Backproto
network backpressure routing applied to AI agent payments
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I’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
HN · launched Mar 18, 2026 · 5 upvotes (top 89%) · 0 views
Niche: multi-agent frameworks and protocols · 299 launches, 11 in the last 7 days ▼ -31% · Explore this niche →
Category and tags
- Fintech
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
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More like this: all 299 launches in multi-agent frameworks and protocols →
Could you build this?
No Adapting the Tassiulas-Ephremides backpressure routing algorithm to real-time streaming payments requires deep expertise in stochastic network optimization, queueing theory, and payment channel distributed protocols.
What it would actually take: Building this requires a distributed systems architecture managing state-channel streaming payment topologies (e.g., Lightning or Interledger). The core challenge is implementing dynamic queue-weight calculations, congestion control feedback loops, and loop-free payment routing without risking locked liquidity or state desynchronization, demanding specialized research in network optimization and crypto-economic protocols.
Discussion
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Competitors
Other products that read as similar to this one : 174 launches clear the similarity bar, closest 8 shown.
Attention rank: #170 of 175 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 140 days after the earliest competitor.
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