

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.



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.