Our open-source meta-agent framework research was grounded in the premise that there should be an intuitive structure out there in the open, general and flexible enough for a wide variety of use cases, and transparent enough to let creators and users debug and understand the flow very well. ROMA is built on hierarchical recursive decomposition, which lets one prescribed topology be reused across many use cases and removes the need for anyone to rebuild the scaffolding around the agents from nothing. "At a very high level, information in ROMA flows top down through decomposition, bottom up through aggregation, and left to right through conditional dependencies between sibling subtasks. You start off with this root node, which is the original task, and it goes through top-down decomposition. It passes through the atomizer, whose job is to decide whether the task is simple enough for a normal LLM to execute, or complex enough that it needs to be broken down and planned out. If it's atomic, it goes straight to an executor. If it's not, the planner generates different subtasks, and these subtasks should ideally work towards achieving the final goal. Some of them are conditioned on the ones before them, so they can't really run until those finish, and the ones that aren't can all run in parallel. Then once the subtasks are completed, you have bottom-up aggregation, where the parent node looks at all the results of these nodes and tries to resolve its original task using those results. And this is the same logic for every node, which is what makes the whole thing recursive." ROMA dictates a standard topology for many use cases, and we're claiming this topology is interpretable, composable, and very easy to iterate on top of. We're taking the structural guesswork out of building these systems, which opens doors for enthusiasts, explorers, and builders, because they can vibe-prompt their way into whatever specific application they want without worrying about structure or setting things up. All they have to worry about is how the aggregator aggregates information or how the planner plans, and these are essentially just agents with particular prompts. Given the reduced barriers to entry, they can contribute, explore different use cases, and experiment with many different tools and mix them together. Anyone can plug in a code interpreter, a bug finder, a video generator, an image generator, a comic book generator, or whatever they find useful.