MiroShark - Universal Swarm Intelligence Engine for AI agents

MiroShark reads your seed closely and pulls the people, organizations, and claims it mentions into a knowledge graph. It then casts that graph as a few dozen distinct agents, each with its own beliefs, incentives, and posting style. Nobody starts as a blank slate; everyone has something at stake.

Each agent is built from the graph, never from thin air. It draws on five layers of context: its own attributes, its relationships, semantically similar entities, its neighbours in the graph, and, for public figures or thin sources, a live web-research call. You can anchor the whole cast to real-world demographics too. That is why a journalist argues like a journalist and a whale trades like a whale.

The agents post and argue on a simulated Twitter and Reddit, take positions on a Polymarket-style prediction market, and revise their views round by round as the story moves. When it settles you get a cited report: who said what, how belief drifted, and where the market landed.

Three worlds run at once every round - a simulated Twitter, a simulated Reddit, and a prediction market - and they are wired together: traders read the posts, and the social agents watch the prices. Each agent carries a belief state (a stance, a confidence, and a sense of who it trusts) and updates it as the story develops, so momentum and doubt spread the way they do in a real crowd.

Yes - a run is something you reach into, not a video you watch. Drop breaking news into the timeline with Director Mode and it lands on every agent’s next move. Fork the timeline on a counterfactual - “what if the CEO resigns in round 24?” - and the branch runs as a first-class sibling you can diff against the original. Or message any agent directly and it answers in character, from its own beliefs and posting history.

A cited write-up produced by a report agent that reads the real feed and market before it writes, so every claim points back to an actual post or trade, nothing invented after the fact. Around it sit the analytics: a belief-trajectory chart, an agent-to-agent interaction network, a demographic breakdown, and a quality score for the run itself.