RiskGate
← Use cases·Agent upgrades

The upgrade trap

When you swap the AI model, yesterday's safety evidence expires. RiskGate notices the swap and asks a person until it is recalibrated.

Transcript0:54 · narrated

Offline replay of public τ²-bench (Sierra, MIT) and AgentDojo (MIT) logs · not a live deployment

01 · What happened

The situation

Calibrated on four 2025 agents on τ²-bench airline, wrong approvals stayed under the 10% limit. Then the 2026 agents arrive, and the obvious move is to keep the calibration that worked.

02 · The miss

Why the obvious safeguard didn’t catch it

Keep the old calibration and wrong approvals jump to 14.6%: the limit breaks. Nothing in the logs flags it; the new model simply makes different mistakes.

03 · RiskGate

List, play forward, decide

  1. The certificate records the exact agent it was measured on. RiskGate fingerprints the agent; a new agent makes the calibration void.
  2. Until it is recalibrated, every write goes to a person.
  3. Recalibrated on 2026 runs: 6.4%, back under the limit. The price: 80% of airline writes still go to a person.
04 · At scale

What held, and the price

It doesn't always break, which is the point: retail held under the swap, airline broke, and on AgentDojo 35% of model swaps broke the limit. You can't know in advance, so RiskGate doesn't assume.

14.6%wrong approvals after a swap
6.4%after recalibration
35%of AgentDojo swaps broke the limit

Name one action your agent isn’t allowed to take today.

Send us its traces and what happened afterwards. We’ll show how often it could have run safely, and what it would have stopped.

The SDK is open source (Apache-2.0): pip install --pre riskgate, with full documentation. If it helps, a star on GitHub helps others find it.

Try it from your own agent: agent skills for Claude, Gemini CLI and Codex (/plugin marketplace add reallysaurabh/riskgate in Claude Code).

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