[canpan]

One big pain point is not seeing the thinking trace. I noticed using pi with a self hosted model that I could spot, stop and correct my prompt much faster. With claude etc I have to first wait for it to think 3 minutes and then notice it got completely off the path I wanted.

I still use a plan, because my local model is not as smart as opus, but I can iterate much faster.

[WilcoKruijer]

I’ve seen people have success figuring out model reasoning by adding a required `reasoning` parameter to tool calls. Might be worth experimenting with this for the `write` tool call in a coding agent harness.

[embedding-shape]

Also "divide and conquer" is still applicable. Tired of waiting 10 minutes for the model to come up with a plan that ends up being wrong? Divide the problem into pieces and attack the pieces individually, worst case scenario the model spends 2 minutes and got some detail wrong, but way easier to correct the tiny stuff.

Once you've done with the pieces, do one "integrate them together" part, then you have a fully formed plan with less chance of wrong stuff in it. Yes, this requires a bit more interactivity than "prompt model then come back after making and drinking a coffee", but personally I prefer that.

[carterschonwald]

this so true. its really hard to make sure a model isnt going off the rails if i dont see full cot. the fact that oai and anthropic models hide it now has made them less reliable. which is a shame

[trollbridge]

The great news is you can use DS-V-Pro, MiMo-V2.5-Pro, GLM-5.2, or K3 and see everything.

I tend to use 5.6-Sol now more for one shot type of tasks where all I want is the answer and I’m not going to read the reasoning.

[carterschonwald]

5.6 sol is pretty good, its definitely very very well tuned, i'm not quite sure which of the others i should use near term, but theyre doing great work