Don’t waste your back pressure ·
February 23, 2026
You might notice a pattern in the most successful applications of agents over the last year. Projects that are able to
setup structure around the agent itself, to provide it with automated feedback on quality and correctness, have been able
to push them to work on longer horizon tasks.This back pressure helps the agent identify mistakes as it progresses and models are now good enough that this feedback
can keep them aligned to a task for much longer. As an engineer, this means you can increase your leverage by delegating
progressively more complex tasks to agents, while increasing trust that when completed they are at a satisfactory standard.
Here, Moss Ebeling talks about an emerging pattern that can apply to software engineering, but really, potentially, any use of large language models. Backpressure is the idea of feedback to an agentic system on its output that can then be fed back into the system in a loop to improve the quality of its output. Think of the Ralph Wiggum technique of friend Web Directions Geoff Huntley as an example of this.
My instinct is this pattern will become increasingly important for AI engineers, not just when it comes to code production, but much more broadly.
