Hanuman

AstroMesh is a multi-agent simulation and autonomous constellation management platform designed to handle Low Earth Orbit (LEO) congestion using Crusoe Managed Inference. Core Architectural Pillars Track 1: Done Means Done: Natural-language goals are converted into machine-enforced Invariant Contracts. An independent Adversarial Verifier Agent stress-tests and audits every proposed trajectory against real-time simulation state before thruster actuation. Track 2: Shared Brain: A shared Orbital Memory Graph tracks active debris vectors and encounter history. Common prefix prompt structures hook directly into Crusoe's KV-cache infrastructure to eliminate prefill latency for newly spawned agents. Track 3: Version N+1: An automated Playbook Evaluator Agent conducts post-mortems after each epoch, sandbox-testing mutated policies (Version N+1) against synthetic holdout scenarios to ensure measurable, data-driven self-improvement. Tech Stack Inference: Crusoe Managed Inference (optimized for high throughput and low TTFT). Orchestration: Python asyncio, custom agent topology graphs, and Pydantic validation. Simulation: Real-time 3D orbital mechanics engine with live fleet telemetry dashboards.