| ▲ | tiffanyh a day ago | ||||||||||||||||
Dumb question: don’t you eventually need a way to monitor the monitoring agent? If a second LLM is supposed to verify the primary agent’s intent/instructions, how do we know that verifier is actually doing what it was told to do? | |||||||||||||||||
| ▲ | alexgarden a day ago | parent [-] | ||||||||||||||||
Not a dumb question — it's the right one. "Who watches the watchmen" has been on my mind from the start of this. Today the answer is two layers: The integrity check isn't an LLM deciding if it "feels" like the agent behaved. An LLM does the analysis, but the verdict comes from checkIntegrity() — deterministic rule evaluation against the Alignment Card. The rules are code, not prompts. Auditable. Cryptographic attestation. Every integrity check produces a signed certificate: SHA-256 input commitments, Ed25519 signature, tamper-evident hash chain, Merkle inclusion proof. Modify or delete a verdict after the fact, and the math breaks. Tomorrow I'm shipping interactive visualizations for all of this — certificate explorer, hash chain with tamper simulation, Merkle tree with inclusion proof highlighting, and a live verification demo that runs Ed25519 verification in your browser. You'll be able to see and verify the cryptography yourself at mnemom.ai/showcase. And I'm close to shipping a third layer that removes the need to trust the verifier entirely. Think: mathematically proving the verdict was honestly derived, not just signed. Stay tuned. | |||||||||||||||||
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