I've been building this "general problem solver" (will likely focus on math problems first) that uses a special kind of orchestrator to direct/structure the problem solving approach in accordance with how many 'rounds' remain and other aspects of problem context. It does this largely by influencing the behavior of specialists.

Just posted a first early demo and sample orchestrator system prompt yesterday: https://x.com/Westoncb/status/2053429329233895857

You initialize the system with an objective and a number of rounds to run for, and it loads the current config (orchestrator + specialist prompts and LLM configs) and begins working on it. You can manually step one round at a time or just let it run.

Rather than accumulating a single long work log/context, at each round specialists apply patches to a number of named 'artifacts' with different roles (e.g. uncertainties, dead ends, findings), which are injected into prompts during subsequent rounds.

The engine is written in rust and there's a web UI (and CLI). You can use the built in config editor to define specialists (and their prompts), what the artifact set is, orchestrator prompting etc.