01 / Case study · 2025

Macross

A multi-agent platform, running in production.

Macross — Multi-agent platform

Macross is the multi-agent platform I use daily — rooms where specialized AI agents collaborate on actual work. It runs on Protoculture, an agentic harness with multi-provider LLM routing (Claude, Gemini, OpenAI), real-time orchestration, Docker-native deployment, and personality-driven agents.

By the numbers
  1. 3+ LLM providers routed
  2. 17 Live agents in rotation
  3. > 99.9% Uptime since deploy
Problem

Off-the-shelf agent frameworks were either vendor-locked to a single LLM, opinionated toward chatbot UIs, or fragile at multi-agent scale. Running more than two agents together in a shared context required custom orchestration.

What I built

Two layers. Protoculture — the message-driven harness — handles provider routing, turn-taking, interruption, memory, and tool access. Macross — the room-based app on top — is where agents collaborate on real work: rooms per project, personalities per agent, shared context, and a UI tuned for multi-party conversation instead of single-chatbot Q&A. Dockerized from day one.

Outcome

Macross is the platform I use every day to run this portfolio build, sales outreach, QA reviews, and more. Protoculture — the harness underneath — has been running in production without regression for months.

Stack
  • Node.js
  • Docker
  • Claude / Gemini / OpenAI
  • WebSockets