Earlier quoted context omitted.
I feel like people who can't get AI to write production ready code are really bad at describing what they want done. The problem is that people want an LLM to one shot GTA6. When the average software developer prompts an LLM they expect 1) absolutely safe code 2) optimized/performant code 3) production ready code without even putting the requirements on credential/session handling. You need to prompt it like it's an…
Exactly this. Not sure what code other people who post here are writing but it cannot always and only be bleeding edge, fringe and incredible code. They don't seem to be able to get modern LLMs to produce decent/good code in Go or Rust, while I can prototype a new ESP32 which I've never seen fully in Rust and it can manage to solve even some edge cases which I can't find answers on dedicated forums.
1) the models people are using (default model in copilot vs. Opus 4.5 or Codex xhigh)
2) the tools people are using (ChatGPT vs. copilot vs. codex vs. Claude code)
3) when people tried these tools (e.g., December saw a substantial capability increase but some people only tried AI this one time last March)
4) how much effort people put into writing prompts (e.g., one vague sentence vs. a couple paragraphs of specific constraints and instructions)
Especially with all the hype, it makes sense to me why people have such different estimates for how useful AI actually is.