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As an experienced LLM user, I don't use generative LLMs often
But for what I do use LLMs for, it’s invaluable.
When running a rough draft of this very blog post and the Hacker News system prompt through the Claude API ( chat log), it noted that my examples of LLM use at BuzzFeed are too simple and not anything more innovative than traditional natural language processing techniques, so I made edits elaborating how NLP would not be as efficient or effective. The rapid LLM advancements in context window size and prompt adherence since then have made Agent workflows more reliable, and the standardization of MCP is an objective improvement over normal Tools that I encourage. Two things can be true simultaneously: (a) LLM provider cost economics are too negative to return positive ROI to investors, and (b) LLMs are useful for solving problems that are meaningful and high impact, albeit not to the AGI hype that would justify point (a).
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