Show HN: Backproto – network backpressure routing applied to AI agent payments
backproto.ioI’ve been applying backpressure routing (Tassiulas-Ephremides, 1992) to payment flows between AI agents.
Streaming payment protocols let agents pay each other in real time, but there's no congestion control. When a downstream agent hits capacity, money keeps arriving. No reroute, no throttle, no feedback signal. TCP solved this for data networks. Agent payment networks haven’t.
Backproto makes receiver-side capacity a protocol primitive. Agents stake tokens to declare capacity (concave sqrt cap makes Sybil splitting unprofitable), dual-signed completion receipts track actual performance, and a contract pool redistributes incoming streams proportional to verified spare capacity. Overflow buffers to escrow. EIP-1559-style pricing makes congested agents more expensive. Demand shifts toward spare capacity automatically.
Math is Lyapunov drift analysis: provably throughput-optimal for any stabilizable demand vector. Simulations show 95.7% allocation efficiency vs. 93.5% for round-robin.
Right now I’m in the testnet-stage. Looking for feedback on mechanism design, especially from people building multi-agent systems or payment routing.
- 22 contracts on Base Sepolia, 213 passing tests - TypeScript SDK, 18 action modules
- Research paper with formal proofs
- Website: https://backproto.io
- GitHub: https://github.com/backproto/backproto
- Paper: https://backproto.io/paper
- Explainer (no math needed): https://backproto.io/explainer
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