[hn_throwaway_99]

I don't really disagree with anything in this post, but the advice is so basic it could have easily been written by an LLM, and apologies for my jadedness but I've seen like a million other posts with the same advice. The advice is simply:

1. Write detailed prompts.

2. Don't trust generated code output - it must be thoroughly reviewed, and feedback should be given back to the LLM.

3. AIs are very helpful for those learning new architectural patterns.

4. Try different tools.

If you really want to learn about using AI to write code (including the pros and cons), I think this post, https://news.ycombinator.com/item?id=44159166, is excellent. Note the author of the Cloudflare OAuth component, kentonv, makes a lot of good, insightful comments in that thread IMO.

[rfitz]

No need to apologize for the jadedness at all! I think we're in an era of AI fatigue where every piece of content you see feels like it's AI generated (or assisted). Arguably most points in this post can be looked at as common sense to some degree. I think what I was trying to get across was my mental models and view on AI in tech since I still see a shocking amount of devs who look at it simply as a means to generate code for them and nothing more.

I'm planning on writing more that dives a bit deeper into experimentation I've done as far as tooling, MCP servers, etc that may be a bit more intriguing to those who have already dove into the AI side of things.