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01:37

Lessons from Building Claude Code: How We Use Skills

Claude Code 技能实战:Anthropic 内部数百条技能的经验与分类

Anthropic engineers share practical lessons from maintaining hundreds of Claude Code skills internally. The post categorizes skills into nine types—library reference, product verification, data fetching, business process automation, code scaffolding, code quality, CI/CD, runbooks, and infrastructure ops—and offers concrete writing tips: focus on non-obvious hints, build gotchas sections, use the filesystem for progressive disclosure, avoid over-constraint, design setup flows, treat the description field as a trigger for the model, store memory (logs, JSON, SQLite), and bundle scripts/libraries to reduce token waste. It also covers distribution strategies (in-repo vs. marketplace), skill composition, and usage measurement via PreToolUse hooks. A must-read for anyone building agent-centric workflows.

01:36

Rewriting Bun in Rust: 535K Lines, 11 Days, 64 AI Agents

11天、64个AI Agent、535K行代码:Bun从Zig到Rust的史诗级重写

Bun's creator Jarred Sumner recounts how he used Anthropic's Claude Fable 5 to rewrite Bun's 535,496 lines of Zig into Rust in 11 days. The motivation: Zig's manual memory management caused numerous use-after-free, double-free, and memory leaks when mixed with JavaScriptCore's GC. Instead of an incremental port, he orchestrated 64 Claude agents in parallel using dynamic workflows and adversarial review. 100% of Bun's test suite (over 600k assertions) passed on all 6 platforms. The rewrite fixed 128 bugs, reduced memory usage by up to 90%, shrank the binary by ~20%, and improved throughput by 2-5%. The article details the workflow, common porting mistakes (e.g., debug_assert! side effects, slice overruns, comptime format differences), and how Rust's Drop systematically prevented memory leaks. A first-hand account of using cutting-edge AI to accomplish a year-long team project in less than two weeks.