The core idea of the RLM paper is to make a regular LLM act more like a coding agent - offload context to something external that needs to be explicitly queried instead of filling up valuable context. The "recursion" part of the paper really only wins because they use a top-tier model for the root agent, and cheaper models for the sub-agents.

Prime Agent took the RLM idea (which is really just an academic view on how coding agents have always worked) and then added this "continual harness" idea. This part isn't super well described in the blog post, but includes some message passing between the agents, and the ability to share code.

Overall I chalk it up as neat, but not revolutionary. Another version of what most of these systems are already doing.