Recent content by amber3679

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

The point about apps and limitations is interesting. In practice I would keep the first test simple, record what worked, and only add extra complexity if it solves a specific limitation. It also gives you a cleaner baseline if you want to compare tools or settings later.

For AI Analytics & Growth, 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...