LLMS are basically just like higher level programming tools - knowing how to utilize them is the key. Best practice is not to depend on them for correctness, bu

LLMS are basically just like higher level programming tools - knowing how to utilize them is the key. Best practice is not to depend on them for correctness, but instead utilize them as automatic maps from data->action that you would otherwise have to write manually. For example, I wrote my own MCP server in Python that basically makes it easy to record web browser activities and replay them using playwright. When I have to look at logs or inspect metrics, I record the workflow, and import it as an MCP tool. Then I keep a prompt file where I record what the task was, tool name, description of the output, and what is the final answer given an output. So now, instead of doing the steps manually, I basically just ask Claude to do things. At some point, I am going to integrate real time voice recording and trigger on "Hey Claude" so I don't even have to type. The only thing I wish someone would do is basically make a much smaller model with limited training only on things related to computer science, so it can run at high resolution on a single Nvidia card with fast inference.