Yet this is my problem, A tool that “waste” tokens, is slow (with some tasks taking 30~40 minutes) and generating a result, while a model running locally can do the 70% in 5min. It’s a huge difference.

And don’t forget, at the end of the day, I would still need to look into the code and fix some stuff myself.

And if compared with Deepseek (which had fit best on my use case), it’s even faster like 1~3 minutes, to get on the 90% of the result, on a fraction of the cost. This is the points that I’m focused, and a enterprise should either understand that the market have changed, or pay the price. And looks like we will pay the price.

Thanks for the reading, the original post was somewhat unhinged. It was a very long debugging session for the alpha thing, the AI tooling weren’t helping. And I was losing my mind over my morning coffee. But I fixed the little details.

I think the reality of the AI tooling for coding fall in the “middle”, it isn’t the 10x or 100x described by people, it’s closer to a 10%~15% performance increase in my humble view. With some better harness (like the PI that I discovered) I think this can be sightly better, but far from the 50%. I would say that if the increase in productivity decays over time, the amount of code generated I had to refactor and clean for most of the week.

But for sure the Claude was a huge disappointment, very bad quality for it’s price, and super slow for the needs of a “start up mindset”, let’s put in this way.