2 hours ago · 15 min read2975 words · Tech · hide · 0 comments

I’ve talked a bit about large language models (LLMs), and I do have friends who’ve been at odds with me for my reluctance to call these predictive algorithms “artificial intelligent”. Still, I do use LLMs frequently for coding both professionally and on my own projects. For things I care about, I often use them as a scalpel, either using chatbot output to implement my own design or heavily refactoring generated code to be maintainable. I’ve limited pure prompt-based development, or vibe coding, for simple one-time use tasks or throwaway scripts. Recently, I’ve started using LLMs for workflow projects using only lists of text specifications. In a radical departure from my normal engineering flow, I’ve let agents just write software without individually verifying the code. I do often get usable tools, although they often need a considerable number of refining steps. However, looking under the surface reveals confirmations of many of my apprehensions about heavy dependence on these tools…

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