"It was a matter of arriving on location and seeing the sun go down to get into position to wait for the sky to darken."
Last May, I wrote a blog post titled As an Experienced LLM User, I Actually Don’t Use Generative LLMs Often as a contrasting response to the hype around the rising popularity of agentic coding. In that post, I noted that while LLMs are most definitely not useless and they can answer simple coding questions faster than it would take for me to write it myself with sufficient accuracy, agents are a tougher sell: they are unpredictable, expensive, and the hype around it was wildly disproportionate given the results I had seen in personal usage. However, I concluded that I was open to agents if LLMs improved enough such that all my concerns were addressed and agents were more dependable.
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These exist in confusables.txt because they map to the same abstract character under NFKC decomposition. The map is semantically correct. But from a visual perspective, these are false positives: a human would never confuse Mathematical Fraktur l with plain l.
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