nhorozov.xyz/thoughts/agent coding thinking bottleneck

agent coding thinking bottleneck

i like agentic coding because it moves the bottleneck when coding to how well i can think about it. this is exactly where the bottlenck should be. i can think for a few hours and then give glm5.3 flash or qwen3.8-27b a complex and detailed task, and then i can think about something else. ive done this with a lot of things. my site is a lot easier to write to because i had my agent make a cli that lets me type markdown into nvim and then rsyncs it over to the site, along with running a pile of sed commands i can imagine would should be doing but dont know how to write them (to update other pages to link to the new post/thought).

the other day i spent a while thinking about a method i saw at a conference (which was super fun to attend) and when i typed my long prompt into my agent to run a few experiments for it, i could think about other things.

in case you are interested here are the prompts

Read and deeply understand the poster in this directory. More context: https://nhorozov.xyz/blog/nemi26.md. I want to apply this method to a series of simple models and use numpy.linalg.matrix_rank to see how the rank of the matricies in these models changes, as they are trained from scratch at their tasks, and then as the Hessian null space continuation method is applied. Gain a lot of comprehensive context about this project, reason deeply, and get back to me when you are ready to start.

This is good, for point 2 add the transformer from (https://www.alignmentforum.org/posts/N6WM6hs7RQMKDhYjB/a-mechanistic-interpretability-analysis-of-grokking) to the list of the three models that will be trained from scratch and then phase b, with both unsteered and CKA-steered applied to all of them. Start, and if you have questions about something or have unresovable issues with hardware stop working and ask me to help.

I added my blog post to the agent’s context because I explain more of the method there.

this was written sept 6 2026 at 10am