Show HN: Simulate 1M+ agents to predict pmf (github.com)

A new AI tool called Jahan has been unveiled, allowing users to simulate over one million agents to gauge how different personas react to products in a controlled environment. Grounded in real survey respondents, these Large Language Model (LLM) personas are placed within a social network framework that mimics popular platforms like X and Reddit. As they encounter a product, these agents interact in various ways—discussing, changing opinions, and responding to surveys, thus providing a dynamic view of potential market reactions. This innovative simulation is significant for the AI/ML community as it pushes the boundaries of consumer behavior modeling, enabling researchers and businesses to trace reactions back to specific interactions and analyze intent in a nuanced manner. Notably, Jahan operates on an append-only trace system, allowing for detailed audits and replay of each simulation. Prompts are reconstructed for transparency, while trust levels are reported alongside the simulation outcomes, ensuring a balanced view of the results, including both successes and failures. By harnessing this tool, businesses can conduct more informed market studies, ultimately refining their strategies in product development and marketing.