Lenny's PodcastClaude Code head Boris Cherny: Why he ships 30 PRs a day
Through hundred-percent AI-written code and parallel running agents on autopilot; 'clodify everything,' unlimited tokens, and latent demand make the builder.
CHAPTERS
Boris’s “coding is solved” thesis: 100% AI-written code and multi-agent workflow
Boris opens with a striking claim: he hasn’t hand-edited code since November, ships 10–30 PRs a day, and runs multiple Claude agents in parallel. He frames this as the beginning of a broader shift where coding becomes universally accessible and traditional roles start to blur.
Why he briefly left for Cursor—and why Anthropic’s mission pulled him back
Lenny asks about Boris’s two-week stint at Cursor. Boris explains he admired Cursor’s product and team, but quickly realized he deeply needed Anthropic’s safety-focused mission to feel fulfilled.
Claude Code’s first year: from internal hack to a global development force
Boris reflects on Claude Code’s rapid adoption, including staggering market-level metrics and accelerating growth. He shares that it began as a small prototype inside the Labs team, and only later became widely understood externally.
Why the terminal won: under-resourcing, speed, and keeping up with model improvement
Boris explains the surprising product decision to stay terminal-first. The core reason: the model was improving so quickly that heavier form factors couldn’t keep up, and shipping fast mattered more than polish early on.
From partial assist to 100%: the exponential curve and the ‘no IDE’ prediction
Boris describes how Claude’s contribution grew from ~20–30% to crossing 100% in November, matching an exponential trajectory. He recounts predicting engineers might not need IDEs by year-end—once a shocking idea, now increasingly plausible.
How work changes when AI writes everything: review, safety checkpoints, and idea generation
With AI producing most code, bottlenecks shift to verification and deciding what to build. Boris explains Anthropic’s practices—Claude reviewing all PRs, humans still doing final checks, and the emerging frontier where Claude proposes fixes/features from telemetry and feedback.
Team operating principles: ‘clodify’ everything, underfund projects, move today
Boris shares cultural principles that shape Claude Code’s execution speed. Understaffing creates pressure to automate; encouraging immediacy (“if you can do it today, do it today”) turns Claude into a force multiplier.
Tokens economics: ‘start loose’ to discover what’s possible, optimize after PMF
Boris argues companies should initially remove token constraints so engineers can explore. He notes that even high token spend can be rational, and in some cases individual engineers may burn hundreds of thousands per month—yet the ROI can still be worth it.
Do engineers lose something? Enjoyment, atrophy fears, and the printing-press analogy
Boris explains he enjoys coding more now because tedious details vanish, though he acknowledges others may feel loss. He frames the shift historically: like the printing press democratizing literacy, coding becomes broadly accessible and unlocks unforeseen societal change.
Roles after ‘software engineer’: builders, generalists, and everyone coding
The conversation shifts to how adjacent roles (PM, design, data science) will be impacted as agents spread beyond engineering. Boris predicts titles blur: more overlap, broader generalism rewarded, and “software engineer” potentially replaced by “builder.”
Latent demand: building where users (and the model) already are
Boris explains “latent demand” as spotting people misusing a product to solve real needs—then productizing that behavior. He extends the idea: also watch what the model “wants” to do and design minimal scaffolding that enables it, rather than boxing it in.
Cowork in 10 days: agentic desktop automation, guardrails, and early release for learning
Boris shares how Cowork shipped quickly by essentially embedding Claude Code into the desktop app, powered by Claude Code itself. He emphasizes releasing early not only for product iteration, but also to understand safety in real-world conditions.
Anthropic’s safety stack: interpretability, evals, and ‘in the wild’ behavior
Boris outlines a three-layer approach to safety: mechanistic interpretability during training, controlled evals, and real-world observation. He highlights Anthropic’s efforts to publish and open-source safety tooling to create a ‘race to the top.’
Power-user workflows: multi-interface coding, plan mode, and running agents constantly
Boris shares practical tips for getting more out of Claude Code and Cowork. He recommends the most capable model, frequent use of plan mode, and experimenting with multiple interfaces (terminal, desktop, iOS) while running many agents in parallel.
Building AI products: don’t box the model, heed the Bitter Lesson, build for 6 months ahead
Boris advises builders to avoid rigid workflows and over-scaffolding, because model improvements quickly obsolete them. He urges teams to bet on generality (the “Bitter Lesson”) and design for the capabilities models will have soon, not just today.
Lightning round + personal arcs: Ukraine/Odessa connection, Twitter feedback loop, and miso post-AGI
In the closing segment, Boris and Lenny discover they were both born in Odessa, Ukraine. Boris explains why he became active on Twitter (fast bug fixes and feedback), shares favorite books, and answers a playful ‘post-AGI’ question with a return to rural life and miso-making.
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