🦈 Before that press release goes live, why not test it against "hundreds of public voices" first? A slightly futuristic engine now simulates an entire crowd's reaction for $1 in 10 minutes. Title: aaronjmars/MiroShark URL: 📦 Overview MiroShark is a "Universal Swarm Intelligence Engine." For any scenario—a press release, a news headline, a policy draft, or a question—it simulates in real time how hundreds of AI agents would react. The agents post, argue, trade, and shift their positions as simulated time passes. ❓ Challenges Solved Organizations want to test how the real public will receive an idea before committing resources. MiroShark removes the need for lengthy focus groups and expensive market research, enabling validation for under $1 in less than 10 minutes. 💡 How It Works It runs in five phases. ・Generate an ontology from the input documents ・Build a Neo4j knowledge graph of entity relationships ・Ground 100+ personas using demographics, web enrichment, and graph attributes ・Have agents interact hourly across Twitter, Reddit, and prediction markets ・Generate reports that cite the actual simulated posts and trades Posts are ingested via NER, embeddings, and entity resolution, then retrieved by fusing vector, BM25, and graph traversal. 🎯 Use Cases ・PR crisis testing and market-reaction forecasting ・Ad campaign pre-testing and policy impact analysis ・Personal decision scenarios and historical counterfactuals You can also inject breaking news mid-run, or fork a running simulation (counterfactual branching). 📊 Highlights ・1.3k GitHub stars and 265 forks, AGPL-3.0 licensed ・Each simulation runs at roughly $1, about 10 minutes, with 100+ agents ・Python backend, Vue.js frontend, Neo4j database; LLMs via OpenRouter (local Ollama also supported) #AIAgents# #Simulation#