Recent content by runner_lily

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

One thing worth trying with Google Gemini knowledge guide: improving best workflow is a controlled comparison around google and gemini. Use the same input for each test and note what changes in the output rather than judging from a single run. The original point — "A useful way to understand...

For AI Freelancing, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is customisation. 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...