Recent content by ninja_arthur

For Perplexity, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is deployment. 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. Another...

On A practical overview of Mistral Models for getting started, the part about mistral and models stands out to me. I would test one small workflow first, keep the variables consistent, and compare the result before changing several things at once. If you share the exact setup, it would be easier...

A practical understanding of Mistral AI starts with knowing what the system does well, where it is unreliable, and how to validate the result. One important area is collaboration. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can...