Good advice yesterday, good advice today, and good advice tomorrow.

I don't remember if I read this advice or just intuited it myself (perhaps after some hard lessons), but it's a programming habit I've kept for as long as I can remember (I started coding in the 90s). If I feel rushed, e.g. someone looking over my shoulder, and I copy+paste something, it always leaves me with a sense of unease. It creates a memory & comprehension hole that sticks out like a sore thumb, even for seemingly simple snippets. You can't really be sure it's simple without stepping through it carefully, and simple can be deceptive because it's usually the interactions and assumptions wrt surrounding code that lead to surprises. Typing out code manually gives you time and space to consider the broader picture.

What I did is kinda similar, I downgraded to $20 plan and just ask questions and almost never let it write the code, and if I can I use the web ui like the good old days and not spend my CLI tokens.

This is a new form of prayer for those who can't break their religious addiction to LLM code generators.

You are cooked if you can’t actually write better code than llm. Try reading some books or documentation

Nice workflow! I'll give it a try. I'm struggling with building mental model of AI-generated code. And code review fatigue is real. This may be the way.

If you copy/paste code from a teaching book, you will probably not learn as well as if you type it.

Typing itself is irrelevant, it is the timing spent, even if only seconds, pondering at what each word or syntactic element is and why use it.

Being slower does not automatically make you learn better, focus on the learning is what makes the difference.

If you don't have the opportunity to learn, the time to actually think, then a faster tool is not helping.

TL;DR: what matters is why you are doing something, is it solely to get the task done or is it primary to learn, or both?

But this way you move way slowly even on personal projects, like you will not even get the basic UI for the app done in a few days? Is that OK for you?

This method doesn't seem bad.

Realistically, LLMs write code much better than most people. In my domain, there are areas where I still write better code than an LLM, especially when it comes to physical constraints it might not understand, but there are far more domains where the LLM writes much better code than I do. In that sense, writing code with an LLM and keeping track of it feels more helpful than I expected.

Practicing solo coding for an hour a day often ends up being mechanical and not very useful. This might actually be more helpful.

In my current workflow, I've settled into a three tier system when coding:

1. HIGH-VALUE CODE:

I write it all myself. I will occasionally use AI for mostly mechanical changes, like cleaning up variable names or mass-changes when a function signature has changed. Either way, every line is read carefully. Sometimes this means isolating my high-value code as a library in a separate repo. Usually it's just a note in AGENTS.md, or even a well-written comment at the top of certain files. I'm not obsessive about it, though, as it can't hide from git. And learning what it's trying to change is sometimes a useful insight.

That doesn't stop me from using AI as a consultant. This is the one time I'll use a beast like Fable. Ask it to write a technical/security analysis on a section of code and damn it can pull out some impressive insights. It can't write new code particularly well, but it can inspect code like a boss. But that all stays in the chat window. (And despite being so infrequent, they ends up costing significantly more than all my other AI costs combined!)

2. BOILERPLATE/PROCEDURAL CODE:

I'll write the first draft, but once I've set the tone, I'll allow AI to build and maintain it. I keep on top of things like a senior manager, just to make sure it's not doing stupid things. Every few days I tell it to mow its own grass: AI is good at recognising its own stupidity, you just need to give it an opportunity to look.

3. TEST/HARNESS CODE:

Bring on the slop. If I get nothing else from the AI revolution, it's not having to write another stupid test unit. Nothing makes me happier than setting the AI to work writing every permutation of test I can think of. I will slop this code all day, and I won't read a single line of it. Why should I? If I ever doubt whether a particular test is correct, I'll test the test by breaking the code, not by reading the test. But I almost never catch it out. In my experience, AI is especially good at writing tests. Perhaps more than anything else.

Tests don't just take the form of a few mocks and props in a test harness. In one recent case, my project involved writing a library for the API of an obscure commercial microcontroller-powered device. I took the API documentation and made AI build me a complete simulator. I then made it write a full suite of tests using my client library within the test code. I then got it to run that test suite against real hardware and identify any inconsistencies. From there it could recursively modify the simulator until it became unreasonably good at mimicking the real hardware. I haven't read a single line of its code. But it's now core to the library's CI.