AI Skills Are Never Finished: Iterating Agents Through Errors
dSebastien · x · 2026-08-03
The author shares a core insight on building AI skills: a good skill is never truly finished.
In practice, every invocation can reveal missed steps or weird edge cases. An effective approach is to ask the AI within the same session what went wrong and have it update the skill to prevent future errors. Through this continuous patching feedback loop, AI skills remain alive and constantly evolve.
Related event: A Practical Guide to Building Reliable AI Skills(2 posts)→
More from coding & agent
- Fixing MCP failure detector: false positives traced to SDK error code overloading — Thirumalaiboobathi · 2026-08-03
- SkillDeck: Native macOS GUI for Managing Multi-Agent Coding Skills — tom_doerr · 2026-08-03
- Turso Database Overcomes SQLite Limits with Concurrent Writes — glcst · 2026-08-03
- Use Vendor Contracts to Mandate AI-Assisted Code Security Audits — chrisrohlf · 2026-08-03
- Cloudflare Open-Sources @cloudflare/computer: A Smart Agent Runtime for Isolates and Containers — Cloudflare Blog · 2026-08-03
- The Daily Diff: Lua-Native Shell and the Pitfalls of Over-Proving in AI Agents — arpit_bhayani · 2026-08-03