Autonomous agents: execution is the hard part
Why the difficulty in autonomous AI agents is not reasoning quality but execution, recovery and bounded authority.
Reasoning quality is no longer the bottleneck for autonomous agents. Execution is. An agent that plans well and recovers badly is worse than no agent.
Every autonomous system built here — including the Linux operator agent and the Autonomous Trading Agent — enforces bounded authority: the agent may act, but only inside limits it cannot rewrite.
Recovery matters more than success rate. An agent that fails safely and reports precisely is deployable; one that succeeds 95% of the time and fails silently is not.
Where this shows up
- EPN Labs
An independent research laboratory for ideas that are too early to be startups.
- Autonomous Trading Agent
A research-first trading system, currently in hibernation while strategies evolve.