Recent content by annathinker

A useful way to understand AI Workflows is to separate the goal, the input, the model or tool, and the way the output is evaluated. 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...

For AI E-Commerce knowledge guide: improving common mistakes, I would separate the problem into setup, output quality and repeatability. e-commerce and common fits into that because it can change the result quite a lot depending on the workflow. It is usually easier to troubleshoot when each...

For n8n, it helps to think in terms of inputs, constraints, verification, and iteration. 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 tell what actually improved the outcome. Another...