31–40 of 87 posts
[stub for offtopicness]
"Back pressure" is already a term widely used in computing for something entirely different: https://schmidscience.com/what-does-back-pressure-in-compute...
Y'all are sleeping on custom lint rules. Every time you find a runtime bug, ask the LLM if a static lint rule could be turned on to prevent it, or have it write a custom rule for you . Very few of us have time to deep dive into esoteric custom rule configuration, but now it's easy. Bonus: the error message for the custom rule can be very specific about how to fix the error. Including pointing to documentation that ex…
My mental model is that ai coding tools are machines that can take a set of constraints and turn them into a piece of code. The better you get at having it give its self those constraints accurately, the higher level task you can focus on. Eg compiler errors, unit tests, mcp, etc. Ive heard of these; but havent tried them yet. https://github.com/hmans/beans https://github.com/steveyegge/gastown Right now i spent a lo…
I've found https://github.com/obra/superpowers very helpful for breaking the work up into logical chunks a subagent can handle.
Backpressure != feedback (the more general term). And in the agentic world, we use the term 'context' to describe information used to help LLMs make decisions, where the context data is not part of the LLM's training data. Then, we have verifiable tasks (what he is really talking about), where RL is used in post-training in a harness environment to use feedback signals to learn about type systems, programming language syntax/semantics, etc.
I got turned off in the first paragraph with the misuse of the term "back pressure". "back pressure" is a term from data engineering to specifically indicate a feedback signal that indicates a service is overloaded and that clients should adapt their behavior. Backpressure != feedback (the more general term). And in the agentic world, we use the term 'context' to describe information used to help LLMs make decisions,…
My mental model is that ai coding tools are machines that can take a set of constraints and turn them into a piece of code. The better you get at having it give its self those constraints accurately, the higher level task you can focus on. Eg compiler errors, unit tests, mcp, etc. Ive heard of these; but havent tried them yet. https://github.com/hmans/beans https://github.com/steveyegge/gastown Right now i spent a lo…
> Right now i spent a lot of “back pressure” on fitting the scope of the task into something that will fit in one context window (ie the useful computation, not the raw token count). I suspect we will see a large breakthrough when someone finally figures out a good system for having the llm do this. I've found https://github.com/obra/superpowers very helpful for breaking the work up into logical chunks a subagent can…
I got turned off in the first paragraph with the misuse of the term "back pressure". "back pressure" is a term from data engineering to specifically indicate a feedback signal that indicates a service is overloaded and that clients should adapt their behavior. Backpressure != feedback (the more general term). And in the agentic world, we use the term 'context' to describe information used to help LLMs make decisions,…
I'm not trying to discount any attempt to correct people, especially when it gets confusing (like here, I was also confused honestly), but we could formulate it nicer IMHO.