Comment by tstrimple

Any time the LLM can establish a tight feedback loop it can iterate effectively enough to make good progress. But if for one reason or another that feedback loop is long, the more guidance and direction they seem to need. If they cannot correct their course based on feedback from their own output they need an outside observer to push them towards different paths. CRUD stuff is the obvious easy answer. It represents some absurd amount of software development work and is drastically overrepresented in training data. For good and bad. Lately I've been working on a diffusion model for terrain generation. The goal is to be able to recreate realistic terrain based on water flow and erosion on top of plate tectonics for much longer geological time terrain adjustments. These are much longer feedback loops. Sometimes it'll spend 6+ hours training a diffusion model on my 5090 just for the quality to degrade compared to the last experiment. So letting the model go wild trying different approaches and evaluating the results doesn't work nearly as well as when it can iterate 1000 times in those 6 hours while checking its own answers.