40:I[185,["/_next/static/chunks/3xnt26d00_zk-.js","/_next/static/chunks/1s-yni1uf2lwd.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/06x30xgfe6iur.js","/_next/static/chunks/3b4qrzgkt_l12.js","/_next/static/chunks/15lgs8s22dk5l.js"],"SendEmailButton"] 42:I[63625,["/_next/static/chunks/3xnt26d00_zk-.js","/_next/static/chunks/1s-yni1uf2lwd.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/06x30xgfe6iur.js","/_next/static/chunks/3b4qrzgkt_l12.js","/_next/static/chunks/15lgs8s22dk5l.js"],"AddToLibraryButton"] 43:I[29721,["/_next/static/chunks/3xnt26d00_zk-.js","/_next/static/chunks/1s-yni1uf2lwd.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/06x30xgfe6iur.js","/_next/static/chunks/3b4qrzgkt_l12.js","/_next/static/chunks/15lgs8s22dk5l.js"],"ShareButton"] 44:I[58016,["/_next/static/chunks/3xnt26d00_zk-.js","/_next/static/chunks/1s-yni1uf2lwd.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/06x30xgfe6iur.js","/_next/static/chunks/3b4qrzgkt_l12.js","/_next/static/chunks/15lgs8s22dk5l.js"],"ProcessEpisodeButton"] 45:I[45269,["/_next/static/chunks/3xnt26d00_zk-.js","/_next/static/chunks/1s-yni1uf2lwd.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/06x30xgfe6iur.js","/_next/static/chunks/3b4qrzgkt_l12.js","/_next/static/chunks/15lgs8s22dk5l.js"],"SignupCTA"] 3a:["$","div",null,{"className":"flex flex-wrap items-center gap-x-4 gap-y-1 font-mono text-[12px] uppercase tracking-[0.1em] text-[color:var(--fg-3)]","children":[["$","time",null,{"dateTime":"2026-08-05T22:00:00.000Z","children":"August 5, 2026"}],["$","span",null,{"aria-hidden":true,"children":"·"}],["$","span",null,{"children":"00:09:52"}],false]}] 41:T4dd,Every builder learns early that vague prompts produce bad code, so the natural correction is to add more detail. But there is a ceiling: past a certain point, each additional constraint you write into a prompt makes the output worse, not better, because the model starts optimizing for satisfying your list instead of solving your problem. This episode maps where that ceiling sits, what it looks like when you cross it, and why the fix is moving detail out of prompts and into the codebase itself.

Produced by VoxCrea.AI

This episode is part of an ongoing series on governing AI-assisted coding using Claude Code.

👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way.
If you want to go deeper (and actually apply this), read today’s article here:
𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬

At aijoe.ai, we build AI-powered systems like the ones discussed in this series.
If you’re ready to turn an idea into a working application, we’d be glad to help.