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The Creator of Claude Code on The Hottest Piece of Software in the World
Brief
Claude Code — Anthropic’s agent-oriented coding product — was the subject of this Odd Lots episode (published July 20, 2026) with guest Boris Cherney, who leads Claude Code. Cherney framed the product as an outgrowth of Anthropic’s long-standing safety mission: models must be tested in the wild because laboratory checks and mechanistic interpretability don’t reveal all real-world usage patterns. He traced Claude Code’s user growth to concrete model-capability milestones (Opus 4 in May 2025, Opus 4.5 in Nov 2025, Opus 4.6 in Feb 2026) and argued that the harness intentionally uses the same public Anthropic API customers use so product improvements and model gains benefit everyone.
The interview pivoted to safety, governance and enterprise concerns. Cherney described multiple technical guardrails — an open-source sandbox that limits file and web access, an automode permission flow that surfaces dangerous commands, and neuron-level probes from mechanistic interpretability — and cited a $20,000 red-team competition in which external researchers could prompt-inject other models but (he said) could not compromise Anthropic’s model in Claude Code. He acknowledged staged rollouts for higher-risk frontier models (Mythos/Glasswing) while saying broadly useful models like Fable are widely accessible; many enterprise customers favor per-token pricing to avoid blunt rate limits.
On capability and impact, Cherney argued Claude Code now writes code that can beat human first drafts for many tasks and changes engineering workflows: he claimed that since Nov 2025 he personally has had 100% of his code produced by Claude Code and estimated Anthropic-wide usage around 90%. He gave a concrete case where an engineer migrated Bun from Zig to Rust in ~11 days with Claude Code (cost ~USD 150k in credits), an operation that previously would have required many engineers over months. Hosts Joe Wisenthal and Tracy Alloway probed implications — job roles, UI changes (terminal vs. Slack/desktop/mobile), governance, and intra-office friction when an agent interjects in chat — and Cherney answered that organizations that make Claude central to workflows realize the biggest productivity gains, while also stressing continued investment in alignment, red‑teaming and careful rollouts as model capabilities advance.
Why it matters
Boris Cherney (head of Claude Code at Anthropic) said Claude Code was born from Anthropic's safety-first agenda: the team built a coding product to learn about real-world model behavior and safety when models interact with the world by writing code.
Key details
- Model improvements drove Claude Code adoption: Cherney cited clear growth inflection points tied to model releases — Opus 4 (May 2025), Opus 4.5 (November 2025) and Opus 4.6 (February 2026) — and said later Fable/Mythos-class models continued that trend.
- Anthropic built layered defenses against prompt injection and other attacks: Cherney described an open-source sandbox, an 'automode' permission system, mechanistic interpretability probes, and a $20,000 external red-team competition in which outside researchers could prompt-inject every tested model except Anthropic's Claude (per his claim).
- Cherney reported heavy internal and enterprise usage: since November 2025 he says 100% of his personal code has been written with Claude Code and Anthropic's internal average is roughly 90% code authored by Claude Code; he named customers including Airbnb, Ramp, Salesforce, Deloitte and NASA.
- Claude Code is being used for large migrations and productivity projects: Cherney highlighted a migration — converting Bun's codebase from Zig to Rust — completed by one engineer plus Claude Code in about 11 days, costing roughly $150,000 in cloud credits instead of a multi-person year-long project.
- Business and rollout policy: Cherney distinguished frontier / high-risk models (Mythos) that required staged access (Project Glasswing/whitelists) from broadly available models (Fable), and said many enterprise customers prefer per-token billing rather than hard rate limits.