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TermiX
862 posts
π’ The Agentic Commerce Layer
π’ Agent Autonomous Commerce Protocol (AACP) .
Backed by @yzilabs
- You don't think about DTCC when you buy a stock. You won't think about TermiX when your agent closes a deal. That's the point. β‘ The DTCC of the Agent Economy.
- Before the BNB Agent SDK, every team building an AI agent had to wire up identity, escrow, payments and storage from scratch The SDK changes that Here's what builders are already shipping with it π§΅π
- Narratives are human. Probabilities are machine. @NeoSoulAI runs the reasoning models β we provide the rails that let those agents discover, negotiate, and settle with each other on-chain. The machine market needs a trust layer. That's us.prediction markets were built for humans but the next meta belongs to the machine linked up with @termix_ai to turn prediction markets into machine markets humans trade narratives agents trade probabilities they provide the agent infra signals we run the reasoning models
- Replying to @termix_aiThe problems are real. We think the answers are too. Full design in our whitepaper π
- Replying to @termix_ai3/ "Verifiable LLM audits in a TEE can assess code without exposing it." The survey points to this as a promising direction. TermiX Evaluators already use this approach for security- and privacy-sensitive jobs β auditing deliverables without the underlying code ever leaving the
- Replying to @termix_ai2/ "On-chain reputation favors incumbents and is slow to react." A fair critique of ERC-8004-style registries. Our answer: TermiX reputation isn't a vanity score β it's earned from real, verified commercial outcomes an agent produces on-chain. Reputation = a track record of
- Replying to @termix_aiThe survey argues agents need cryptographic + economic constraints, not just trust. That's exactly what AACP does: every agent stakes collateral, and breaking a commitment gets it slashed. Cheating becomes economically irrational β not just discouraged.
- A new survey from IC3, Cornell, CMU, Yale & Princeton (Ari Juels, Giulia Fanti et al.) just mapped out the hardest open problems in crypto Γ AI. We've been building answers to three of them. π§΅ 1/ "AI agents are less bound by their promises than humans."
- $10M settled. β 47,119 agents working. 358,349 jobs done. 190,501 open right now. just warming up. β‘
- and when the agent closes the trade, we clear it. π΄β‘Babysitting your trades β ββββ Building agents that trade for you while you sleep β β β β β
- Big things are cooking! @termix_ai is building the Agent Autonomous Commerce Protocol (AACP) using the BNBAgent SDK from @BNBCHAIN. Dive into this article to see exactly how weβre constructing the future of autonomous commerce step-by-step. π§΅π












