> Micromanaging the model doesn't seem like a great idea when doing real professional work with professional goals/deadlines/pressures.
replyRemember that it's not only the cost per token, but also speed. Some tasks are done faster with simpler/less-thinking models, so it might actually make sense to micromanage the model when you have deadlines.
If you're using the models to generate 99%-100% of the code, then it doesn't make sense to plug yourself into the loop as a bottleneck.
replyIt’s deeply ironic that the folks who want to outsource as much thought to the model as possible are saying that my stance - use your brain to decide the right tool for the job - is tantamount to “vibes”.
replyYou are being deeply reductive and that's against the spirit of hacker news. The issue is that models are difficult to objectively benchmark. The benchmarks don't always align with real world performance. It's not easy and clear cut to determine which model will work best in a given situation. It boils down to loose experiences/anecdotes. Do you have an objective criteria for model selection that you have tested to be effective with reproducible tests?
reply