Conversation with Anthropic Growth Lead: How to Achieve an Exponential Leap to $19 Billion with Minimal Resources?

It’s April 2026. Lenny Rachitsky sits in front of a podcast microphone, listening as the growth lead at Anthropic, Amol Avasare, rattles off the numbers across the table. He pauses for a beat.

Fourteen months ago, Anthropic’s annual recurring revenue (ARR) had just broken $1 billion. That was early 2025. Today—one year and two months later—that figure has skyrocketed to $19 billion. Atlassian and Palantir have been at it for nearly two decades, and their ARR has been stuck around $4–$5 billion. For Anthropic, it’s like they conjure up a Palantir out of thin air every few months.

That kind of momentum makes everyone inside the company feel like something about it isn’t real.

When Amol was still toiling as a regular user, mucking around with Claude, he watched this smart but slightly clunky AI when it came to the commercial feedback loop. He sighed. He was sure this gang of geeks didn’t have a single decent growth team. Based on the instincts he’d honed from founding companies before, he emailed the product lead at the time, Mike Krieger. Yes—the guy who casually co-founded Instagram.

The email didn’t contain a single word of small talk. The gist was: your product is great, but you have no growth strategy—you need to talk.

Mike replied. Amol became the only product manager in that company who had gotten in via cold email, and later climbed all the way to the top growth spot.

Before the story goes any further, list three unconventional insights Amol brought—against conventional wisdom.

• Smart growth deliberately creates precise friction to filter and truly understand your users.

• Traditional hands-on A/B testing basically fails in the face of AI’s explosive, index-level growth. Either you bet on the plates that can amplify by 1,000x in the future—or do nothing.

• If project development time is less than two weeks, you can temporarily skip a product manager and have engineers take responsibility for the outcomes themselves.

The success disasters that keep you trapped

Most of the 70% of growth experience Amol had built up at other companies barely applies here. Half his day is spent cleaning up a mess that his team internally calls “success disasters.” New models are too popular—traffic instantly blows through the servers—or they directly crush the existing user pathways.

All the metrics on the screen are green. The line shoots up toward the upper-right—but the whole team’s nerves are stretched so tight they’re about to snap.

In this context, the classic “workplace three-corner triangle” starts to break apart. With tools like Claude Code, engineers’ output efficiency can double or even triple. Back then, one product manager coordinated with five engineers; now those five people’s code output can equal fifteen people.

PMs get strangled by delivery volume and can’t keep up. Amol’s solution is so direct it’s almost brutal: for work that doesn’t exceed two weeks of engineering effort, engineers handle it as their own product managers. They align stakeholders themselves. They even pick fights with legal themselves.

If even writing documents and running data reports can be replaced by machines, what are human PMs supposed to do to survive?

Amol’s strategy is to stop obsessing over standardized skills and start looking for points where fire crosses. Find those odd combinations of experiences in you. Amol has founded companies, worked in investment banking, and almost went into sales—then he blended it all into building commercial growth. In an era when a big model can write marketing copy for you, only people with a bit of cross-domain “back-alley” experience won’t be so easily cut by algorithms.

Growth hackers taken over by big models

Facing the pushback—this acceleration—from technology, human reaction speed can’t keep up anymore.

They built a project called CASH (Claude Accelerates Sustainable Hypergrowth). In simple terms, it’s letting Claude take over growth experiments itself.

The system automatically identifies opportunities, forms hypotheses, modifies the copy and UI code on its own, ships to run tests, and finally puts the data results on the table. Amol calculated that the system’s win rate is already not worse than that of a junior product manager with three years of experience. As long as you set the brand boundaries, it’s an unrelenting machine.

If machines can write docs and run data, what are humans doing?

Amol dumps expense reports and meeting-room bookings into AI. Even more interesting: every week, he has Claude scan his direct supervisor Ami Vora’s public articles and internal Slack chat records. Then he asks the AI: based on what you know about Ami, and on what I did this week, how do you think she’ll respond?

He’s using big models to get a read on the boss’s temperament in advance. That sounds a bit absurd—but it works extremely well.

The head that got shattered in one kick

Amol isn’t the kind of Silicon Valley elite whose life has gone smoothly.

In 2022, during a regular mixed martial arts (MMA) training session, Amol took a solid kick to the head.

Life instantly got yanked to a screeching halt.

For nine straight months, he couldn’t work. In the first few months, besides taking showers and using the bathroom, his wife handled everything for him. Listening to 20 seconds of music made him nauseous and vomit. Looking at the world on a screen made everything spin—literally. It took him half a year to relearn how to walk like a normal person. Back then, he even discussed with his wife what they’d do if his life was ruined—how to live afterward.

Rehabilitation for brain injury is an excruciating process. But it was those days of probing the edge of despair that gave him a steadiness—unusual, hard to explain.

Later, after joining Anthropic, facing growth curves and work noise that were enough to make anyone’s nerves fray, he found he no longer worried so easily. Someone who’s lost even basic survival capacity wouldn’t be frightened by a few data tables bouncing wildly.

Because he’d lost everything, he became obsessed with constraints. Like Anthropic in its early days, when it was so broke it barely had change—no Meta cash, no OpenAI first-mover advantage. They had to bet all their chips on B2B and code generation. The path they were forced to choose due to having no money and no resources, ironically, helped them dodge the meaningless money-burning death spiral at the hands of big companies.

Your anti-derail rehabilitation guide

Finally, a few wake-up tips for workplace people who are being dragged almost out of control by the AI era.

Learn to leave a little money on the table.

Never try to squeeze out the last drop of profit. Sacrificing user experience or breaking safety guardrails just for a handful of conversion-rate points is extremely short-sighted. Giving up immediate monetization opportunities for the sake of safety principles—this restraint that pushes money outward—has actually become Anthropic’s toughest survival barrier today.

Force the power cut.

Even if the company brings in tens of millions of dollars every day and there are countdowns everywhere to new model releases, Amol forces himself to unplug the power twice a day—morning and afternoon—and spends ten minutes alone in the meditation area of his office.

The world doesn’t lack your ten minutes to change things, but you need those ten minutes to confirm you’re still alive.

After all, no matter how wild an exponential growth curve gets, it can’t withstand some fragile blood vessel in your head suddenly rupturing.