There is a big gap between model capability and auto mode could be a big win if that mode were utilized to use the best thinking model to supervise the less capable auto mode ChatGPT or even ollama local models.
Whenever I see the auto model chat stream going in a direction where the model is about to do something stupid or against the rules I just provided I have to quickly stop the auto model and switch to a capable model - if I can read fast enough! Imagine if the chat stream were going at two times the speed, it would be impossible for me to intervene.
Ideally, there would be a supervisor model that was Strategy model ($$$), a Boundary model ($$) a worker auto model ($) that did the work. The Strategy model would take written (pinned requirements) documents and formulate next steps that are optimized to stay within requirement but plan next steps (these are currently the task list). Then the Boundary model would be set up to keep the worker auto in line and restrict it from going off the road.
The pinned requirements (doc’s) is a necessary step in this execution optimization. Without it, context is quickly lost.
