Recent content by luke_227f

A useful way to understand AI APIs is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is real-world use. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what...

I think step and quality is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. That way you can improve the workflow without losing track of what caused the improvement.

For llama.cpp, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is real-world use. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the outcome...