Recent content by mountainlucy

A useful way to understand Deep Learning is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is future improvements. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can...

On Understanding Research Agents: learning curve and productivity, the part about research and agents 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. It is usually easier to troubleshoot when...

When working with AI Robots, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is performance. Define what a good result looks like before changing tools or settings, then test one variable at a time so you...