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I use LLMs for 80%+ of our code, but of course it is always human reviewed and tested. We use all types: llama, gpt, claude, gemini, replit, grok and others: we

I use LLMs for 80%+ of our code, but of course it is always human reviewed and tested. We use all types: llama, gpt, claude, gemini, replit, grok and others: we want to know which is the most productive (it's by a large margin sonnet 3.5 for what we do; gemini is terrible so far). We are fine with code generated to be executed immediately (has to be to be productive really), but once we are satisfied, we won't let the PR get get approved without reviews.

shekkizh 2y ago
This resonates with me too. However, as LLMs increasingly shift towards more "agentic" capabilities—where they're not just generating code but also executing it and performing actions beyond just text generation—I'm thinking: where do we draw the line? What should startups and developers working on such systems do to be trusting?