40:I[185,["/_next/static/chunks/2ys9ev5m3_24i.js","/_next/static/chunks/3pomb8r7ja54n.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/178kgr5-cejk9.js","/_next/static/chunks/1v5ewlr55okcj.js","/_next/static/chunks/3jnlvw-emqotx.js"],"SendEmailButton"] 42:I[63625,["/_next/static/chunks/2ys9ev5m3_24i.js","/_next/static/chunks/3pomb8r7ja54n.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/178kgr5-cejk9.js","/_next/static/chunks/1v5ewlr55okcj.js","/_next/static/chunks/3jnlvw-emqotx.js"],"AddToLibraryButton"] 43:I[29721,["/_next/static/chunks/2ys9ev5m3_24i.js","/_next/static/chunks/3pomb8r7ja54n.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/178kgr5-cejk9.js","/_next/static/chunks/1v5ewlr55okcj.js","/_next/static/chunks/3jnlvw-emqotx.js"],"ShareButton"] 44:I[58016,["/_next/static/chunks/2ys9ev5m3_24i.js","/_next/static/chunks/3pomb8r7ja54n.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/178kgr5-cejk9.js","/_next/static/chunks/1v5ewlr55okcj.js","/_next/static/chunks/3jnlvw-emqotx.js"],"ProcessEpisodeButton"] 45:I[45269,["/_next/static/chunks/2ys9ev5m3_24i.js","/_next/static/chunks/3pomb8r7ja54n.js","/_next/static/chunks/42spz6paskvb6.js","/_next/static/chunks/178kgr5-cejk9.js","/_next/static/chunks/1v5ewlr55okcj.js","/_next/static/chunks/3jnlvw-emqotx.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":"2026-06-28T14:00:00.000Z","children":"June 28, 2026"}],["$","span",null,{"aria-hidden":true,"children":"·"}],["$","span",null,{"children":"00:09:04"}],false]}] 41:T482,Experienced builders keep getting burned by the same mistake: they hand an LLM vague intent the way they would brief a senior engineer, and then blame the model when the output is wrong. The real problem is a mental model mismatch. LLMs are more like compilers than collaborators, and once builders internalize that distinction, their output quality improves immediately and their frustration drops sharply.

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.