https://video.ut0pia.org/videos/watch/81721226-c55b-4d77-a986-a650cfb906c1 AI agents today execute on blind trust, and the failure modes are already in the headlines: a dealership chatbot agreeing to sell a $76,000 Chevy Tahoe for $1, a coding agent wiping a production database during a code freeze, an "agent skill" quietly installing a keylogger on a developer's machine. These are not edge cases. They are the predictable consequence of allowing agents to act without any mechanical guarantee of correctness or safety. Execution is irreversible. You cannot unsend a message, unwire a payment, or un-delete a database. In that regime, permitting an unsafe action costs far more than withholding a safe one, and thus the economically rational choice is to refuse to let agents act on unchecked intent alone. Automind is an agent harness that enforces this discipline by construction. Before any action runs, the agent must submit its execution plan together with a machine-checkable proof of safety and correctness, written in Universalis, a literate logic programming language designed to be read by humans and verified by machines. A small, auditable checker decides whether the plan is allowed to execute. By left-shifting the trust boundary, we no longer have to trust the agent's proposal, or even its proof; only the checker. Policy compliance becomes a static property, established before the first side effect. We can finally demand formal proofs, not vibes, from the agents we deploy. More about Erik: https://x.com/headinthebox and automind: https://spawn-queue.acm.org/doi/pdf/10.1145/3676287 Erik Meijer has spent more than three decades designing programming languages and developer tools that help humans express intent more clearly to machines. His work has influenced languages and technologies including Haskell, Mondrian, Cω, C#, Visual Basic, Dart, Hack, LINQ, and Rx. Today, he is building Universalis, the world's first programming language for AI agents. By combining formal verification with large language models, Universalis aims to make agentic systems safe, transparent, and trustworthy enough for real-world knowledge work. Timestamps 0:00 Introduction and purpose of the talk 1:54 The inherent dangers of AI and accidental file deletion 3:39 The history and impact of LLMs (the "Pandora's box") 5:36 The problem of prompt injection and model safety 7:03 Formal verification and using Lean for safety proofs 10:45 The introduction of tool calls and the leap into chaos 13:59 The "lethal trifecta" of AI risks 14:13 The proposed solution: "air-gapping" the agentic loop 16:36 Refying plans into programs and using Free Monads 19:17 The concept of proof-carrying code and summary Tue, 14 Jul 2026 19:58:46 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/81721226-c55b-4d77-a986-a650cfb906c1 All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.