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0 pointstheo08331y ago0 comments

I use llms exactly and exclusively for the first two cases - just write comments like:

// map this object array to extract data, and use reduce to update the hasher

And let llms do the rest. I rarely find my self back to the browser - 80% of the time they spit out a completely acceptable solution, and for the rest 20% at least the function/method is correct. Saved me much time from context switching.

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skydhash1y ago

For me the quick refresh is better as I only need to do it once (until I don't use the language/library again) and that can be done without internet (local documentation) or high power consumption (if you were using local models). And with a good editor (or IDEs) all of these can be automated (snippets, bindings to the doc browser,...) and for me, it's a better flow state than waiting for a LLM to produce output.

P.S.I type fast. So as soon as I got a solution in my head, I can write it quickly and if I got a good REPL or Edit-Compile-Run setup, I can test just as fast. Writing the specs, then waiting for the LLM's code and then review it to check feel more like being a supervisor than a creator and that's not my kind of enjoyable moment.

theo0833OP1y ago

I agree with you, creating something just feels better than reviewing code from a LLM intern ;D

That's why I almost never use the 'chat' panel in those AI-powered extensions, for I have to wait for the output and that will slow me down/kick me out of the flow.

However, I still strongly recommend that you have a try at *LLM auto completion* from Copilot(GitHub) or Copilot++(Cursor). From my experience it works just like context aware, intelligent snippets and heck, it's super fast - the response time is 0.5 ~ 1s on average behind a corporate proxy, sometimes even fast enough to predict what I'm currently typing.

I personally think that's where the AI coding hype is going to bear fruit - faster, smarter, context+documentation aware small snippets completion to eliminate the need for doc lookups. Multi file editing or full autonomous agent coding is too hyped.