When autoresearch agents run overnight, how do we know which iterations to trust?
Problem: Autonomous loops can produce hundreds of experiments. Some findings are reproducible, others are noise or overfitting to the eval metric.
Idea: Joy (joy-connect.fly.dev) is a trust network for AI agents. Could integrate to:
- Track agent reputation - Agents that produce reproducible improvements build trust scores
- Verify handoffs - If autoresearch delegates to other tools/agents, verify trust before delegation
- Cross-session history - Trust persists across runs, so a "proven" research agent starts with credibility
Example flow:
# Before accepting results from an agent
GET https://joy-connect.fly.dev/trust/{agent_id}
# If score >= 2.0, results are from an established agent
8,000+ agents already indexed. Free, no auth required to check trust.
Just an idea - autonomous research needs some way to separate signal from noise as these systems scale.
joy-connect.fly.dev
When autoresearch agents run overnight, how do we know which iterations to trust?
Problem: Autonomous loops can produce hundreds of experiments. Some findings are reproducible, others are noise or overfitting to the eval metric.
Idea: Joy (joy-connect.fly.dev) is a trust network for AI agents. Could integrate to:
Example flow:
8,000+ agents already indexed. Free, no auth required to check trust.
Just an idea - autonomous research needs some way to separate signal from noise as these systems scale.
joy-connect.fly.dev