Yeah that was an interesting discovery in a development meeting. Many people were chasing after the next best model and everything, though for me, Sonnet 4.6 solves many topics in 1-2 rounds. I mainly need some focus on context, instructions and keeping tasks well-bounded. Keeping the task narrow also simplifies review and staying in control, since I usually get smaller diffs back I can understand quickly and manage or modify later.
I'll look at the new models, but increasing the token consumptions by a factor of 7 on copilot, and then running into all of these budget management topics people talk about? That seems to introduce even more flow-breakers into my workflow, and I don't think it'll be 7 times better. Maybe in some planning and architectural topics where I used Opus 4.6 before.
I wonder if there are different use cases. You sound like you’re using an LLM in a similar way to me. I think about the problem and solution, describe what I need implemented, provide references in the context (“the endpoint should be structured like this one…”) and then evaluate the output.
It sounds like other folks are more throwing an LLM at the problem to see what it comes up with. More akin to how I delegate a problem to one of my human engineers/architects. I understand, conceptually, why they might be doing that but I know that I stopped trying that because it didn’t produce quality. I wonder if the newer models are better at handling that ambiguity better.
I'll look at the new models, but increasing the token consumptions by a factor of 7 on copilot, and then running into all of these budget management topics people talk about? That seems to introduce even more flow-breakers into my workflow, and I don't think it'll be 7 times better. Maybe in some planning and architectural topics where I used Opus 4.6 before.