People keep saying this and I agree Claude has gotten a lot better even in my own experience, but I think the value is questionable.

What’s the point of adding features that are inscrutable? I have gotten Claude to make a feature and it mostly works and if it doesn’t work quite right I spend a massive amount of time trying to understand what is going on. For things that don’t matter too much, like prototyping, I think it’s great to just be able to get a working demo out faster, but it’s kind of terrifying when people start doing this for production stuff. Especially if their domain knowledge is limited. I can personally attest to seeing multiple insane things that are clearly vibe coded by people who don’t understand things. In one case, I saw API keys exposed because they were treating database users as regular user accounts for website login auth.

> I move much, much faster than before

This is a bad metric as has been attested multiple times in unrelated situations. Moving faster is not necessarily productivity nor is it value.

I find LLMs useful in regurgitating one-liners that I can’t be bothered to remember or things where even being flat out wrong is okay and you just do it yourself.

For all the folks spending a lot of time and energy in setting up MCP servers, AGENTS.md, etc. I think this represents more that the LLM cannot do what it is being sold as by AI boosters and needs extreme amounts of guidance to reach a desired goal, if it even can. This is not an argument that the tech has no value. It clearly can be useful in certain situations, but this is not what OpenAI/Anthropic/Perplexity are selling and I don’t think the actual use cases have a sustainable business model.

People who spend the energy to tailor the LLMs to their specific workflows and get it to be successful, amazing. Does this scale? What’s going to happen if you don’t have massive amounts of money subsidizing the training and infrastructure? What’s the actual value proposition without all this money propping it up?