π Beyond RAG: Simulating the Future with MiroFish
Lately, most of us have been working with RAG systems retrieving context, grounding responses, improving accuracy. But what if instead of just retrieving knowledge, we could simulate outcomes? I re...

Source: DEV Community
Lately, most of us have been working with RAG systems retrieving context, grounding responses, improving accuracy. But what if instead of just retrieving knowledge, we could simulate outcomes? I recently came across MiroFish, and decided to test it out. π§ͺ What I Tried I cloned the repo, ran it locally, and fed it a simple scenario: βWhat happens when an AI assistant is introduced into a companyβs daily workflow?β Instead of a static answer, it generated a multi-agent simulation over time. π§ What Makes It Different Unlike traditional systems, MiroFish: Creates a virtual environment Generates multiple agents (employees, managers, etc.) Simulates interactions over time Produces a temporal report (day-by-day evolution) This means youβre not just asking: βWhat will happen?β Youβre observing: βHow things evolve step by step.β π Sample Insights from My Test From a 14-day simulation, I observed: π Initial boost in productivity βοΈ Diverging employee satisfaction π Emerging dependency on AI