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I'm in the same boat, I still find the model to make mistakes or solve things in a less than ideal way - maybe the future is to just not care - but for now I wa

I'm in the same boat, I still find the model to make mistakes or solve things in a less than ideal way - maybe the future is to just not care - but for now I want to maintain the level of quality that the codebase currently has. I think it's good to keep up with what early adopters are doing, but I'm not too fussed about missing something. The plugins is a good example: A few weeks ago there was a post on HN where someone said they are using 18 or 25 or whatever plugins and it's the future, now this person says they are using none. I'm still waiting for the dust to settle, I'm not in a rush.

CuriouslyC 1y ago
The person using 25 plugins is giving bad advice. The agent isn't going to need all those tools at once, and each tool burns context and causes tool confusion. Enable MCPs for the specific task you're going to have your agent do. The trick is to create deterministic hurdles the LLM has to jump over. Tests, linting, benchmarks, etc. You can even do this with diff size to enforce simpler code, tell an agent to develop a feature and keep the character count of the diff below some threshold, and it'll iterate on pruning the solution.