🧠 The Danger of Code That “Just Appears”#
Have you ever finished an AI coding session and felt like you wrote a lot of code… but understood nothing? 🤔
The Problem with Agentic Code Generation#
When we use AI to generate code, we get all the outward signs of having programmed (the code is there, it works), but without the internal processes that happen when we write it by hand: comprehension, retention, learning.
Default code generation is antithetical to skill retention. The “ask and receive” UX resembles a slot machine: pull the lever and get a reward.
🛠️ Strategies for Using AI More Deliberately#
- ✍️ Write the initial implementation yourself and ask the agent to review it
- ❓ Use the agent to ask questions about code you don’t understand — not to write it
- ⚖️ Ask it to think through two approaches and then critique the one you didn’t pick
- ⏳ Start using the agent only after 20 minutes working the problem alone
- 📚 Go back to reading books and academic papers
All these strategies add deliberate friction that, in the short term, slows you down, but in the long term strengthens your foundation as a developer.
💡 Explanation in a nutshell#
If an assistant does your homework for you every day, you eventually forget how to do it yourself. The same happens with AI: if it always gives you the code, you stop learning to think like a programmer. The idea is to use it as a trainer, not a replacement.
More information at the link 👇
