Boris Cherny: How We Built Claude Code

Boris Cherny: How We Built Claude Code

Y CombinatorFeb 17, 202650m

Boris Cherny (guest), Garry Tan (host), Jared Friedman (host), Garry Tan (host)

Building for the model six months aheadTerminal as an accidental but durable form factorTool use as the key unlock (bash, scripts)Latent demand and user-driven feature discoveryCLAUDE.md as lightweight, shared team scaffoldingVerbosity trade-offs and configurable transparencyPlan mode, subagents, swarms, and agent topologiesProductivity measurement and rapid codebase rewritesDev tools design parallels with TypeScriptAI safety, mission, and ASL-3/ASL-4 concerns

In this episode of Y Combinator, featuring Boris Cherny and Garry Tan, Boris Cherny: How We Built Claude Code explores inside Claude Code: terminals, tool-use, iteration, and model-driven design Claude Code began as Boris’s quick-and-cheap terminal chat client to learn the Anthropic API, then became powerful once tool use (bash) revealed the model’s drive to interact with the real world.

Inside Claude Code: terminals, tool-use, iteration, and model-driven design

Claude Code began as Boris’s quick-and-cheap terminal chat client to learn the Anthropic API, then became powerful once tool use (bash) revealed the model’s drive to interact with the real world.

Internal adoption at Anthropic spiked organically (“vertical” usage chart), with early value in Git automation, bash/Kubernetes operations, and safer coding tasks like unit tests—before coding quality dramatically improved.

Product development is driven by “latent demand” and relentless iteration: features like CLAUDE.md and plan mode emerged directly from observed user behavior and GitHub/Slack feedback, while UI/“scaffolding” is treated as temporary tech debt in the face of rapid model gains.

Cherny forecasts continued shifts: less need for explicit plan mode, more multi-agent “teams/swarm” workflows, and a future where coding is broadly solved and software roles converge toward generalist “builders,” alongside heightened attention to AI safety risks.

Key Takeaways

Build for the next model, not today’s model.

Cherny’s core heuristic is to target what models are currently weak at but improving quickly, because capability jumps can erase elaborate product work and create leapfrogging risk.

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Tool use is the “aha”: models want to act, not just chat.

Claude Code’s inflection point came when bash tool use enabled real-world interaction (e. ...

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The terminal succeeded because it minimized UI commitments during rapid model change.

CLI started as the cheapest prototype, then persisted because any heavier UI risked becoming irrelevant within months; the team kept flexibility while models matured.

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Let user behavior invent the roadmap (latent demand).

Plan mode and CLAUDE. ...

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Keep CLAUDE.md minimal and refresh aggressively.

Cherny’s own file is only two lines; when instruction files bloat, he recommends deleting and re-adding only what’s necessary, since newer models typically require less steering.

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Default transparency matters; make verbosity adjustable.

Attempts to hide bash output caused internal revolt; later, summarizing tool actions worked better as models became more reliable, but external users wanted details—leading to a configurable verbose mode.

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Scaffolding is a short-lived advantage and should be treated as tech debt.

Non-model code can yield ~10–20% gains, but those gains are often “wiped out” by the next model; Claude Code frequently unships tools and rewrites components because nothing stays stable long.

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Multi-agent workflows increase capability via parallelism and clean context windows.

Teams/swarms leverage “uncorrelated context windows” as test-time compute; a plugins feature was reportedly built over a weekend by a swarm operating from a spec and an Asana task board.

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The key human skill is beginner mindset + scientific thinking.

As models improve, entrenched senior-engineer opinions can become liabilities; Cherny screens for adaptability by probing when candidates were wrong and how they learned.

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Coding roles will broaden toward ‘builder’ generalists—while safety risks rise.

He predicts coding becomes “generally solved,” enabling PMs/design/finance to ship via agents, but also flags ASL-4-level dangers (recursive self-improvement, misuse like bio/zero-days) as a serious parallel track.

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Notable Quotes

“We don’t build for the model of today, we build for the model six months from now.”

Boris Cherny

“It’s unbelievable that we’re still using a terminal.”

Boris Cherny

“The model… it just wants to use tools. That’s all it wants.”

Boris Cherny

“Plan mode… there’s no big secret to it. All it does is… ‘Please don’t code.’”

Boris Cherny

“There’s no part of Claude Code that was around six months ago.”

Boris Cherny

Questions Answered in This Episode

You say “build for the model six months from now”—what specific capability gaps did you bet on for Claude Code that later became ‘free’ with newer models?

Claude Code began as Boris’s quick-and-cheap terminal chat client to learn the Anthropic API, then became powerful once tool use (bash) revealed the model’s drive to interact with the real world.

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Where did the terminal form factor actively constrain the design in a good way (features you *didn’t* build because CLI forced simplicity)?

Internal adoption at Anthropic spiked organically (“vertical” usage chart), with early value in Git automation, bash/Kubernetes operations, and safer coding tasks like unit tests—before coding quality dramatically improved.

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Can you share concrete examples of ‘scaffolding’ you removed after a model upgrade made it unnecessary, and what you learned from that deletion?

Product development is driven by “latent demand” and relentless iteration: features like CLAUDE. ...

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What signals tell you it’s time to summarize tool output (file reads/searches) versus showing raw details—especially as user trust varies?

Cherny forecasts continued shifts: less need for explicit plan mode, more multi-agent “teams/swarm” workflows, and a future where coding is broadly solved and software roles converge toward generalist “builders,” alongside heightened attention to AI safety risks.

Get the full analysis with uListen AI

For teams adopting CLAUDE.md: what belongs in a shared repo-level CLAUDE.md vs a personal one, and how do you govern changes without creating bureaucracy?

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Transcript Preview

Boris Cherny

at Anthropic, the way that we thought about it is, we don't build for the model of today, we build for the model six months from now. That's actually, like, still my advice to, to founders that are building on LLMs. Just try to think about, like, what is that frontier where the model is not very good at today? 'Cause it's gonna get good at it. All of Claude Code has just been written and rewritten and rewritten and rewritten over and over and over. There is no part of Claude Code that was around six months ago. You try a thing, you give it to users, you talk to users, you learn, and then eventually you might end up at a good idea. Sometimes you don't.

Garry Tan

Are you also in the back of your mind thinking that maybe, like, in six months you won't need to prompt that explicitly, but the model will just be good enough to figure out on its own?

Boris Cherny

Maybe in a month. [laughing]

Jared Friedman

[laughing] No more need for plan mode in a month?

Boris Cherny

[laughing]

Garry Tan

Oh, my God.

Jared Friedman

[music]

Garry Tan

Welcome to another episode of The Lightcone, and today we have an extremely special guest, Boris Cherny, the creator, engineer of Claude Code. Boris, thanks for joining us.

Boris Cherny

Thanks for having me.

Garry Tan

Thanks for creating a thing that has taken away my sleep for about three weeks straight. [laughing]

Jared Friedman

[laughing]

Boris Cherny

[laughing]

Garry Tan

I am very addicted to Claude Code, and, uh, it feels like rocket boosters. Has it felt like this for people, like, for, you know, months at this point? I think it was, like, end of November is where, uh, a lot of my friends said, like, something changed.

Boris Cherny

I remember for me, I felt this way when I first created Claude Code, and I didn't yet know if I was onto something. I kinda felt like I was onto something, and then that's when I wasn't sleeping. [laughing]

Garry Tan

Yeah.

Boris Cherny

And that was just like-

Garry Tan

When was that?

Boris Cherny

- three straight months. This was, uh, September twenty twenty-four. Yeah, it was, like, three straight months. I, I didn't take a single day of vacation, worked through the weekends, worked every single night. I was just like, "Oh, my God, this is-- I think this is gonna be a thing. I don't know if it's useful yet," [chuckles] 'cause it, it couldn't actually code yet.

Garry Tan

If you look back on, uh, those moments to now, like, what would be, like, the most surprising thing about this moment right now?

Boris Cherny

It's unbelievable that we're still using a terminal. That was supposed to be the starting point. I didn't think that would be the ending point. And then the second one is that it's even useful, 'cause, uh, you know, at the beginning, it didn't really write code. Even in February, when we cheated, it wrote maybe, like, ten percent of my code or something like that. I didn't really use it to write code. It wasn't very good at it. I still wrote most of my code by hand. Uh, so the fact that it, it-- actually, like, our bets paid off, and it got good at the thing that we thought it was gonna get good at, because it wasn't obvious. At Anthropic, the way that we thought about it is, we don't build for the model of today. We build for the model six months from now, and that's actually, like, still my advice to, to founders that are building on LLMs is, you know, just try to think about, like, what is that frontier where the model is not very good at today? Um, 'cause it's gonna get good at it, and you just have to wait.

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