AI Coding: You're the Chef, Not the Steak Machine

AI Coding: The Steak Problem

AI can churn out code at an unprecedented pace. Developers now build nonstop, creating agents, workflows, and prompts without fully understanding the underlying systems. But what we get is often like a burnt steak: technically edible but far from the perfect medium-rare we imagined.

Yurii Sydorets, in a blog post that's climbing Hacker News (337 points, 367 comments), draws a sharp analogy: AI is a steak machine, not a chef. It can follow a recipe, flip at the right time, and drop in butter, but it can't see the picture in your head. You have to translate your vision into requirements, constraints, and tests. Even then, the output is limited by the model's context window and the system around it.

The Illusion of the Premium AI Product

Frustrated, many developers turn to paid AI tools or agencies, hoping someone else solved the problem. But often, they get the same burnt steak. Why? Because every restaurant hired the same AI cook. "Cost optimization," management says. Most users won't notice the mediocre quality—they tolerate weird interfaces and generated code nobody understands. But you'll notice, especially when you care about the product.

The Only Way Out: Learn to Cook

Sydorets argues there's only one real solution: learn to cook. Understand what heat does, why pan thickness matters, why resting matters. You'll ruin a few dinners, but eventually, you'll stop depending on luck. Software development is the same. AI can make you faster, automate repetitive tasks, and explain code, but it can't replace your judgment. It can't define quality or decide tradeoffs.

Practical Advice for Developers

To build good software with AI, you still need to understand software. You need to know what you're asking for, how to judge the output, and when the machine is confidently serving charcoal. Keep learning, keep failing, and eventually, you'll produce the results you want. Then you can hire a few AI cooks of your own—most people won't notice the difference, but you will.

The Takeaway

Don't expect AI to turn you into a Michelin-starred chef overnight. Instead, invest in your own skills. Learn the fundamentals of your stack, understand the architecture, and practice code review. Use AI as a tool to amplify your abilities, not as a substitute for them. As Sydorets puts it, "To build good software with AI, you still have to understand software."