AI coding as a steak machine, not a chef
A memorable analogy for AI-assisted development: models can make building faster, but quality still depends on the human ability to specify, judge, test, and understand the system.
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Logged at IST: 2026-08-12 10:27 IST
What it is: Joe Ingeno sharing Yurii Sydorets’ essay, “Almost No Skill Required to Cook a Steak (Though You Probably Can’t Make a Decent One).”
Gist: Sydorets uses the steak analogy well: AI can make software creation feel as easy as putting meat in a hot pan, but consistently good results are still a craft problem. Models can follow recipes, generate starting points, and automate repetitive work, but they do not know the taste in your head unless you translate it into requirements, constraints, examples, tests, and feedback.
The sharper point is that outsourcing to a premium tool, agency, or framework may still leave you with the same burnt steak if everyone is using the same underlying AI cook. Acceptable software may pass for many users, but if you care about the result, you still need the judgment to notice when something is technically correct but wrong in the ways that matter.
Newsletter angle: Good companion to the recent “coding is still hard” note: AI reduces execution friction, but it increases the value of taste, judgment, and the ability to evaluate outputs rather than merely request them.