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0 pointsepolanski6d ago0 comments

Got few questions:

- the project essentially spans almost 3 different (albeit minor) generations of LLMs. Have you noticed major differences in their personas, behavior, output for that specific use case?

- when using AI for feedback, have you ever considered giving it different "personalities"? I have few skills that role play as very different reviewers with their own different (by design conflicting) personalities. I found this to improve the output, but also to be extremely tiring and to often have high noise ratio.

- when did you, if ever, felt that AI was slowing you down massively compared to just doing it yourself (e.g. some specific bug or performance or design fix)? Are there recurring patterns?

- conversely, how often did AI had moments where it genuinely gave you feedback or ideas that would've not come to you?

- last: do you have specific prompts, skills, setups, etc to work on specific repositories?

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antirez6d ago

1. The huge jump from from Opus to GPT 5.3. Game changer. GPT 5.4, 5.5, were better but only incrementally better.

2. Nope I don't give much personalities, but I use subtle prompt differences to maximize certain responses I want, to make the model focusing in a given detail or acting in a specific kind of engineering mindset.

3. It never happened that the AI was slowing me down since I always had the full context and code detail in mind of what was happening. I believe that this happens more when you don't have a clear idea. Also GPT >= 5.3/4 is not the past generation of models, it is very hard to trap it into a situation where it seems unable to understand what you mean.

4. A few times the AI provided fresh insights that I really liked. Most of the times it was the other way around. Certain implementations were written by the AI at a very impressive level of quality.

5. I don't use general skills, I build skills with deep search when needed for specific projects, and build an AGENT.md that works as a knowledge base as I work with the AI. One thing that I use a lot is, when there is a very complex problem, to tell GPT that I have a friend called Machiavelli that is an incredible computer scientist. To write him an email in /tmp/letter.md with the problem we are facing, and I'll try to get a reply. Then I ask GPT 5.5 Pro on the web with extensive reasoning set on. It will take sometimes 30 minutes or more to reply. Often times after I feed back the reply, the agent will be able to see things a lot more clearly.

porridgeraisin3d ago

Ha. I use the letter thing as well. I make it address it to a Mr. Chad G Petey. Only I maintain it for posterity in project/letters and project/letters/responses.

epolanskiOP5d ago

Thanks a lot for the insights. I like the Machiavelli thing.

> Then I ask GPT 5.5 Pro on the web with extensive reasoning set on. It will take sometimes 30 minutes or more to reply.

Any reason why Codex can't do that?

antirez5d ago

If Pro is the same model (hard to tell, I'm not sure) it has a token budget to think (test time scaling) which is huge compared to the Codex endpoint.

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