Give the Agent a Budget, Not a Token
Sachin Malhotra
- When
- Thursday, July 23:20 PM – 3:40 PM · 20 min
- Where
- Leadership 2San Francisco, CA · imported from ai.engineer's public schedule feed
About this session
Every agent demo runs with a god-token. Then it ships, and someone has to explain why the helpful AI just rm -rf'd the staging database "to clean up." I run platform infrastructure at a frontier lab, and for the last year my job has partly been: let coding agents do real work against real systems, without ever having to write the postmortem. This talk is the permission model that fell out of that - not RBAC-with-extra-steps, but primitives designed for an actor that's smart, fast, tireless, and occasionally confidently wrong. The four primitives: - Asymmetric verbs - the agent can `quarantine` but not `delete`, `retry` but not `approve`, `propose` but not `merge`. The verb list is the security boundary. Stop thinking in resources, start thinking in reversible vs. irreversible actions. - Regenerating budgets - every agent identity gets N disruptive actions per window. Burn the budget, you're benched until it refills. No human-in-the-loop until the budget's gone — which means 95% autonomy with a hard ceiling on blast radius. - The undo test - if the agent can't undo it, the agent can't do it without a second key. One line, surprisingly load-bearing. - Tripwires over allow-lists - let the agent roam, but instrument the three actions that would actually hurt. Cheaper than enumerating everything safe. I'll show the ~200-line policy layer that implements all four, the failure modes each one exists to catch, and the one design I shipped that turned out to be security theater. Tool-agnostic - works whether your agent is touching CI, a database, a cloud account, or your users' files. If you're shipping an agent that does anything more than read, you'll leave with a threat model and a starting policy you can paste into your repo on the flight home.
Speaker
Member of Technical Staff, Anthropic
Sachin Malhotra is a Member of Technical Staff on the Developer Infrastructure team at Anthropic, where he builds and operates the CI/CD systems underpinning one of the world's largest ML monorepos. His work spans test reliability, CI observability, and—increasingly—the challenge of giving AI agents real write access to production systems, safely. He has spent the past year thinking about what it looks like when developer tooling has to scale with the pace of frontier ML research. Before Anthropic, Sachin held engineering roles at Etsy and Microsoft. He holds an MS in Computer Science from the University of Southern California.
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