Shane Barron: If you've ever shipped an AI agent that confidently claimed it did the work and didn't, this is for you.
I just publish
If you've ever shipped an AI agent that confidently claimed it did the work and didn't, this is for you.
I just published the whitepaper for Vision — a deterministic control layer that forces LLM agents to mechanically earn cryptographically signed permission tokens before they can mutate state, and routes their natural-language claims through a verifier-gated correction loop before those claims become decisions in your environment.
Same Macaroons primitive (Birgisson et al., 2014) that web auth has trusted for a decade — applied to the agent.
Working v0 on a single workstation. Reference implementation open-source. The threat model treats the LLM as a confused deputy: it has tools, but it must not be trusted to decide whether it's authorized to use them.
Whitepaper + repo: https://gitlab.sbarron.com/barronai/vision-system
Apache 2.0 / CC-BY 4.0.
Anyone here building agent infra in crypto-adjacent spaces — DeFi bots, on-chain agents, autonomous trading, governance — would benefit from looking at the gate design. The same problem that breaks "I fixed the bug" claims breaks "I executed the trade safely" claims.
Tag the builders. Pushback welcome.
Shane Barron: If you've ever shipped an AI agent that confidently claimed it did the work and didn't, this is for you. I just publishe
If you've ever shipped an AI agent that confidently claimed it did the work and didn't, this is for you. I just published the whitepaper for Vision — a deterministic control layer that forces LLM agents to mechanically earn cryptographically signed permission tokens before they can mutate state, and routes their natural-language claims through a verifier-gated correction loop before those claims become decisions in your environment. Same Macaroons primitive (Birgisson et al., 2014) that web auth has trusted for a decade — applied to the agent. Working v0 on a single workstation. Reference implementation open-source. The threat model treats the LLM as a confused deputy: it has tools, but it must not be trusted to decide whether it's authorized to use them. Whitepaper + repo: https://gitlab.sbarron.com/barronai/vision-system Apache 2.0 / CC-BY 4.0. Anyone here building agent infra in crypto-adjacent spaces — DeFi bots, on-chain agents, autonomous trading, governance — would benefit from looking at the gate design. The same problem that breaks "I fixed the bug" claims breaks "I executed the trade safely" claims. Tag the builders. Pushback welcome.
