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Anthropic's $1B to $19B growth run: how Claude became the fastest-growing AI product in history

In 14 months, Anthropic went from $1 billion to $19 billion in ARR — the most explosive growth trajectory in business history. The company that was widely dismissed as «too far behind OpenAI to compete» is now adding more revenue every few months than companies like Snowflake generate in an entire year. How did a late-mover with no distribution, no free cash flow, and no first-mover advantage pull off what appears to be a complete miracle? And what does it cost to lead growth inside a company where 70% of your time is spent firefighting «success disasters» — when things are going so well that other things break?

Длительность видео: 1:52:49·Опубликовано 5 апр. 2026 г.·Язык видео: en-US
13–14 мин чтения·23,731 произнесённых словсжато до 2,715 слов (9x)·

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Ключевые выводы

1

When your product value is driven by AI's exponential improvement curve, optimize for large strategic bets (70% of effort) over small incremental tests (30%), because the future product will be 100–1,000× more valuable than today's — making micro-optimizations relatively irrelevant.

2

Anthropic is already automating growth experimentation using Claude itself. Their «CASH» initiative (Claude Accelerates Sustainable Hyperrowth) generates test ideas, builds features, and analyzes results at the level of a junior PM — and improving weekly. Human review still required, but the toil is rapidly disappearing.

3

Adding friction in onboarding — asking users questions about who they are and what they need — consistently outperforms frictionless flows. The key: use friction to help users understand why the product is for them, then route them to the right features. This pattern holds across Anthropic, Masterclass, Mercury, and Calm.

4

The PM-to-engineer ratio is inverting: engineers using Claude Code deliver 2–3× output, but PMs and designers haven't scaled proportionally. Solution: deputize product-minded engineers to own projects under two engineering-weeks; PMs focus on strategy, alignment, and the «why» rather than shipping code themselves.

5

Anthropic's real competitive moat isn't the models — it's the mission-driven culture, radical transparency (every employee has a public «notebook channel» sharing thoughts), and talent density so extreme that the US Ambassador to Australia is «just an employee.» No one is checked out; everyone is all-in.

Вкратце

Anthropic's unprecedented growth isn't primarily a growth story — it's a focus story enabled by exponential AI capabilities, world-class research talent, and a willingness to leave short-term money on the table in service of long-term brand and safety. The growth team's secret: shift 70% of effort to large bets instead of micro-optimizations, automate experimentation with AI itself, and hire product-minded engineers who can act as mini-PMs in a world where engineering leverage is accelerating faster than PM and design capacity.


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The Unprecedented Growth Trajectory

Anthropic grew from $1B to $19B ARR in 14 months, the fastest in history.

ARR at Start of 2025
$1 billion
Starting point for the unprecedented 14-month growth run
ARR Mid-2025
$4 billion
ARR End of 2025
$9 billion
ARR End of February 2026
$19 billion
The number is already outdated — revenue continues to climb
Year-over-Year Revenue Growth Rate
10x
This 10x growth trend has held since the company's earliest days
Growth Team Size
~40 people
Structured as horizontals (platform, monetization) and audience-focused pods (B2B, Claude Code, API, knowledge workers)

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How Amole Got the Job: The Cold Email That Worked

Amole cold-emailed Mike Krieger with a perfected formula and got hired.

Amole didn't apply through Anthropic's website or get a referral. He was a Claude user who saw an obvious gap: the company had no growth team. So he sent Mike Krieger, then Chief Product Officer, a cold email. Krieger responded, and one conversation led to another. Amole is the only PM Mike has hired via cold email.

Amole's cold email tactic is battle-tested from his founder days. First, craft a subject line with extremely high open rates (he keeps the exact copy secret). Second, find the recipient's personal email — not LinkedIn or work inbox, where everyone else is reaching out. Third, keep the message short: here's who I am, here's why I'd be a good fit, let's chat. Fourth, follow up repeatedly until they tell you to stop. The philosophy: if you really care, keep reaching out.

The timing was perfect. Anthropic wasn't publicly hiring for growth roles, but leadership was just beginning to think about it. Amole's cold outreach landed at exactly the right moment.


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70% Firefighting, 30% Strategy

Leading growth at the fastest-growing company means constant «success disasters.»

SUCCESS DISASTERS (70% OF TIME)
When growth is so extreme that systems break
Anthropic's charts are «fully green, up and to the right,» yet the team is emotionally exhausted. Success disasters occur when one thing scales so well that adjacent systems collapse. Examples: acquisition spikes overwhelm activation flows, new model releases make prior onboarding irrelevant, cross-functional coordination bottlenecks multiply. Amole describes this as the hardest job of his life despite working at a rocketship — because hypergrowth creates a new class of urgent, high-stakes firefighting every week.
PROACTIVE GROWTH WORK (30% OF TIME)
Standard growth levers when there's breathing room
The remaining 30% is classic growth work: deciding which products to prioritize (Claude Code, Co-work, API), defining long-term pricing and packaging as technology and user behavior shift rapidly, and determining the right moment to activate growth optimizations for newly launched products. This is the «bread and butter» of growth — but at Anthropic's pace, even this work is compressed and high-stakes.

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The Power of Good Friction in Onboarding

Adding steps to ask who users are consistently beats frictionless flows.

💡

The Power of Good Friction in Onboarding

One of the cleverest moves Anthropic made was importing memory from ChatGPT to ease cold-start problems. But the broader lesson is counterintuitive: adding friction — asking users questions during signup to understand their needs — reliably outperforms removing all steps to «minimize time to value.» Amole saw this pattern at Masterclass (quiz before purchase), Mercury (breaking form fields into multiple screens), and now Anthropic. The key: use friction to help users feel the product is for them, then route them to the right features. Cut annoying friction that adds no value, but don't shy away from intentional friction that improves activation and long-term retention.


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Shift to Larger Bets When AI Drives Your Value

Anthropic invests 70% in big swings, 30% in small tests — the inverse of traditional growth.

Traditional growth teams spend 60–70% of effort on small-to-medium optimizations and 20–30% on large strategic bets. Anthropic flips this ratio: 70% goes to large swings, 30% to micro-optimizations. Why? Because the product value two years from now will be 100–1,000× higher than today due to AI's exponential improvement curve. In contrast, a grocery delivery app might improve product value 30–50% over two years — making incremental optimization highly valuable relative to future gains.

When your core value proposition is underpinned by rapidly improving AI models, the future opportunity dwarfs present-day metrics. Small optimizations compound, but they're dwarfed by the need to unlock entirely new markets as capabilities expand. Anthropic's growth team built the Chrome extension — a research-heavy, product-like initiative — because no one else was doing it and it unlocked multiple use cases for Co-work and Claude Code. That's the kind of large bet that pays off in an exponential world.

Amole's advice: if AI is central to your product's value (like Cursor, Lovable, or other AI-first companies), operate this way. If AI is a side feature and not your core value prop, stick to traditional growth ratios.


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Automating Growth with Claude Itself

🤖
CASH: Claude-Powered Growth
Anthropic's growth platform team runs an initiative called CASH (Claude Accelerates Sustainable Hyperrowth). Claude identifies opportunities, builds features, tests quality, and analyzes results — the full experiment loop.
📊
Win Rate: Junior PM Level
The system's win rate matches a junior PM with 2–3 years of experience. Not yet senior-level, but improving weekly. A few months ago, this wasn't possible at all; now it's delivering real revenue impact.
🎯
Starting Small, Scaling Fast
Currently focused on copy changes and minor UI tweaks. But as models improve, larger experiments become viable. The system «prints money» on autopilot — you press play and it runs. Human review still required for brand and quality, but less every week.
🔮
The Missing Piece: Stakeholder Alignment
The one thing Claude can't automate yet: cross-functional stakeholder management. For small projects, you can skip it. For large ones, humans still needed. Amole jokes: «We will have AGI and it will still be impossible to get six people in a room to align.»

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The PM-to-Engineer Ratio Is Inverting

Engineers using Claude Code deliver 2–3× output; PMs and designers are now squeezed.

Engineers are getting the most leverage from AI tools like Claude Code — effectively 2–3× output per person. A team of five engineers now functions like 15 in the old world. But PMs and designers haven't scaled proportionally, creating a squeeze. One PM used to manage five engineers; now they're managing the equivalent of 15–20. This is straining PM and design capacity across the company.

Anthropic's solution: deputize product-minded engineers to be mini-PMs. If a project requires two engineering-weeks or less, the engineer owns it — talking to legal, security, and cross-functional stakeholders. The PM advises if needed but isn't on the hook for execution. If a project is larger than two weeks, the PM drives it (unless they delegate). This isn't a clean rule — use judgment — but it's the default framework.

This shift elevates product-minded engineers dramatically. An engineer who can think like a PM becomes a unicorn. Their value goes up an order of magnitude. Meanwhile, Anthropic is hiring more PMs to fill the gap, because at scale, cross-functional coordination and stakeholder alignment still require human brains. The best use of a PM's time isn't shipping the 21st feature when 20 engineers are already shipping — it's improving the «why» and the «what» by 5%, which has exponentially higher leverage.


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Using Claude to Find Misalignment and Coach Yourself

Amole runs weekly automations where Claude reviews Slack to flag conflicts and gives him feedback as his manager.

1

Schedule Claude to Monitor Slack Weekly Using the Slack MCP (Model Context Protocol) in Co-work, Amole schedules Claude to scan Slack channels for projects he's working on and surface potential misalignment. It runs automatically and delivers a summary each week.

2

Identify Cross-Functional Conflicts Early Claude flags areas where teams may be duplicating work, have conflicting priorities, or are siloed. This prevents teams from spinning their wheels or discovering misalignment too late. One growth leader found major alignment issues that would have cost weeks of wasted effort.

3

Get Feedback as Your Manager Amole asks Claude to role-play as Ammy Vora, his manager. Claude reviews everything Amole did (or didn't do) that week, reads Ammy's public writing and internal Slack messages, then delivers feedback from her perspective. It's like having a coach who's «kind of drunk at times» — sometimes spot-on, sometimes irrelevant.

4

Use Notebook Channels and Skills for Context Anthropic employees maintain public «notebook channels» on Slack — like internal Twitter feeds where they share thoughts and priorities. Claude uses these, plus skills and project docs, to build a model of each person and give increasingly accurate feedback.


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The Secret Moat: Culture and Talent Density

Anthropic's real advantage isn't models — it's mission-driven culture and absurd talent concentration.

I look around, I'm like, man, I'm playing for Madrid, right? It's like you just like have the best people in the world. I think it's most the case on research. We have like the very very best researchers in the world. But even you look on product, we have Ammy Vora like she is phenomenal. We have Mike Krieger. You're like, 'Okay, casually started Instagram. He's here.' On growth we have John Egan who's the OG in growth engineering. We have Alexey who teaches growth engineering at Reforge. He's just like another dude on the team. My favorite here is like in LA a couple of months ago we had our onsite and I'm walking around 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.'

Amole Avasari


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Focus as a Forcing Function

Anthropic bet on B2B and coding early — not by choice, but by necessity.

Anthropic's sharp focus on B2B and coding use cases wasn't entirely strategic vision — it was necessity. Historically, they were the smallest, least-funded player in the space. They didn't have Meta or Google's free cash flow and distribution. They didn't have OpenAI's first-mover advantage. So they had to pick a very narrow focus to maximize their chance of reaching escape velocity.

Ben Mann wrote a memo in 2021, months after Anthropic was founded, arguing the company should focus on AI coding. This was years before anyone knew the size of the market. Leadership also believed deeply that coding would accelerate research — a mainstream view now, but prescient then. If Anthropic had the best coding models, researchers would build better tools faster, accelerating the research loop.

Amole describes this as «freedom through constraints.» When you have limited options, the path becomes clear. You stop wasting energy on excess choice. Ironically, Anthropic had built a chatbot before ChatGPT launched but chose not to release it for safety reasons. They didn't want to kick off a global AI arms race. When OpenAI launched ChatGPT and gained massive consumer traction, Anthropic's path became even clearer: go deep on B2B and coding, where focus and safety could be competitive advantages.


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Leaving Money on the Table Is a Growth Strategy

Anthropic is comfortable forgoing revenue to protect brand, safety, and user experience.

💡

Leaving Money on the Table Is a Growth Strategy

Growth teams often squeeze every last dollar out of users, but Amole sees this as a mistake — in both growth and life. If you're a founder raising money and you extract every dollar from investors, they won't come back next round. The same applies to growth. Anthropic is very comfortable leaving money on the table to prioritize AI safety, protect brand, maintain quality, and deliver a great user experience. When evaluating controversial tests, Amole asks: is this a red line we won't cross regardless of results, or is it uncomfortable but testable? AI safety falls into the first category — it's why the company exists. The long-term view: the best products in the world operate this way, and that focus on quality and values actually drives more growth over time.


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How to Thrive as a PM in the AI Future

🔧
Use the Tools Relentlessly
Use Claude Code, Co-work, and every new model release. Test what works, what fails, and what's newly possible. Product sense for AI products comes from hands-on experimentation. Each model unlock changes what's viable.
📈
Double Down on Your Spike
Identify the one skill where you have an unfair advantage — stakeholder alignment, craft, domain expertise — and become the best at it. Forget your weaknesses. In a world where AI automates the average, spikes matter exponentially more.
🔀
Go Interdisciplinary
The product-minded engineer is now a unicorn. So is the PM who can design or the designer who can code. Amole's edge: founder background + finance + sales + growth. Nick Lynn (financial services PM) came from investment banking and private equity. Find your unique combo.
🌊
Stay Radically Adaptable
Amole estimates 50–70% of how he operated in the past is irrelevant at Anthropic. Trying to apply old playbooks creates friction and limits impact. The job is changing faster than ever. Embrace it.

14

From Traumatic Brain Injury to Leading Growth at Anthropic

A brain injury forced Amole to relearn walking and working; it made him better.

In early 2022, Amole suffered a traumatic brain injury during a routine Muay Thai sparring session. For nine months, he couldn't work. The first few months were brutal: he couldn't shower or use the bathroom without help. Listening to music for 20 seconds made him nauseous. He couldn't look at screens. It took roughly six months before he was comfortable walking again. For a long time, it wasn't clear he'd ever work again.

Recovery required slowly increasing tolerance to stimuli — pushing just enough without triggering setbacks. After nine months, he returned to work. Then, a month into joining Mercury in mid-2023, he was re-injured when a bag hit his head getting off a plane. He was out for another two months. He's still not 100% healed — he experiences dizziness and headaches — but he's learned to work around them.

Amole credits the injury with making him more effective. He doesn't drink alcohol or caffeine. He takes short breaks between morning and lunch, and lunch and end of day — even on the craziest model launch days. He meditates regularly and does annual retreats at Spirit Rock. These aren't optional; they're survival mechanisms. But they've also given him space between awareness and reality — the place where choice lives. In a job as intense as leading growth at Anthropic, that space is what keeps him from losing his head. The injury taught him what one of his meditation teachers said: «True freedom in life is learning how to be content when you don't get what you want.»


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Люди

Amole Avasari
Head of Growth at Anthropic
guest
Lenny Rachitsky
Podcast Host & Newsletter Author
host
Mike Krieger
Chief Product Officer at Anthropic (co-founder of Instagram)
mentioned
Dario Amodei
CEO at Anthropic
mentioned
Daniela Amodei
Co-founder and President at Anthropic
mentioned
Ben Mann
Co-founder at Anthropic
mentioned
Ammy Vora
Amole's Manager at Anthropic (former podcast guest)
mentioned
Alexey Komissarouk
Growth Engineering Lead at Anthropic (teaches at Reforge)
mentioned
John Egan
Engineering Counterpart on Growth Team at Anthropic
mentioned
Joel
Head of Design at Anthropic
mentioned
Nick Lynn
Lead for Financial Services Product at Anthropic
mentioned
Eros Resmini
CMO of Discord (adviser to Amole)
mentioned

Глоссарий
ARR (Annual Recurring Revenue)The predictable revenue a company expects to receive annually from subscriptions or contracts.
ActivationThe stage in a user journey where a new user experiences the core value of a product for the first time, often measured by specific actions like completing onboarding or achieving a key outcome.
Capability OverhangWhen AI models improve so rapidly that the technology's capabilities far exceed users' awareness or ability to fully utilize them, creating a gap between potential and realized value.
MCP (Model Context Protocol)A protocol that allows AI models like Claude to connect to external data sources (e.g., Slack, Chrome) and retrieve context to perform tasks.
Agentic CodingAI systems that autonomously write, debug, and ship code with minimal human intervention, unlocking new markets by dramatically accelerating software development.

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