Recent content by harryfuture74

A practical understanding of Research Agents starts with knowing what the system does well, where it is unreliable, and how to validate the result. 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...

I wanted to start a broader productivity ideas thread around Python. A useful angle is limitations, but it also connects with common mistakes. Different tools and workflows can produce very different results even when the goal is similar. It would be interesting to compare practical examples...