Thanks for that, it's the level I like to work too - what model/quant are you using? How much vram/context and which coder?
I'm using Qwen3.6 27B Q4, max context with pi on 32GB VRAM (although I'm testing out Glimmer on a feature implementation literally right now). Pi is great because it has minimal context added by the agent.
Looking forward to the 3.8 27B release to compare.
Pi and a similar set of tools is also likely similar to the harness these models are trained on. More complex harnesses burn reasoning tokens on these small models and in my benchmarking don't seem to be able to beat Pi ever. Usually it isn't close on some tests.