going to keep growing at this rate? And it just has not slowed down. And, you know, these numbers are public. The 19 billion number you quoted is from the end of Feb. So that is also out of date. And look, it's absolutely insane. The funniest thing is something that I'm noticing internally is linear charts are just not cool. No one cares about linear charts. Everything is log-linear. Show me it log-linear scale, and that's kind of the scale we think. And I think overall we're just, you know, really hanging on by the seat of our pants and we're trying to manage the growth and do the best that we can for our users.
I was talking to somebody at Anthropic about you and they said that basically anytime they want something to grow, they ask you to help and it works. So you talked about how things are magical and amazing, and Claude and all the tools you all built are amazing innately and that's a big part of the reason they grow. I think many people listening to this will be like, what do you actually even do, Amol, with a magical micro god that can just do anything for you? Why do we need a growth person? What do you even do? Talk about just the stuff that you focus on and maybe a couple of the wins that your team has shipped that have helped accelerate growth.
I would say they're not fully wrong, right? We're very, very lucky to have the best models in the world. We're very lucky to have products like Claude Code and Cowork. It certainly makes life a lot easier. Having said that, I would say this is the hardest job I've had in my life, and that's, you know, having been a founder, having been an investment banker and other things like that. It's tough. And if I look at what do we do as a growth team here? I think ultimately it's the same categories of things that you would think about at a normal company. So, we care about acquisition, how are we getting more people in the door, what's the intent of the people coming through the door. We care about activation, the sign-up flow, funneling people to the right products, making them successful. You know, we care about things like monetization, free to paid conversion, pricing and packaging, all of that stuff. The categories of work are the same.
I think then probably the big difference is I would say that roughly 70% of what I spend my time on is what we internally refer to as success disasters, and that is where things have gone so well that other things are breaking now. And I think anyone who's worked at companies that have gone through rapid growth, things like Facebook or Uber or DoorDash early on, they understand this viscerally, where scaling this much just brings a lot of challenges. If you think about each of those categories, on acquisition, on activation, on monetization, there's just a ton of firefighting, jumping from one urgent thing to another, and it's often extremely painful. And it's funny because you look at all the charts, all the charts are green, fully up and to the right, and it can be quite tough emotionally still. And so, you need to sort of step back and just realize that we're very lucky to have these problems. But that's sort of 70% of my time, I'd say, is just this firefighting of success disasters.
And I think the 30% remaining is just much more standard bread and butter growth work where it's more proactive. So, you think about, okay, if we have limited resources, we have many different products, which are the products we want to put some juice behind? What does our long-term pricing and packaging look like? Especially given that the technology is changing a lot and behavior and engagement trends are shifting. And then, you know, things like, we have a lot of new products coming up. Like, okay, you shipped Cowork. Now what? When is the right time that we should lean in as a growth team to start optimizing the core adoption funnel for Cowork? So, it's very much 70% just crazy firefighting, 30% more bread and butter stuff.
Okay, I'm going to dig into a lot of that stuff. One of the cleverest growth moves you all made recently was this idea of importing memory from ChatGPT, where you just made it really easy and kind of jumped on this trend of people getting really excited about Anthropic. Is there anything you could share about the behind-the-scenes story of that feature?
We were always thinking about what can we do to improve the cold start problem and improve the new user experience. I think that activation is a really big challenge in AI. And so, you know, that's one example of something that we shipped that was very, you know, specific to a moment in time. But ultimately, you zoom out, it's like, okay, how do you really make it easier for people who are signing up to have Claude understand who they are and understand how Claude can help them and get them to the right place.
I want to follow that thread, activation. There's something that comes up a ton when I talk to people leading and driving growth on AI products. It's just like
Like, there's so much stuff trying to get your attention these days, for people to get to a place where they're like, okay, wow, this is really going to be something I want to keep using. It proves to be really hard. And it's also just unreliable. Sometimes it's not going to be magical. It's AI. It's non-deterministic. I guess one is just, how important is focusing on activation, getting people to that aha moment with AI products? And two, what are some things you've learned about how to do that well with Claude or AI in general?
Yeah, it's a good question. I think that activation is critical, right? And defining that as early activation, call it the day zero, day one product experience. I think that historically, anyone who's been in growth or been in product understands that that's usually one of the highest levers that you have to actually even increase longer-term retention. And I think that the importance of that has just gotten exponentially higher. Now, zooming out, I feel like one of the biggest problems in the industry is capability overhead, where the models are just getting better so quickly. And the real challenge is on the product side of how do we start to diffuse those benefits to people, where even internally there's new models coming internally and you're sitting there, you're so busy, and when a new model's available, you need to really carve out time to be like, "What can this do? How do I need to update my priors?" And if you think about it more broadly, for most people, you may have AGI or some model that can do all sorts of crazy things, but if people's instinct is to come there and be like, "Hey, what's the weather in SF?" then they're not going to get the most out of the product.
And so I think that it's tough because the model capabilities are rising so much. So if I think about, okay, back when we had, I don't know, say Opus 4, there's a series of things the model can do at that point, and Opus 4.5 unlocked a whole bunch of new things. You can think about, okay, we sit there, we've got this new model, Opus 4. The time to then go and run a bunch of tests, figure out, okay, there's the capabilities from this new model, what are the right on-ramps to guide people to those features? You run tests, you get the learnings, you then ship a new flow. By then, you may already have the next model, which unlocks newer capabilities that make all these learnings irrelevant, right? So it's actually just a really difficult problem to stay on top of.
I think that many of the same old trends in growth and activation remain accurate, where to me, ultimately, some of the highest leverage comes from finding the right product or the right feature for the right user. And I think that one learning I've seen time and time again across companies is that the right friction helps, and adding more friction usually works if you do it the right way. I think that's something I've consistently seen, and we've seen it here as well. So to me, being able to identify what are the characteristics of the user that allow you to then recommend them to the right feature or product, and not being shy about adding friction to do that, is probably the single biggest thing that's important here.
When I asked Ben Mann, one of the co-founders and a former podcast guest, what to ask you about, this is what he highlighted: your experience, especially at Mercury, redoing onboarding and making it magical. And basically he's in the same place as you on just how important it is for people to understand what the AI tool is capable of, to help people decide to use it and stick with it. Is there an example of something you changed in onboarding that helped significantly improve activation?
Yeah, it's a great question, and I like that he brings up Mercury. I talk about their product a lot. So I worked on the growth team at Mercury. I think it's a fantastic product. It's something many people use, and the reason they use it is because it's a better banking experience than you'd get elsewhere.
Yeah, I'm a very happy customer, just to put that out there. I love it. Great product. Highly recommend it. They have personal banking. Everyone's got to go and use it.
Right, they just launched that. And so I think that the interesting thing about Mercury is the core value is that it's a better experience, right? That's the reason you use it. You're not getting better other things. It's just a better product experience. And so that ethos is very, very deeply held within the company. It comes from a number of the founders, and I think that we had a big push one quarter when I was there on the onboarding flow. So, onboarding flows for banking institutions and regulated entities are extremely complex. The amount of time I spent on the difference between a registered agent address and a legal address and a physical address. These things are very, very complex, and we basically looked at the onboarding flow and were like, "Okay, we invested so much in quality in the rest of the product, but we haven't really done it here. And this is the first experience that people have." And so we said, "Forget metrics, forget growth, forget everything else." As the growth team on conversion, we're going to spend a whole quarter fixing quality in this flow. And so that's what we did. Forget the metrics, we're just going to make this as good of an experience as we can and fix all these things, like going back from one field to the other field and adding in your beneficial ownership details. And it actually ended up being, probably until I joined here, the single most impactful quarter that I've ever had as a growth team in terms of the impact that it had. We saw a significant uplift on basically our onboarding start-to-completion from just focusing on quality. And so that to me is a broader learning around quality driving growth that I've tried to bring to Anthropic.
I think for us at Anthropic, some of the things that we've done in the onboarding flow is basically we ask users questions around who they are and what their interest areas are. And we then use that to recommend different products and features. And a number of people look at the flow and they're like, "You have so much friction. It's such a long flow." And I'm like, "We have the data. We're kind of happy with how that's performing."
What is your philosophy on friction, good friction versus bad friction?
I've just seen time and time again, at every job I've been in in growth, that adding friction and adding the right steps leads to higher conversion and higher funnel completion. I think especially if you have high volume, you should test the majority of this and just learn and see if this applies to your business as well. You want to get rid of annoying friction that doesn't add value, but I think the most simple understanding people have is just solve time to value. Cut all the steps and just get them into the product. And that doesn't work most times.
I think if you've really thoroughly tested your flows... I look at the companies I've been at. MasterClass: if you go through MasterClass's purchase flow right now, you'll go through all these steps in this quiz when you're trying to buy, and you're like, I came here to buy and it's taking me through all these questions, what are you here for, etc. I think it's easy to look at that and be like, why do they have this? This is a terrible thing. Just cut it all. And it's like, no, that's been thoroughly tested, and actually that was a significant revenue driver, because it helps users feel that the product is for them by understanding what their interests are and then recommending the content and classes there. One of the growth PMs on our team left to join Calm, calm.com, the meditation app. If you go to Calm's landing page and you go through their purchase flow, their login flow, you'll see a quiz. It's not a coincidence. At Mercury we also tested, I think you might have seen a post on Twitter, we broke out some steps in onboarding. If you have one screen with five or six different form inputs and you break that into two screens and reduce the cognitive load on people, that is something that performs well. We added steps into the flow there that actually performed well. Same with at Anthropic.
So I think the takeaway to me is: cut friction when it doesn't add to the experience of helping a user understand why the product is for them. But if you can help users understand why the product is for them, how to use it, and what's most relevant to them, and it's going to add friction, don't shy away from it. Test it, confirm that it works for you, but I think this is something that most growth practitioners deeply understand.
And the "for them" is really important there, which you described as adding friction to better understand who they are so that you know how to recommend the right thing for them.
Correct. Yes. And done right, that just flows through, right? So it helps you with activation, but then it helps you with lifecycle. You know more about those users and why they're here, and in the most sophisticated businesses, even if someone drops off, you can do look-alike targeting and you can get them at the ad layer as well. So that initial piece of how you understand who the user is, it's a juice that just keeps on giving if you then use it right further down funnel.
Everyone's about to go do a bunch of tear-downs of Claude's onboarding, MasterClass onboarding, Mercury onboarding. Kind of as a tangent, I was at this PM dinner recently and I was asking all the PMs, how has your role as a PM changed most with AI? Where has AI most impacted what you do? And one of the PMs answered that it's actually doing competitive analysis, doing a bunch of tear-downs of what other people are doing for pricing pages and onboarding. So it's easy to do now. Just, hey, Cowork. I don't know, would you use Cowork for this, or Claude? What would you use for that? Okay, this is good. Help people pick which tool to use. If you want to go do a bunch of tear-downs of other competitors' onboarding flows, what would you use?
You can use Cowork for this, right? So if you have Cowork with the Chrome extension, if you task Cowork with the Chrome extension to go and look for these flows and give me a view of what's working and what's not, that's definitely something that Cowork can do.
Cool. I imagine that's one of the challenges: you have all these tools now, and just, which one's for me? By the way, the Chrome extension, I use it all the time. It's amazing.
I want to drill a little bit further into the growth org. There was this whole meme on Twitter the other day that you have one growth marketer driving all growth at Anthropic, and it's like, "Okay, that's crazy." How many growth people are there? What's the rough org structure of the growth team?
We're roughly maybe 40 people now, and we are, I think, structured very much like a traditional growth team, in that we have horizontals of growth platform and monetization, who think about the sphere of growth across the entirety of our products, and then we have more audience-focused growth pods. You can think about B2B growth, Claude Code growth, knowledge worker growth, API growth. So really these audiences, to keep a narrow focus, which is a thing you have to do when you have so many different products. And then these horizontals that think about things across the board.
And is it a team of engineers, designers, PMs? What are the functions within the growth org?
Yeah, it's engineers, designers, PMs, data. I think that overall the shape of the org is quite similar to, I'd say, a traditional growth team. Probably the thing that's maybe different is that I think we index a lot more towards larger swings as opposed to smaller optimizations. If I think about a traditional growth team, I would have probably spent maybe 60–70% of my time on small to medium bets, and 20 to 30 percent on larger swings, and I think for us we flip it a lot. We do much more the other way, where it's 70/30 or more like 50/50, rather than indexing towards smaller bets. That's probably one of the biggest changes, I think.
Just to highlight that, what's interesting there is at the scale you guys are at, a 1% win is massive in the scheme of things. So it's interesting that even at the scale you're at, you're not focusing on these micro-optimizations.
It is easy. You could easily focus on these small optimizations, and then you tally them up at the end of the quarter, and you're like, "Look how much impact we made." And you could do that.
Another billion. No big deal.
Yeah, but the thing is, we've been tracking at 10x year-on-year, and that's the thing that we keep in mind, and I think it ultimately comes down to our fixation in this company on the exponential. I think if you look at anyone from Anthropic talking about basically anything, we always talk about the exponential. Effectively, as model capabilities continue to grow on an exponential, and the tools around them do a better job of diffusing that into useful use cases, you basically just keep unlocking new markets where the value of those markets significantly dwarfs the value of the previous markets. And agentic coding is a great example. It didn't exist a year and a half ago. And now the value of agentic coding is bigger than the previous market of AI coding use.
And so I think that is the core thing here, which is that the future product value is an order of magnitude higher than it is today. And I think about, I don't know, a normal business, like a number of companies that I may mention, like a trading app or a grocery delivery product. Many of these leading companies are great businesses, but if I think about the product value of a standard company, call it a grocery delivery app, what is the product value you get as an end user today versus two years from now? I look at it as, two years from now, even if you're shipping all these new products, as an end user the value you get from that product maybe goes up 30 to 50% if the company's done a really good job of shipping new features. It's not exponential, though. And so if I think about, okay, you're here today, in two years you're going to have 30 to 50% more product value, then as a growth team, that relative differential of the product value two years from now relative to today, I can actually capture a decent percentage of that with the small to medium optimizations that typically have higher conviction, as opposed to larger bets. But for Anthropic, it's not really that way, because of the exponential, and our products being very, very, very... the product
value coming from AI, the product value that we will deliver in two years' time is probably like a thousand X, a hundred to a thousand X what it is today. And so if I think about that, there's so much value on offer. You need to shift more towards, okay, we need to take larger bets, and then we need to not miss the forest for the trees. And so that's why we still do all the small optimizations. It really matters, and no one else is going to do some of these things, so we need to do it. The compounding value is not immaterial, but we do take on much larger core product type of swings as well.
So you mentioned the Chrome extension. That is now the thing that underpins a number of use cases on Cowork and Claude Code as well, and that's something that the growth team built. That's a very AI-filled product, a very research-heavy product, but we were just bullish on it. We had an engineer who was very bullish on it, and we were just like, "Hey, no one else is doing it. We're going to do it." And so that's the sort of thing that I wouldn't have done at another company.
Oh, wow. I did not know that. So one takeaway here is, you know, there's stuff to extract from your advice that is only true at Anthropic, and then there's what can other companies learn from this experience that you've had? So one is your sense that if you're working in AI, shift more of the pie chart towards bigger bets, because in the future the opportunity is so large, you want to find those as soon as possible versus micro-optimize?
To be more specific there, I'd say that if the primary value that your product delivers is underpinned by AI as a central element of it, then I think you should operate this way. So, I don't know, companies like Lovable, Cursor, all these great businesses where, as the exponential rises, their value props are also going to continue to rise significantly. If you're building a product where it's an AI-first product, then I would definitely operate in this way. I think if you're building a product where it's not necessarily an AI-first product, and you have some AI features that are on the side, but it's not the core of your value, I don't know that I would operate this way. It would depend on how the rest of the product is all staffed, and how growth is all staffed in relation to that.
Okay, awesome. And then in terms of the way you are structured, I thought that was really interesting. It's a combination of different sorts of things. So there's the API growth, there's Claude Code growth, but then there's also personas, like a vertical of knowledge workers and B2B. Is that intentional? Like some specific bets and one just broad market opportunity?
When you have one product, it's easier to have a growth team that's more purely on the funnel, right? You have conversion, you have activation, you have monetization. But as you start to get into having multiple products, I think that's harder, because if you just have one activation team, for example, but then you have Claude Code, you have Cowork, you have all the other things, they're very different audiences, and they're very different sets of cross-functional stakeholders internally. So we're looking at what structures, which are not perfect and are right for a point in time, but we're looking for the structure that allows us to have as much focus. Focus is a really big thing, on audience and problems, and also the ties to cross-functional partners are really, really important. The folks in our Claude Code growth team work extremely closely with Cat and Boris and the others on that team. And so that tie-in is really important as well.
So you've done growth at a lot of different companies, a lot of, let's call it, traditional growth before Anthropic. How else is growth as a function and as a skill set changing with the rise of AI, AI products, AI startups?
I think if your core product value is very backed by AI, then it is shifting, where you're skewing more towards larger bets as opposed to small and medium experiments. And maybe a big thing related to this that I think will accelerate this, which I am really interested to see how it will play out, is we are starting to look at how we automate growth, which I think is a really interesting area. So our growth platform team, we're very lucky, we have Alexey Komissarouk, who teaches growth engineering at Reforge, and he's just the guy on the team. And so he is driving this effort. The name is a little cringey, I didn't come up with it. It's called CASH, which is Claude Accelerates Sustainable Hacker growth. I did not come up with that. But really it's an effort to look at how we can use Claude to automate growth experimentation.
And it is still very, very small. It's still very, very early. We kicked it off only, I think, a couple of months ago. I think before Opus 4.5 it wasn't really possible; we just weren't seeing the results. And more recently with Opus 4.6 we're like, okay, this is headed in the right direction. And so I think this will happen more and more across the industry. I think this can happen all across product, but growth teams in particular, because there's this whole body of work that is very small optimizations that I think is just more inherently suited to tackle this earlier.
If you think about the life cycle of shipping, there are sort of four parts to it. One is identifying opportunities: how good is Claude at actually identifying opportunities based on different trends, based on previous trends that Claude has seen in the past? Second is building the actual feature and getting it ready to ship. Third is testing and ensuring that it meets your quality bar and your brand bar. And then fourth, once you've actually shipped the thing, is analyzing the data and gathering the learnings. If you think about that as the loop, these are four things that you can eval and hill climb on, and understand how well a model is doing for you in each of these areas. We basically think about it in those four ways, and we are scoring how well Claude is doing in each of those areas.
And so we've been testing this at pretty small scale right now. It's all been a lot of copy changes and some very minor UI tweaks. It's delivering results, right? You can press play with it, and it ultimately prints money, where I'd say that the win rate is like, I would expect to see a junior PM do better. I would say this is like a junior PM, two or three years in; this is the win rate that I would expect from a junior PM. But it's not quite at the senior PM level. Although, you look at the exponential: this wasn't available at all a couple of months ago. So it's getting better rapidly, and I think it's going to change where you'll be able to do this for larger and larger types of experiments.
But then, you think about the largest types of experiments. I mentioned the four pieces around identifying opportunities, building, testing, and shipping. The one I didn't mention there, Lenny, is cross-functional stakeholder management.
There's still a need for human brains. Yes, there it is.
And I think that one is going to mean that, in my eyes, the work of PMs is not going away anytime soon. That piece, especially for larger projects. You don't need to do as much of it for smaller stuff, right? You can skip it, but for larger stuff that piece is not going away.
Until the other stakeholders are their own little agents running around.
That's right. I think that would be the point where that changes. It's funny, we had a difficult meeting a couple of weeks ago, and my head of design, Joel, and I were debriefing afterwards, and he's just like, "Oh, we will have AGI and it will still be impossible to get six people in a room to align." And I'm like, "Yeah, I can see that."
Like, what's the harder alignment problem? Oh. Okay, this is so interesting, and this is exactly where I feel like things are going. So just to be clear on what you shared here, there's basically this tool that comes up with experiments to run to help grow Claude and all the tools. So it comes up with ideas, somebody looks at them, approves, cool, let's do these things, it builds it, ships it, tests the results, sees how it's doing, and then it comes back with here are the things that are working. Is that roughly right?
It's roughly right, and right now we have a human in the loop approving. But I think about scaling this way: week on week, are things getting better in each of the areas? Are people spending less time on each of the areas? Are your results getting better in each of the areas? And as long as week on week that's getting better, then you're like, okay, this whole initiative is scaling. So that's roughly right, but I think a lot of this can be automated where human review is not needed. We care a lot about brand, right? So that is something that we do look at right now. We don't want to be shipping something that goes against the brand. But then you can have a skill that contains your brand guidelines and very clear do's and don'ts on brand. And so all of these types of accompaniments, I think, are going to get better. The models then get better at understanding how to use them, and so over time I think the need to human review this really decreases significantly.
Yeah, and you could always unship it if it's like, oh yeah, that was actually not a great idea. And that's such a good point, that we think we need people to do these things forever, and it turns out, okay, a skill could do this really well. Here's our brand guidelines, here's our vision, here's our mission, here's our goals, here's what matters to us. Okay, let's not ship that thing.
So the reason I think this is so interesting is I've just been watching the expansion of AI doing more of the product development process, in this case the growth process: from helping you write code, to writing all your code, to reviewing your code. Now it feels like, what are the two ends around this? It's kind of going from the middle out. The top of that is coming up with what to do, and then there's the alignment stuff, still very hard. And then on the other end, it's reviewing the code and then shipping it, and then getting distribution, which is a whole other thing I want to talk to you about.
So what I'm hearing here, and this is exactly what I thought was going to start happening, is AI is now getting really good at telling us what to do, not just taking our orders and building it. And it feels like the growth version of this is where it starts, because it's so much simpler. Not that growth is easy, but it's data-driven; there's this loop that you talk about. So I think this is such an interesting sign of things to come across product generally.
Yeah, definitely.
Just putting that out there. Okay, so something that I'm constantly thinking about along these lines is the future of product, PM, engineering, how those roles shift over time based on the stuff we're talking about. How are you working together as a triad? And where do you see these roles going? What's most going to change, do you think, across these three roles?
This is something that we talk about and think about frequently, and the picture changes rapidly. Historically, when things break and the execution bottlenecks break, it's like, okay, now you need to hire more engineers, you need to hire more designers, etc. And it's more just a life cycle thing: where is the life cycle of your team and that specific pod, to identify where the bottleneck is. But now, when things break, you need to still look at it: is it the actual ratio, or are there also underlying technological shifts that are causing this to break? And so that's an interesting thing.
I think in smaller companies, say a 15 or 20 person company where you're the only PM there working with some designers and engineers, you'll see probably the biggest blend, where the PM will be doing all sorts of things; they'll be designing, shipping, etc. And I think you'll just have extreme bifurcation. At larger organizations, more scaled organizations, I think the jury is still very much out. You speak to people even internally here, and different people in different teams have different views of how much these roles are coming together versus how much these roles are going to be separate.
It's not to say that PMs aren't shipping; a number of PMs are themselves shipping and pushing PRs, etc. But if I look across what I'm seeing, I think it's clear that while PMs and designers are getting more leverage from AI, engineering is getting the most leverage right now. I look at tools like Claude Code, and the amount of leverage engineers are getting from them is higher than the leverage that designers and PMs are getting from them today. Now, this is also rapidly changing, but that to me is my view today.
And so if you think about the default team, which is, say, five engineers, one designer, one PM: with Claude Code, those five engineers are two to three x'd, right? And the PMs and designers have also increased, but now they're managing what is effectively a much larger group of engineers. And so even though the head count in the org structure hasn't changed, you're now dealing with a situation of maybe 15 to 20 engineers in the old world, one and a half to two PMs, and maybe one and a half to two designers.
And so we're seeing that that's putting a lot of strain on PM and design. And it's not everywhere. I look at teams like Claude Code, and I think because that product is so technical, it's probably just the right thing, where the PMs are all basically engineers themselves anyway. But we had a PM lead offsite the other week, and we were all talking about this, where across the board their feeling is that PM and design are just squeezed. They're just absolutely squeezed. And we're like, is the right thing here that we just need to actually hire a ton more PMs? And that could actually be where we land.
On growth, how I think about it is, one, we are hiring a number of growth PMs. We desperately need people who are very, very good, and we are hiring. So if you are excited by what we're doing and you know growth, please feel free to apply. I would love to chat.
Maybe craft an amazing cold email to you. Yeah, yeah, yeah. Feel free to craft that
email. So that's one is I think we are going to be hiring a number of PMs. But then the second thing that we do is we very much hire product-minded engineers. I think this has always been the best thing to do in growth. Like you always want to have the engineers coming up with ideas etc. And so we especially, especially people who can really like step in as mini PMs if the PM is absent. And so we're like basically more formally leveraging that right now because we are so stretched.
So the frame that we have is that if a project is two weeks of engineering time or less, then the engineer is on the hook to effectively be the PM for that. And so that means things like talking to security, talking to legal, talking to cross-functional stakeholders. And the engineer is very much driving that. The PM will get looped in and they'll advise if needed. And if something is like wildly going off track, then they'll step in, but they're much more in an advisory capacity versus execution. If a project is more than two engineering weeks, then the default is that the PM should continue to be on the hook for making that go well. And they'll delegate more to eng, but they're like squarely accountable.
It's not like fully clean cut. It's like use your head. Like if this is a one-week thing, but it's extremely controversial, like the PM should probably still drive it, but that I think is like the approach that I expect more companies will start to do, which is just deputize the engineers to be mini PMs. Now, not everyone can do it, right? So, the engineers who are more product-minded, suddenly their value goes up significantly, like an order of magnitude. And then I think we will probably still be hiring a lot of PMs.
There is so much interesting stuff I want to follow up on here. Okay, so one is this idea of two weeks just briefly. I always joke as a PM, you can go on vacation and be away for like a couple weeks from your team, and things are going to be all right. Like, you know, there's like a momentum, there's a plan, people will keep operating. And it feels like that's kind of this rule of thumb you use of just okay, if it's a two-week project, you'll be all right without a PM, you can handle it. I love that those two connect.
Okay, the other here is so interesting. So, you're saying here that because engineers are so accelerated, and this all makes sense, PMs and design are kind of just like holy sh— it's hard to keep up with the pace of engineering. And what you're saying is you need more and more PMs to keep up. That's one route, or it's engineers that can PM essentially. Which is so funny. It's just like okay, great news for product managers until more of the PM-y stuff can be done by AI. But that's a really interesting trend. I don't know, is there anything else there, just like oh wow, we actually may need more PMs. The ratio, more PMs, fewer engineers might be the future.
Yeah, I think this is like, it just like really depends on the industry, the size of company. Like any company where you're building something that's like much more developer focused, like you're going to rely on the engineers a lot more. Earlier companies, you don't have as much of this like cross-functional coordination, stakeholder alignment nonsense that you need all these PMs for. So, you can like get by with less. But then as a company scales, then like if I think about okay, now you have this ratio where maybe the one PM became two PMs from like productivity, the like five engineers became like 20 engineers, the one designer maybe became like three designers.
If you think about like what is the best use of time for that PM? I think this is like a really interesting thing of like how much should PMs be actually shipping things themselves versus everything else. I think like in the world where you're like limited on engineering, the PM should definitely be shipping things. I think in today's world, this is a good way to like get an understanding of the tools, which is really important. So, the PM should be shipping for that reason. But if I'm one PM or two PMs and there's 20 engineers, I think about what is the incremental value I can add with my time, and is it actually shipping like the 21st PM feature, or is it saying how am I getting a little bit better at guiding the team on what the right opportunities are?
And so, that's where I think like in this world, you may have all these engineers who are like mini PMs. And the better that happens, like that's like where I would love to be doing more of. But still, like if you then get a really good PM who can come in and can like improve the like why and the what, and why and the what particularly by like 5%, that is like such a high leverage hire.
This is such an interesting insight you're making. It's like so counter to how a lot of people are thinking PM is evolving. Like what I'm hearing here is because PMs are so behind, because engineers are just getting so much done, there's like many people here saying okay, you need to be prototyping, you need to be shipping PRs as a PM. What you're saying, which I completely agree with, is your time is much better spent helping PM basically, and helping the engineers become better PMs themselves. And the leverage there is a lot higher than you spending time coding, shipping PRs in most cases.
I think that's true in certain circumstances. I think that as a smaller company, I don't know that that's the case. In a smaller company where it's all hands on deck, I think you probably need to be shipping. I think if you're in a company where like budgets are very tight, and engineers are very tight, and you know, you're not able to just hire because money's unlimited, then like you need to do what is needed to accelerate the impact your team's going to have, right? So there's going to be a number of cases where like as a PM, the right thing to do is to be like screw it, I am shipping, and like I am going it the whole way. But I'm talking here more about the like larger companies, more scaled businesses. Yeah, if you have 20 engineers, is it the highest leverage use of your time to ship an extra feature, or figure out how do I up-level everything that we're doing, get the user insights better, etc.
Yeah, and I think there's also an element of shipping to learn, building a prototype so that you can have a better opinion. Like a lot of people talk about just, I'm just going to try three things, see how it goes, and that'll help inform the road map. This is now the PRD: look at it instead of talking about it. So there's a lot of value there still.
That's very true. I think that's a great point. So like even for me now, where we've got a number of PMs, we've got many engineers, there are certain times I'm like, I want to articulate the idea I have in my head. It's just better for me to prototype it and show it, right? So I think that is really important. And then, you know, we are very scrappy. So, like we're like a big company by name, valuation, but we're like extremely scrappy, and just the focus internally is just like minimize bureaucracy and just like just go. And so, probably 70%, maybe 60, 70, 80% of what we ship does not have a PRD. I'm like averse to PRDs. I think I just like hate documentation. I'm just like go go go. Just like cut the blockers. 20, 30% of stuff where it's like it's important, it's really important to get right. Like the documentation should be really good and like the people should spend a lot of time on it. But by and large I think PRDs are just outdated at this point and you can just kick things off with a good team without needing to do that sort of thing.
Say more about that. What do you do to help make sure, because people can build so fast or spend a lot of time going in the wrong direction, ship things that are not what you're asking. How do you kick off a project and clarify here's what we're doing? Is it just a conversation or is there anything beyond that?
It really depends on the size of it. And this kind of goes back to like the two week thing. So, why we have that two week thing, it's more like a how do I have some filter to say if we're investing heavily into something, we should apply more thinking behind it, versus if it's a smaller set of investments, just go for it. Then as a growth team again, you do have a decent amount of these smaller things that you do. So, for very small changes, you know, like, there's a thing coming, we need to have an upsell for it. What is the thing we're doing? Like this is just on Slack, right? This is just purely on Slack. It's just messages back and forth, and I think it also depends on having a good caliber of engineer in there. But engineers can understand like, "Hey, I know you said this, but like what about that for the audience?" And so, like we're lucky we have good product-minded engineers in that sense. But all these smaller things are very much just on Slack back and forth, and that's what you do.
For the larger things, I very firmly believe in like a proper kickoff. So, we still do, just there's so much going on at this place. No one's got time. No one knows what's going on. And so, doing a cross-functional kickoff, get legal, get safeguards, get everyone in the room and just be like, this is what we plan to do. What do you care about? What do you care about? What do you care about? Like that 30-minute meeting for larger things is just I think still so important to just streamline all the mess that may happen later if you don't do that work early on.
What's your approach to crafting that PRD in those cases? Is it like ramble into Claude? Do you have a template?
Even in those cases, there are times I don't craft a PRD. Like cuz everything's moving so quickly, right? So, there's still some of those cases where I just set up the meeting. And then like 5 minutes before, I'll put it into Cowork, like here, you know, some of my thoughts, like here are the things that I need to think about. Spin up like a basic doc and we use it to talk. Other times I won't even have a doc. But if I am creating a PRD, I have basically a skill that I've created, and then there's projects with all the previous PRDs in there. And then it's pretty simple. It has the format down. So, I'll just say, here are the things I care about. Here's the why. Here's the problem. And flesh out the key considerations. Flesh out the cross-functional stakeholders, those types of things. But again, my default is like if I can avoid the doc and if we can just jump to action, then that's what we should do. And increasingly I just jump to prototyping the thing.
Yeah, that's where I think it'll get so interesting once we can automate more of that. Just like your assistant talking to the legal assistant, just like ironing out all these little, you know, what's important to you, what's important to the—
Yes, and it's coming. And I think legal has done like good enablement around this. Like we work in these versions of like how do you, you can think about like how can you mimic what someone might say and like set up, you know, like a quote, right? So, there's things like that that I think that we have now. And then as Claude gets more and more context and gets better at parsing long context, I think these are things that Claude will just get better at knowing.
One of the things, Lenny, it's like a slight tangent, but one of the, I think, most effective ways I use Claude, or one of the most interesting ways I use Claude, and a number of people are doing this internally, is to like help you identify misalignment. This is like, I think it's something that I've found really, really helpful. So, with Cowork, you have the Slack MCP. And you can tell Cowork to say basically look across Slack, you know the projects that I'm working on, these are the things that are top of mind, go and find me areas of potential misalignment right now. And it does a really, really good job. So, this is something that I have scheduled, runs every week. Claude's like looking at things and coming back to me and saying like, "Hey, I think these things you should be aware of." And so, you can think about it in that shipping context, it's a similar thing where Claude can basically be looking at what's happening across the company and say, "You're thinking about shipping this thing, here's who you need to talk to, here's what you need to keep in mind."
That is so cool.
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I feel like there's this like, what are the jobs of a product manager, and then how are they slowly going to be supported/done by AI. So, there's this misalignment, just like find misalignment, and then maybe one day it'll be like aligning people initially. You talked about this CASH automation for growing. Like, how do I grow this product? That's starting to happen. Another that I use myself when I'm building stuff is just asking, how do I make this product better? How do I make this a better user experience? And asking the AI, just give me a bunch of ideas, and they're actually really good. So, it's interesting how these little pieces are starting to be put into place to do more and more of this role.
I'm curious what other automations you and your team have that are effective. What I love about these conversations is you're basically living in the future. You're working at like the most bleeding-edge company with the most talented people, with the most cutting-edge tools, and you can like see where things are going and start to actually live in the future, build things that nobody else has even thought about or can do. I'm curious just what else is working, what else your team has done to help save you time, be more productive.
We use it pretty extensively across the board, right? So, there's the standard PM stuff, like writing docs, brainstorming, looking at data. For data, I personally have like a Cowork task that runs on a schedule and looks at 20, 25 different charts every morning, and then when I come in the morning, there's just so many charts, so many products to track. Cowork will tell me, "Okay, here are the things that you should pay attention to. Here's like what is concerning, and here are just some like interesting insights."
And it sends you the update in Slack, or how does, what's kind of the workflow?
For me it just comes up in Cowork. So Cowork has a schedule— Desktop app? Yeah, in the desktop app you can have a scheduled task that you create, and so I have a bunch of Hex links that it will go and look at. It uses the Chrome extension for some things and uses MCP for
other things, and then it will just give me a summary. And then I know there's a few charts that I just like to look at, because I just like — I don't know, I'm this guy, I just like charts. And they're all up and to the right too. So I like to see the chart. But then there's a long tail of things, and even the medium tail, where you don't have time to look at it every day, that if Claude is proactively looking at it and you start to feel good over time of, okay, the false positive rate is going down, the false negative rate is going down of things that Claude brings to you, then you just get a little bit more confidence and peace of mind there.
This touches on an idea I've always had that teams will have, is a strategy bot, which, just imagine, that's just constantly watching metrics, the market, the roadmap, what's working and what's not, and just like, "Hey Amol, here's what I think we should do now. Here's the pivot we should take. Here's where we're going to win." It feels like we're very close to that.
I think we're close. I think we'll get there later this year, to the point where that's very, very effective. That's my gut. I think that level of proactivity and looking across a bunch of context and distilling insights is — it's like, you know, the thing I mentioned earlier, Lenny, about the alignment piece. That's like a version of it, right? Now you're just looking across more data sources.
This is something that I use. So I talked about some of the standard PM stuff with it, you know, brainstorming, data, UXR. There's a lot of admin stuff I just hate, like life admin and paperwork. I just hate it. And so I get Claude to book my meeting rooms. Claude archives my email, a first pass at clearing up my inbox. I don't do any of my reimbursements and expenses. Claude will go to Brex and file the reimbursements. He'll go to Brex and file the expenses. So all of that side of things, I just hand it to Cowork. Just get rid of it.
And then the stuff that's quite interesting, I think, is the manager lens, where I talked about alignment is one thing. So I also look across my direct reports. Claude can look into what have they done this week? Look at our team goals and OKRs. Look at the transcripts from our discussions and understand. I can basically ask Claude, what are the key takeaways and observations I should keep in mind, and what feedback do you think I should give them? And that's something that, again, you can just set up weekly. But the quality is hit or miss right now. It's decent on some things. Sometimes you're like, "Holy — I am so glad that I caught this." And that's very, very helpful.
And then I do that for myself as well. So I basically — you know, my manager, Ami Vora, was I think a podcast guest of yours, right? So I say, "Hey, based on what you know of Ami, both publicly — she's written extensively about product — and then internally, and then our discussions, based on everything that I've done or not done this week, what feedback do you have for me as Ami?" And I get that every week, right? So a lot of these things can already be done today. I think as the models improve, the accuracy and the signal of these things is going to continue to improve rapidly.
I don't think you realize just how much awesomeness you're sharing here. Every one of these is like, "What?" Okay, so this Ami example. So you have one-on-ones with her. So do you ask Claude Cowork to go through all of her writing, basically build a model of her, and you ask what should I be doing differently based on what you know about Ami? Is that the difference?
Yeah, it's effectively — there's a number of ways you can do this. I think if someone has a public profile where they've written extensively, it's helpful, because Claude can just get all that information. Otherwise, you can have a project, or you can have a skill, but increasingly Claude is better at just understanding, because you can tell Claude on Cowork, "Using the Slack MCP, look at everything that this person has said in the last, you know, week, etc. And based on that, what are the top priorities? What are priorities my manager has, based on how they're spending their time, that I don't know?"
And so all of this layer of stuff, which I think about as soft coaching, I think that is unlocked, in my opinion, already. It's just that it's like working with a coach who's kind of drunk at times — not drunk, but, you know, sometimes says something and you're like, "Why would you bring that up? That's clearly wrong." But other times you're like, "Wow." There's one of the guys, Scott, who leads our enterprise team. There were a few cases where he found major areas of misalignment that would have caused teams to spin their wheels significantly or do overlapping work. And you think about the impact of that: your shipping in this world, at a bigger company, is going to be constrained often by all the cross-functional coordination, right? And I think we're now starting to see, at this cross-functional coordination layer, AI really being able to be used to reduce that toil. And I think that 6 months ago that wasn't possible, and I'm like, 6 months from now, what is going to be possible there?
Oh man. And I think the fact that all this data is there — there's Slack, there's Granola or whatever people use, all these notes from conversations and discussions — is really key to this working.
Yes.
So for someone that wants to do something like this, how do you set this up? What are kind of the steps?
You go on to Cowork, download the desktop app on Cowork. Connect the Slack MCP. That's where, depending on how big the organization is, you may need to get team or enterprise admin permissions — you know, someone with those permissions to enable that. But once you have the Slack MCP connected and on Cowork, you just ask Claude. That's it.
Amazing. Okay. I'm going to go in kind of a different direction. I'm going to talk about the focus that Anthropic has had over the years. So if you look at the numbers that you're all putting up, what's really incredible about it is the focus that you all have had, and I think this is the reason it has worked out so well. There's a certain competitor in the market that is realizing they should have done this and are starting to shift to a similar approach.
As an external observer, it feels like Anthropic has been very good at doing very few things but going super deep. So B2B, for example, just going deep on B2B, and then going really deep on coding use cases, Claude Code being an example. And it's worked out really well. Who's been driving that focus? Who has helped keep that focus from the beginning?
I think it's a foundational part of the company. I think it's been there from the very, very early days, and it really comes from leadership, and I think they've just done a phenomenal job of distilling that. I think that, you know, I saw this doc come up recently — I don't know where it was shared. It was something that Ben Mann, one of our founders, who you had on the podcast, had written. It's dated 2021, I think a few months after they started the company, and it was like, here's why we should just focus on AI coding. And this is, you know, 5 years ago. This is long before anyone knew what the actual market opportunities were around this. And I think this is just a deep focus that we have had internally from the start on the importance of coding and B2B.
You know, I think there's two lenses to it. There's maybe a view of, okay, this could be commercially beneficial to tackle, and then also the side of it around accelerating research. I'd say it's a pretty mainstream view now. I've now heard people from various labs talking about the importance of coding to accelerate research, but that has just been a very firm view that we have been laser focused on internally of, okay, if you have the best models, that's going to accelerate your research, and that's going to accelerate the research loop. And I think that's something that Dario has seen very clearly for a number of years. So I would say that's probably one — I think a lot comes from Dario, I think a lot comes from leadership and just our DNA.
I think the second, though, is probably just necessity. It's now changed — we're a more well-known company, raised lots of money, blah blah blah — but historically we were very much the smallest, least well-funded player in this space. In many ways it's a complete miracle that we've gotten to the stage that we have. We didn't have the free cash flow or the distribution of a Meta or Google. We didn't have the first mover advantage of an OpenAI. And so what do you do, right? I think there's this broader principle I have just around life of freedom through constraints. When you have a bunch of constraints applied on you, whether that's in personal life or at work, I think that can bring a lot of freedom, because it just frees up all this excess choice. You're like, okay, this is clearly the path. And I think for us it's like, okay, you don't have a ton of funding, you're a small player, you don't have distribution. You just have to really pick a very narrow focus, even for a very generalizable technology, to maximize your chances of getting to escape velocity.
And I think that's also just relating to how history played out, right? So, you know, it was well before my time, but Anthropic had a version of Claude. We had a chatbot before ChatGPT was launched. And we had ultimately chosen not to launch it for safety reasons. I think the team didn't want to kick off effectively an AI global arms race. And, you know, ChatGPT launched and they got insane traction, right? And that just naturally pulled them towards consumer. There's another world where if Anthropic had launched Claude first, maybe it went the other way around, even with all that focus stuff. So who knows? It's always hard to say looking back at some of these things.
Wow. I didn't know that. I think also people just don't realize how far behind Anthropic was. Right now it's like, of course they're amazing. But I just remember when people were talking about Anthropic raising money, I was like, there's no way they're going to compete with OpenAI at this point. It's so over. They're so far ahead. And it shows the power of focus and, I guess, I don't know, all the things you all did. It is absurd how far you all have come and how successful, and how things have changed so quickly.
Yeah. And I would say I very much agree. I think a lot of that comes down to our leadership team. We have a number of people who've worked at, I'd call it, the best companies in the world. Very senior people. And I think almost uniformly everyone's like, this is the strongest leadership team out of any of these companies. And so I think a lot comes from them, and then we're just very lucky to have incredible people. I think that helps a lot as well.
On the coding piece, just to make sure that part is clear. I never thought about this: the reason that the bet was so deep on coding is not just that it's a huge TAM, but that this is a feedback loop that will accelerate us further and further. So if we get the best at coding, coding will help us do research, it will help us build better models, and it will accelerate faster and faster.
Yeah, that's correct. And this is something I think Dario has talked about publicly, so I'm fine to share it.
Okay, it makes sense. The safety piece is really interesting, so let me spend a little time here. So famously, Anthropic — I think the official name of Anthropic is "Anthropic, an AI safety research company." As a growth person, there's this balance I imagine you strike between growing and the mission being don't grow at all costs — our goal is AI safety and alignment. How do you balance those two things? How does that impact your job?
Look, I think it's something we take very, very seriously, and it's the whole reason the company exists. And if you think about it, it's all the way from why they left to start the company. It's deep in our corporate structure itself. So, you know, historically, everyone raising money is like, go create a Delaware C-corp, and that's the structure you do. And with a corporation, you have a fiduciary duty to maximize returns to shareholders, maximize shareholder value. And from the beginning they went a different way. We created a public benefit corporation, PBC, which allows you to legally say that maximizing shareholder value is not the overarching umbrella goal of this company, and you can optimize for public benefit. So really, I think it starts from there and it ladders down from there.
For us, you know, our purpose, our mission ultimately, is to make sure that the transition to powerful AI goes well and is net beneficial for humanity. You know, internally we're very excited. Honestly, there's a lot of — we're very, very optimistic about where this can go. But we also understand what the risks are. And so for us, that top line objective of — this just needs to go well for humanity. This just needs to go well for humanity. That is something that we are happy to take a significant commercial hit for. And we've done that time and time again, right? Back then, okay, you had Claude, but you don't want to release it because you're like, there's a safety risk. And so time and time again I've seen we've been happy to take that hit, and it's actually worked out well for us in other ways.
From a growth lens, you know, I look at it as: growth teams can often push the boundaries of what is a good UX, etc., because they're trying to very much eke out metrics at times. When a controversial test is brought to me, I look at it as there are two types of tests that are controversial. One is when that test is so controversial that you just should not run the thing, because the results don't matter, because you would not ship it for a combination of brand and customer friendliness and values. And then the second is where it's like, it's controversial. Yikes. I don't like it. I certainly don't love it. But it's not a red line. And so, you know, if someone comes to you with conviction and is like, I have a really good hypothesis around this, and you're like, I don't love it, but you can run the test and see what impact it has. And if it's a high level of cringe or yikes, then I want to see a high level of return for that. I kind of think about everything in terms of, is it in one or is it in two? And for every company, one and two is different. I think for us the AI safety
...is very much in one. I think that it's like, yeah, it's why we exist. Like, it's fine, we're just not going to do this thing. I think then there's other things that fall into two, where you're like, heightened sensitivity, but we can try it and see what happens.
I think zooming out there, Lenny, one of the biggest mistakes I feel like I see growth teams make, and particularly just hardcore growth practitioners, is just trying to squeeze every last dollar. I think this is like a general principle also in life. Like if you're a founder raising money, just trying to squeeze out the last dollar, you don't want to do that, because you want people to come back next time as well, is my view. And I think in growth, it's really important that you usually need to be okay leaving money on the table.
And that's a core principle for us as a growth team, where we are very comfortable forgoing metric impact in order to prioritize safety, in order to prioritize our brand, in order to hold a high-quality bar, and to maintain a great user experience. And if you look beyond the short-term and like, "Okay, what are the numbers for this quarter?" and you zoom out and you think about what are the very best products out there, you realize this is how they all operate. And that's actually the thing that's going to drive more growth long-term as well.
And so I think that actually ties back to safety, where as the risks get higher and the stakes get higher, I think the fact that we are taking a stance that safety is critical to what we do is actually going to become a significant competitive advantage for us that I think is going to help us in the long run.
Yeah, and as you share all this, clearly it's working and Anthropic is killing it. So I'm loving those examples when someone approaching a problem that way, it actually works out. It's the same way I think about my newsletter. There's so much more I can do to grow it. My philosophy is just like, just focus on creating good content, nothing else. Like all these micro-optimizations are not going to matter in the end. It'll grow through people sharing it if it's useful to them. So on a very small scale, I have a similar philosophy.
One of the things that people are probably thinking about as we talk. So, you know, we joke about like, "Hey, AI replacing parts of jobs here and there." Like, you know, it is pretty scary to a lot of people. Just like, "What is the future of my job? Will I have a job? How do I stay relevant in this future?" So there's a couple questions here. One is just, for folks that want to thrive in this approaching AI future as a PM, as a growth person, do you have any advice, things that they should be doing right now?
To me, a couple of things come up. Like one thing that everyone says is like, use the tools. You need to be on top of the tools. I think you need to be using Claude Code. You need to be using Cowork and understanding, with each model release, what are the new things you can do with this? How can you apply this to your job? It'll work well in some things, it'll work terribly in other things, and then one model later it's like, "Oh, that other thing worked." But if you didn't go back to try it, you would not have known, and now many months have passed and you didn't know that that was possible. And so I think that being on top of the tools is really important, both for improving your own productivity, but also for getting product sense around AI products, which I think is just going to become increasingly important.
I think then, zooming out beyond that, I kind of look at it as just leaning into where you have a competitive advantage and an unfair advantage. And so to me it's like, you know, there are some PMs who are really good at craft, for example, and there's others who you'll throw them into a situation with all these stakeholders who have all these strong opinions, and, you know, there's no way they're going to mediate this, and they come out and it's like everyone's kind of swimming in the right direction. And so if you think about what is the major skill set that you have where you spike, that can be tied to driving impact for a company in a product role, I would just double down on that and almost forget the weaknesses. Just, what can you do to become the best person at that thing? Because that's very, very valuable.
And I think that ties to the notion of just leaning into being interdisciplinary. So going back to some of what we mentioned earlier on, where it's like, "Okay, in this world of engineers are mini PMs, the engineer who is highly product branded is an absolute unicorn." I think the same thing is true for PMs, where it's like, "Okay, now in this ratio, if the designer's really stretched and you're a PM who can design, you are also a unicorn. Now the chances of a company letting you go has gone down dramatically because you are now just so much more useful." And so I think that is just really, really important.
I think if I look at what's benefited me, it's probably a version of this. For me, I came from a founder background. So the mix of the founder background, the finance—I was an investment banker, so the finance background and numbers—and then sales. Like, I almost became an account exec instead of going into product. I was right on the edge of, should I go into sales or product? And I think a combination of those along with growth is probably what's led to, there are certain areas and situations where I can just have outsized impact relative to other people. And so understanding what that is for you is really important.
I look at our financial services product. You know, we've launched Quip for Sheets, Quip for Excel. They're going to take the market by... the way everyone when Quip launched. I know. But the guy running that, Nick Lin, he came from investment banking, he came from private equity. And he just has such a competitive advantage where he's building that product and he's like, "I know this. I know this." He's built for this. And so I think just understanding what are those interdisciplinary areas you can lean into to make yourself higher impact is really important.
And then the last one is just being adaptable. Anyone who is trying to just keep applying old playbooks, I think you're going to make life a lot harder for yourself. So one of the biggest things when you come into Anthropic is you need to understand that probably, yeah, 50, 60, 70% of how you operated in the past, just throw it out the door. It's not going to be relevant. And if you try to stick to that, you're going to have a lot of friction and it's not going to be helpful. So just being adaptable and understanding that, okay, the job's changed this way, I'm going to go that way, is, I think, so important.
That is awesome advice. It matches a lot of what Jenny shared when she came on the podcast, the design leader on Claude and Claude Cowork and all these things. Just the idea of going deep, becoming the best or one of the best at a very specific thing. And that not every company will need, and you don't need all 10, but just going deep on something. I forget how she described it. Marc Andreessen said the same thing. I think he calls it a sideways E instead of just T-shaped or one thing. If you could have a couple things you're really, really good at, there's a lot of power to that.
Oh man.
Okay. Before I get into something that I think will blow a lot of people's minds about how we actually met and kind of a big part of your journey, let me just ask you this. Is there anything else about Anthropic that might be worth sharing, might be worth talking about?
The thing that maybe comes to mind is just our culture and the people that we have here. I really think it's our secret sauce. I think it's the thing that is the most defensible, the thing that no one else is going to be able to replicate. And I don't think it's an accident. Leadership has really invested in this a lot, and Daniela and Dario, they really believe in this a lot, and I think it's just created a very special culture.
So I would say that, you know, this is truly a mission-driven company. And I was not 100% sure of that when I joined. I was like, I think that this is an exciting company. I very much agree with their principles, but I didn't know anyone at the company. I didn't have any references on what it was like inside. So I was a little skeptical when I joined. I'm like, at least they're talking about it, but I don't know. Are they serious about this? And then I came in, and very early I was like, "Oh. Okay, they are maybe even more serious about this internally than they talk externally."
And so it's a mission-driven company where people viscerally understand both the upsides and the downsides of the technology, and therefore understand the divergent ranges of how this may go for humanity and how different of a future that could be. And I think when you understand how different this could be as a future for all of us and our children and our grandchildren, etc., I think it leads to a lot of passion for what we do, and it just leads to a lot of belief in what we're doing.
And so I kind of look at every other job I've had in the past, there's some degree of people at the company who are just checked out, where it's like, you know, "I'm here. I'm sick of this, but I don't have a better option," or "I'm getting paid too much to leave," etc. That is just not the case here. I have not met a single person—I'm really saying not a single person—who's checked out. Everyone is putting everything they have on the table. Everyone is pouring it out and leaving nothing behind and is just fully in it. And so I think that releases energy that is just very, very hard to describe.
I think you have that energy, you have that mission-driven nature, and then it's such an open culture. So leadership is very, very transparent with us on things. Slack is a whole maze. There's so many things that play out in Slack. We're very open. Everyone has these notebook channels where you kind of have your own Twitter feed in a way, where you're just talking about your thoughts about things. And so you can go and join the notebook channels of people on research and all these other areas, and you can learn whatever you want, and you can spend so much time getting lost in that as well.
But that openness, where we even encourage—people can just argue with Dario. There was an all-hands, he said something where someone didn't agree, and the person goes into Dario's notebook channel and just says like, "Hey, I didn't appreciate how you said this and this and that," and then it sparked a whole big debate. But that sort of thing, where it's encouraged—go to leadership and disagree with them, challenge them publicly—I think that just leads to a level of trust. And all of that together, I think it just means that we have this very, very deep sense of togetherness that, man, I've just never experienced anything like it.
And then you get to the talent, right? I think that is the thing where the talent density is like, I feel like I'm playing for Real Madrid at times. I look around and I'm like, man, I'm playing for Madrid, where you just have the best people in the world. I think it's most the case on research. We have the very, very best researchers in the world. But even if you look on product, we have Amie Vora—she is phenomenal. We have Mike Krieger—you're like, okay, casually started Instagram, he's here. You know, on growth we have Johnny, who is my engineering counterpart. He's the OG in growth engineering, he's great. We have Alexey, who's like, the guy teaches growth engineering at Reforge, he's just another dude on the team. And all of that, I think, is just very special.
My favorite here is, a couple of months ago we had our company-wide on-site in October, and I'm walking around and I see this guy, he's just walking around eating popcorn by himself. I go up to him and I'm like, "You're Jeff, right?" And he's like, "I am." And I'm like, "You are literally the US ambassador to my country, Australia, and you're just an employee here." I'm like, this is insane, and talking to him about prime ministers of our country and all these things. And it's just the talent combined with that culture, I think, is just this secret sauce that is the reason that I think we are as successful as we are.
That notebook channel is so interesting just as a technical thing. So the idea there is Dario just shares—it's like a little internal Twitter feed where folks just share what they're thinking about and what their priorities are and things like that.
Yeah, that's basically it. Well, it's an internal feed where it's not just Dario, everyone has one. And basically you share your internal thoughts. It's a way to keep people updated on things, on what's working. It's a way where people share provocative things. I think from a leadership level, we also think about it as a way to scale your beliefs and views across an org as it grows quickly, right? So if you're now adding a lot of people in the organization, you need to think about, okay, what are the behaviors that we want to model? What are the principles that are top of mind to us? And yeah, you can have a bunch of these meetings where you talk about it. You can model that behavior.
But if you have a channel which is like, here's my top of mind, and you say these things, right? Like if I have a post, which I did the other week, of like, this is the importance of being comfortable leaving money on the table. Now all the new engineers on growth who've joined have seen that, and they're like, "Oh, okay, this is different to what we've known before," right? So I think it's good for the openness, but it's also good as a leader for how you can scale your views as an organization to get people more up to speed on the way that things are done, which is I think really important to avoid that drift. When you have so many new people signing up, that can lead to a lot of drift in strategy and perception. So it just helps run a tighter ship in that way.
And more importantly, it's data for the agents that we've got running to help them work with all these humans.
Yes, that is very, very correct. It is something that goes to Claude. You know, there are certain documents in onboarding where the HR team has written, "Before editing anything on this document, please check with this person, because this is a document that Claude references as a key thing," right? And so more and more, these types of things of, okay, how does the growth team think about this? How do safeguards think about this? You're arming Claude with that context to get better and better at helping in the future.
That's interesting. It feels like that's something that every company's going to have to start doing, is just sharing their thoughts in a structured way so that all these agents that we've all got running have what they need to know.
Another interesting side note here is just Slack. Okay, so there's all
This talk of SaaS tools being replaced by AI, and you guys use Slack. I think there's this famous tweet of you guys still use Workday and all these tools, all these SaaS tools. Everyone's like, what, they're all going to be vibe coded out of existence. The fact that you all, at the cutting edge of what could be built with code, still use Slack and all these other tools, that to me is a good sign that maybe SaaS companies will be all right in the future. I don't know if you have anything there to share.
Yeah, I think it's a really complicated picture, right? There's a number of things that we just build internally ourselves. As time goes on, the ability for Claude to do that better increases, and at the same time, we use Figma a ton, we use Slack a ton, we use Workday, we use a lot of these front ends, and I don't see that changing in the immediate future. And so yeah, I think there's probably some truth to some of this. I think the other parts are like, it's overblown, and many of these products are customers of ours. We value them a lot as customers and we use their products very, very heavily, and I don't see that changing in the...
And you have better things to do. Like, who's going to spend time building a Slack at Anthropic? That is not where value is going to accrue. And I think it also helps you see how sophisticated these things are. They're not just, you know, there's been teams thinking about these problems for a long time. Anyway, that's a whole other tangent.
Just coming back to the values thing, I just want to highlight something here that's really important. A lot of people criticize Anthropic for talking about the dangers to humanity, throwing out all these numbers about jobs going away, just creating all this fear. And people think it's, oh, we're trying to raise money, or we've got to get people's attention, or we're just trying to create headlines. But everything I've ever seen internally is always just: this is what we believe in, we want people to know what might be coming. Even if it isn't bad, we want people to understand here's what might happen, and we are trying to avoid it. And you might say, why is Anthropic even building AI if it's so dangerous? And you know, the understanding Ben shared is just, we think it's better that we go at this and try to build it the right way versus just, instead of that, hoping that nothing bad happens.
Yeah, I think three things come to mind there. First is, I go back to something I said earlier, which is that we very much think about things from an exponential lens. And if you are thinking about things from a linear lens, you will see the world very, very differently, right? Because you look at where we are today and you're like, okay, but how much better can it be in two, three years? I think if you're looking at it from an exponential lens and you understand how exponentials work, then you just realize that a lot of this stuff is actually going to be happening sooner than people think if they're looking at it from a linear lens. And then if you understand that there could be upsides and downsides and the range of outcomes here, I think we very much need to be talking about the downsides so we can avoid them and push towards the upsides.
I think most people at the company are optimists. We're very optimistic about the future. I think it's just we understand the risk. It is not guaranteed that we end up in a good place, and not enough people are talking about the risks, I think, in productive ways, and who have the know-how of the risks. So I think there's people who may talk about the risks but are not in the game, and so they don't actually know fully. They're not surgical on what the specific risks are. But we're in the game, we understand what's happening, and so that's one piece.
I think the second is, I think we actually believe in this stuff more strongly than we say externally. It is just such a key part of how we think internally that sometimes we need to reword your statements, because people might just think we're being too over the top, but internally that's how we think. And what we're putting out is a softer version of that at times.
And then I think the third piece is going to what Ben said, where we think a lot about driving the race to the top. And so it's like, if you're not in the game and you're shouting from the sidelines, no one cares. It's just the reality of how the world works. No one really cares. If you're in the game and you're a leading player and what you're doing is working, you can influence people who are also in the game to take the right actions. And so that is the core of it. If we just pack up and go home, you have no influence on this thing. And if you stay in the game and commercially you're doing great, then you have ways to influence that: okay, these are the principles, and put that into the conversation and make more people believe in those things.
I could talk to you forever, Amol, but two more questions just to round out the conversation and touch on some stuff that I've hinted at a number of times. One is I want to take us actually to failure corner, because someone listening to this may be like, "All right, look at this guy. Just worked at all these amazing companies, cold emailed the CPO at Anthropic, got a job, joined this rocket ship. It's all been up and to the right. Just killing it constantly." What's a story from your career where things didn't work out, when you failed, and what did you learn from that experience?
I have a couple. I think it's very much not that way. I feel like it was a lot of squiggly lines to get here. The biggest, I'd say, is just, you know, founding a company, raising a bunch of money, having employees, and then having to shut it down and tell your investors that you've lost the money and that you had a vision of what you're going to do and that it's not going to happen. And so that, I think, is probably the biggest one. You know, we spent 3 years on it. It was not like we tried something part-time. It was like, no, we went for it. We had spent 3 years, raised a couple of mil. We had maybe seven to 10 employees at our biggest, and it was something that we really believed in. It was around mental health and how you can quantify mental health to help understand or get early predictors of things like generalized anxiety, major depression. So it's stuff that we really, really believed in, but ultimately, you know, we were in our early 20s. We had no idea what we were doing at the time, and there are many things I'd do differently, but that was just a very, very, very painful process.
I think the good thing was we kept our investors in the loop the whole time. So to any founders who are struggling out there, send those monthly investor updates. It's really easy to send those when things are great. It's really hard to send those when things are bad. You just bat it down. You sit down and send an update to your investors about why everything you talked about last month did not go to plan, but it's just the right thing to do, and it keeps people in the loop and it avoids surprises. But it's still so tough when you're then calling to be like, hey, we're shutting down, or making that decision. Everyone had believed in you, and it becomes such a big part of the identity. It's very, very tough. So, man, that was just brutal. It's brutal. And it took me, I think, a number of years to truly get over.
I think that it's a tough thing, but you get so much from that experience that is hard to see in the moment. And I think without doing that, I would not have gone into this. I was not a PM before. I didn't have any of these skills. I'd never worked on products. I didn't know how to cold email, really. And so it was through that job that I learned a ton of the skills that made this career path viable for me. And it's just really hard to see that in the moment when you're looking at a point in time. It's much easier to draw the line looking back, but I think that'd be my takeaway: just keep in mind that it's a long game. And some of those things, I'm so grateful for that experience now. I'm so grateful that it failed and went that way, actually. It's very painful, because otherwise it wouldn't have led to what I'm doing now. And so it's a tough thing, but yeah, positives can come from it.
What I love about this is a lot of people have these times in their career where they're like, it's all over. I failed in such a big way, and my reputation's screwed, and people were counting on me, and now they see I'm an impostor. I never knew what I was doing after all. Now they finally see. And just seeing that... And this was 3 years, you had, I'm looking at your LinkedIn, you had seven employees. Something like that. And then it's like MasterClass, Mercury, Anthropic. I think it's inspiring to hear a story like that, to know that you can have a big failure like that and things can work out. That is not the end.
Okay, so in 2023, I was going to go on pat leave because my wife was pregnant, and I was just like, "Wait, what do I do with the newsletter? I need to take some time off. It would be really nice to take a month or two off." And so my plan was I'm going to do a bunch of guest posts where people line up. I put out a call for guest posts. People apply. I pick a few, and then I kind of slot them in ahead of time so I could take time off. So I put out this call, "Hey, who wants to write a guest post for my newsletter?" I got 500-plus applications. One of those applications was from you. And the pitch was essentially how a traumatic brain injury made me a better product manager. And I still remember reading the first draft you sent me, and I was just like, "Holy... This story is incredible. You feel such feelings." And it was just so tactically interesting and useful. Like, "Oh, wow, this is actually going to make me a better product manager." Share the story of the brain injury that you went through and just the journey that you went on there, because this is going to blow people's minds.
It was the toughest time in my life. It made shutting down a company be like, "Oh, that was nothing, actually." It's just funny how perspective works that way. Back in early 2022, I had a traumatic brain injury. So I've done MMA for many years. I've done Muay Thai, which is a type of martial arts, for many years. Never had a problem, and it's just one of the things that happens, like the wrong session. It's just a normal day of sparring, nothing crazy. You get the wrong hit to the head in the wrong way, and my whole life changed. And basically, I was off work for 9 months. The first couple of months were brutal. It took me roughly half a year till I was comfortable walking again. It was very, very difficult. The first 2, 3 months, beyond just showering and going to the bathroom, my wife did everything for me, including texting my friends. I would listen to music for maybe 20 seconds and feel like I needed to vomit. I couldn't look at screens at all.
And it was a very, very long recovery. It was not clear to me that I would ever work again for a while, actually. We'd even discuss with my wife what we would do in that case, etc. We had to think even on those levels. And through a lot of pushing and really working through it myself... You have to just slowly increase your tolerance to things. It's a brutal process, but you need to slowly expose yourself to different things and just get better and better at each little thing. Actively work on that. Don't push it too far, otherwise you have a big setback. I basically got to the point then where, it was 8 months, and then after that I returned to work.
And then slowly got better. And the part, Lenny, you don't know is, you know, in mid-2023 we posted that newsletter, and a month later I got reinjured, actually. Oh, wow. Because when you have a brain injury, until you're 100% healed, your risk of another concussion or brain injury is elevated. When you're 100% healed, your risk falls down to that of a non-concussed population. But until that time, you could be 95% healed, but you're not 100% healed. And it was just an innocuous, everyday-life thing, getting off a plane and a bag hit me on the head, type thing. And I was off work, like 1 month into joining Mercury. Like, 1 month in, I'm like, sorry guys, I need to peace out for 3 months. And then it was a very, very long recovery from that. And I'm actually still not 100% healed. So I'm mostly good, but I have times when I have dizziness and headaches and other things that I need to work around.
Overall, I feel like it's one of the best things that could have happened to me. And I think that keeping that mindset helps. And there's a point where you can take that too far, when that view is detached from reality, but I think it's just made me so much better and more effective as a person. A lot of the same habits: I don't drink alcohol, I don't drink caffeine. I have to do a bunch of these things for my physical health. I just have to do them, so I keep doing them. I take breaks. This is a really big one. You might think, even in a place like Anthropic, how do you survive in this way? Even on the craziest days, Lenny, between the start of the day and lunch and between lunch and the end of the day, I take a short break. Even on the craziest days, with model launches, etc. Luckily we have a meditation area in the office that I'll go to.
And then the whole side of things around meditation that I talked about in that post. I think both you and I have done a retreat at Spirit Rock, and doing a meditation retreat changed my life, and it's something that I do at least once a year now. I have one coming up relatively soon as well. And I think all of that has helped with better managing the physical side of it, because this job is very taxing, and then emotionally, having a little bit of space to what happens. You have awareness on one side, you have the reality on the other side, and reality's crazy here, man. Reality's insane. There's so much happening every day. There's so much noise. It's mind-blowing. And so that relationship between awareness and reality, that's where you have choice, which you learn from deep meditation: how to shift that and apply your choice there. I think that is the thing that has helped me significantly with just keeping a more level head. I think a lot of staying in this game at this level of intensity is just keeping your head. Just don't lose your head in the crazy times. And I think all of that that I've gone through has helped me do this without resorting to unhealthy coping mechanisms.
Wow. Amol, you're such an inspiration in so many ways. There's so many reasons that you would not have been successful and things would not have worked out. And there's so many lessons to learn from just the stories you've shared and the journey you've been on to help people overcome challenges they're having. Like, if you can come back from an insane... Was it a kick to the head? Is that what happened?
It was a kick to the head. That's correct. Yes.
Just feeling like you may not be able to walk, not being able to listen to music
to just like leading growth at the fastest growing company in history.
There's also just like a lesson here of constraints again. This idea of just like the power of constraints, like you're forced to take breaks, you're forced to go meditate, like in a way that's really helpful, and it's like a lesson for us all. This is actually really good for us all. Yeah, I think that freedom through constraints is like one of the big takeaways I've had during that time, because you may have these constraints, you're forced to adapt, and it gives you, in a business setting, you have to focus more. In a personal setting, like if the constraint is I can't do anything and I'm injured and don't know what's going to happen, I don't know I'm going to get better, you have two choices. Like one, are you just going to resist and like fight with reality and really suffer from that, or are you going to accept the situation and like not let that affect you emotionally? It's not to say like I did everything, man. I was like every single thing I could do, diet, exercise. I was like, I'm on it. Every action I can take, I'm on it. But then you have a choice of are you going to let the impact of that define your happiness or not? And I think that that's the thing when the impacts maybe are not coming, you have to then adapt to it, okay, what I want my happiness to be. And one of the meditation teachers said like the true freedom in life is learning how to be content when you don't get what you want. And it's not to say you shouldn't do something when you don't get what you want, but I think that takeaway of just can you be content and like not have your happiness rely on getting something? I think it's a challenge. I'm not perfect at it, but I think it's probably one of the biggest takeaways from that whole thing.
Incredible. And we'll link to the post if folks want to read this. Before we get to our very exciting lightning round, is there anything else you wanted to share or should we just jump right in? I think we can jump into it.
We covered a lot of ground. Okay, here we go. I've got five questions for you. First question, what are two or three books you recommend most to other people? It probably ties to a lot of what I just talked about. Like I think a lot about meditation and my emotional state. That's what I spend most of my time thinking and like reading and researching and working on outside of work. So my recommendations are really to that. The first is a book called The Joy of Living by a Buddhist monk named Yongey Mingyur Rinpoche.
It's just really about how you can start to think about your life experience in a different way and have tactics of what to do to kind of change just how you think about things. This is one where I've recommended it to a lot of people and they've really, really enjoyed it. I think another one is Awareness by Anthony De Mello, which is a kind of similar thing but from a different angle. Those two I consistently recommend to people. And then the third one is more relevant to the product in many ways, is Thinking in Bets by Annie Duke. I think just being able to break down a situation, and someone's like, "I don't know if it'll get done in time." Okay, like can you put a number to that? Like what percentage likelihood is it? Those types of things I think are just so tactically helpful in product. Favorite recent movie or TV show? I think movie is probably Marty Supreme. It's one of the only ones I watched recently. I thought it was great. I thought it was just an insane, absolutely insane movie. It was ridiculous, but I loved it.
TV show, I have not watched TV in a while. I think it's probably the Olympics would be the one, if that counts. Is there a product that you love, just like I don't know, one you discovered recently or just one you have in your life that's like, "Oh, this is very cool. People might want to know about it"? Yeah, so this is a funny one. I was in Japan last week and
I was sitting in this hotel and I just really loved the pillow that I had in this hotel. It was very random. I've just had at times like neck and upper trap pain, and sometimes I've been frustrated with my pillow because I sometimes sleep facing up, sometimes sideways, and like the height's not quite right. And I was just like, this pillow is just great. And basically this pillow is full of beads, and so you can like naturally shift the height of the pillow while you're sleeping, like even unconsciously without thinking. And so I looked at the tag, like what is this? I ordered it on Amazon Japan and I brought it back with me on the plane. And so I have the name here, it's called the Maruhachi Shinsui Maruhachi Pro Pillow, and you can only get it in Japan, but they ship to the US. No affiliation. And I think that has changed my life in like the last week. That is an awesome pick.
Do you have a favorite life motto that you often come back to in work or in life? Main one I'd say is just "she'll be right." This is a very common Aussie saying, it's like she will be right, she'll be right. It's a common Aussie saying when we are faced with like a tough or difficult situation. You're kind of like dismissing the severity of it in a way by saying like, yeah, it'll be fine. And I think that that's just like such a good metaphor, such a good tactic in many, many cases. And then I think the other one is just like sometimes in life you just have to go for it. And that is something that this guy Eros Resmini, who was the CMO of Discord, who was a very close advisor to me as a founder, he would push me on this, and that was something that he would often say. He's just like, just go for it. And I think that it's a very helpful thing. You can sit there thinking, should I do this, should I not, and sometimes in life you just have to go for it. I love the combo of those two, just sometimes just go for it and she'll be right.
So good. Okay, final question. So I'm curious, you used to be into martial arts, that didn't go great. Do you have a new hobby that you find yourself loving? Do you make time for hobbies? I think I'm just like quite tight on time for hobbies, I would say. I think it's largely just like work and have my body function and then, you know, take care of the most important relationships around me. I think maybe the one hobby I'd say is just I'm really into sports and I've gotten more into sports, football in particular, and watching. Watching, but certainly not playing. My wife is from Michigan and she took me to a game at the Big House and it just changed my life. From then on I was like, I'm a Wolverine fan. Big Wolverine fan, big 49ers fan. I just love football, so that's probably the one that comes to mind.
Amol, this was incredible on so many levels. I'm so thankful you made time for this considering how much you've got going on. Where can folks find you online, and say they want to apply for a job, maybe on your team, where can they find that? And how can listeners be useful to you?
You can find me on my LinkedIn. It's just Amol Avasare. I'm boring. That's it. You can look online to apply on our jobs page. There's roles across growth engineering, growth product, growth design. We are looking for great people on the growth team, so please come and join us. And I think being helpful to me is just two things. Trying our products, giving us feedback, giving us harsh feedback in particular on what can we do better. And then please send great people our way. We are looking for the best of the best to join the team, and we would love to hear from anyone you know of as well who could be a fit for one of our roles.
Dream job for so many people. Amol, thank you so much for being here.
Thanks, Lenny. Bye, everyone.
Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, 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.
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