Show Notes
The day your software does something absurd is coming, and debugging isn't a coding skill locked behind a keyboard — it's a learnable way of thinking. This episode, the ninth in a ten-part beginner series on building software with AI, shows how evidence beats vibes and how two plain questions dissolve most apparent catastrophes. It's a mindset you can point at any misbehaving technology, from a database to your wifi.
In this episode: - Why humans and AI agents both reach for confident, wrong stories — and why you demand evidence before theories - The two core moves: reproduce the fault with the smallest recipe, then isolate it by halving the journey - Two questions that defuse panic: what am I looking at, and as whom? - Stale state as the recurring villain behind fixes that won't stick - How to direct Claude Code or Codex to investigate first and cage the bug with a failing test - A real case where data looked lost but was only hidden by a missing key
Sources: episode-09-when-it-breaks.md
Full episode page: https://fatsandsugars.com/ai-hype-signal/how-to-build-software-with-ai-ep-9-when-it-breaks/
AI Hype & Signal is produced with AI, including its two synthetic hosts, and every episode is grounded in cited sources and reviewed before release. Even so, it is intended for general information and discussion, not professional advice, so please check anything important against the original sources linked above before relying on it.
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