Carson Gross answers a question his computer science students increasingly ask: is programming still worth learning when AI can write the code? His “Yes, and…” is less a job-market forecast than a warning about how expertise develops. Letting an agent finish the exercise can also remove the experience you need to judge its output.

  • Use AI as a teaching assistant: explain concepts, unfamiliar tools, and the obstacles that leave you stuck before the real learning starts.
  • Keep writing code yourself. Gross argues that hands-on practice develops the understanding needed to read and maintain generated code.
  • Don’t mistake prompting for a reliable compiler—a tool that translates a programming language according to specified rules. Gross says AI can add unnecessary complexity rather than remove it.
  • For experienced developers, his preferred uses are bounded: analyzing code, generating small pieces, exploring disposable prototypes, and suggesting tests. He keeps API design—the interfaces other code depends on—in his own hands.

The employer side matters too. Gross asks companies to let juniors write at least some code, even when generation looks faster. Otherwise, the industry is spending expertise it has not arranged to replenish.

The 69-comment thread on Hacker News complicates the learning argument rather than simply endorsing it.

What the thread adds

  • layer8 — sharpens the compiler comparison beyond randomness: “You could make an AI deterministic by fixing its source of randomness. That still wouldn’t allow you to reason about how its output will change when (for example) you add or remove a word in the prompt.”
  • tengbretson — challenges the assumption that writing automatically teaches reading: “It could very well be that reading and writing are two separate (though related) skills that require intentional practice and honing on their own.”
  • glimshe — offers a counterexample to treating generated code as surrendered control: “Assuming that you truly understand and own every line of the LLM’s output, the model is almost working like a macro.”
  • johsole — reports a different workplace bottleneck: “We’ve seen a roughly 30% increase in speed of new features, so the same number of devs are building a lot quicker.” This is one commenter’s account, not an independently verified productivity measure.
  • omoikane — responding to that account, identifies the maintenance risk: “It’s a lot of risk for companies to be accumulating code faster than developers can understand them.”

Handles are pseudonymous; HN publishes no per-comment scores. The source ordering is HN’s ranking, and this usefulness-selected slice of the thread is not a consensus.