How Anthropic uses Claude Code: Agentic Software Engineering at Scale - Daisy Hollman
This talk details the engineering challenges and advanced primitives required for achieving agentic software engineering at scale, particularly within large monorepos. The core thesis is that scaling agents requires sophisticated context management—moving beyond simply increasing model size to implementing abstractions like Skills, Sub-agents, and Hooks. Key focus areas include managing limited context windows (currently around 1 million tokens) by ensuring tools and knowledge are only injected when relevant, thereby enabling complex, long-horizon tasks across massive codebases.
Key takeaways
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Context Engineering is the New Discipline
21:45
As agents become better at writing software, teaching them how to do it—managing context—is becoming the primary discipline of software engineering. This involves carefully selecting and injecting relevant information into the model's limited context window (the 'box').
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Scaling Requires Abstraction Primitives
26:45
To handle massive codebases, simple tool definitions are insufficient. Advanced primitives like Skills (lazy system prompts), Sub-agents (out-of-context processing), and Hooks (event-driven execution) are necessary to ensure that only relevant information is consumed by the model.
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The Importance of Feedback Loops
17:15
The fastest way to improve an agent's performance on a codebase is not necessarily a smarter model, but implementing tighter feedback loops (e.g., type checking, linting) that provide immediate, granular error detection during the tool-use process.
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Scaling Workflows Beyond Single Sessions
46:45
For enterprise use, scaling requires managing multiple concurrent agent sessions. Techniques like using dedicated worktrees and visual cues (e.g., color coding) are essential to manage cognitive load and maintain persistent agent identities across different tasks.