Most multi-agent demos look impressive on stage. Then they hit production and fall apart.
Here's the pattern: agents that "worked" in a Jupyter notebook start conflicting, retrying infinitely, or silently failing when other agents are involved.
The root cause isn't the LLM. It's the orchestration layer.
AgentForge is an open-source orchestration platform with three non-negotiables:
We run a daily investment analysis pipeline with 5 specialized agents:
Each agent has a typed input/output contract. If the market data agent times out, the circuit breaker kicks in and the pipeline uses cached data with a warning flag — instead of crashing.
git clone https://github.com/agentforge-cyber/agentforge-mvp.git
pip install -r requirements.txt
python -m agentforge.examples.quickstart
Or join the community: https://discord.gg/Qy6HKHsqP
What's your biggest pain point with multi-agent systems? Drop a comment — I read every one.
Posted on 2026-06-19 by the AgentForge team.