Backproto
network backpressure routing applied to AI agent payments
Details
- External ID
- 47424932
- Source
- HN
- Company
- —
- Product
- Backproto
- Website domain
- backproto.io
- Launched
- March 18, 2026
- Cohort
- —
- Upvotes
- 5
- Upvotes percentile
- 0.1070110701107011
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
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
Enrichment
- Theme
- payments, billing, and wallet infrastructure
- Vertical
- Horizontal
- Function
- Model & infra
- Audience
- Developer
- AI stance
- AI feature
- Project type
- Hobby / open-source project
- Normalized one-liner
- backpressure routing for ai agent payments
- Manually corrected
- False
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
No comments on this launch.
Competitors
Other products that read as similar to this one — 63 launches clear the similarity bar, closest 8 shown.
Attention rank: #61 of 64 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 138 days after the earliest competitor.
- Routing24 · hn · 2026-07-04 · 8 upvotes · similarity 0.43
- AgentRaaS · ph · 2026-09-08 · 1 upvotes · similarity 0.42
- Rayline routes Claude Code subagents to on-device and cheaper models · hn · 2026-06-08 · 11 upvotes · similarity 0.40
- Sequence Agentic · ph · 2026-07-01 · 245 upvotes · similarity 0.37
- AgentBudget · hn · 2026-02-24 · 7 upvotes · similarity 0.37
- Keyban Agent Wallet · ph · 2026-09-23 · 4 upvotes · similarity 0.37
- I built a tool showing how AI providers (should) throttle their models · hn · 2026-08-28 · 6 upvotes · similarity 0.37
- Ably AI Transport · hn · 2026-01-21 · 7 upvotes · similarity 0.37
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a model & infra tool for Fintech yet.