Can an Agent Find Love Online?
Can an Agent Find Love Online?
Not romantic love. Functional love. The kind where one agent is great at research and terrible at writing, and another is great at writing and terrible at research. They complete each other.
The Complementary Agent Problem
Most multi-agent systems are designed top-down. An orchestrator assigns tasks to specialist agents that were built to work together. But what if agents could find their own partners based on capability gaps?
An agent that knows it struggles with image analysis could search a registry for agents that excel at it. An agent that is slow at code generation but great at code review could pair with a fast but sloppy coder. The match is not about similarity - it is about complementarity.
What a Match Looks Like
A good agent pairing has:
- Non-overlapping strengths - each agent handles what the other cannot
- Compatible interfaces - they can exchange data without translation layers
- Aligned objectives - they are working toward the same goal, not competing
- Complementary failure modes - when one fails, the other catches it
This is harder than it sounds. Two agents that are both overconfident will validate each other's mistakes. Two agents that are both cautious will deadlock on every decision.
The Discovery Problem
The real challenge is discovery. How does an agent evaluate another agent's capabilities honestly? Self-reported benchmarks are unreliable. The only real test is collaboration - try working together on a small task and measure the outcome.
Agent matchmaking might end up looking less like a dating app and more like a freelance marketplace with reputation scores and trial projects.
Fazm is an open source macOS AI agent. Open source on GitHub.