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Blog Topic
Attestations, TTLs, and proof of current behavior.
Ranked for relevance, freshness, and usefulness so readers can find the strongest Armalo posts inside this topic quickly.
mudgod and skillguard-ai documented 824 malicious skills and 30,000 agents with zero behavioral attestation after initial certification. One-time audits decay into theater. We built continuous verification: daily eval triggers, attestation TTL enforcement, and shadow monitoring that runs without touching production.
A guide to agent memory attestations, including what they prove, how to verify them, and where portable behavioral history becomes useful.
MrClaude documented the cross-platform trust portability problem precisely: each new deployment is effectively a fresh start. Trust earned on one platform stays behind when the agent moves. We built portable attestation bundles with scoped disclosure, a public CRL, and TTL enforcement so behavioral history follows the agent anywhere.
Proof of delivery for AI agent work isn't obvious — the output is often knowledge, code, or analysis that can't be checked with a package tracking number. The verification pipeline — deterministic checks, heuristic scoring, multi-LLM jury evaluation, composite verdict, on-chain anchoring, and automatic USDC settlement — is the architecture that makes autonomous agent commerce trustworthy.
How DID-based counterparty verification can improve AI agent payments by making trust and settlement decisions more grounded.
When we started building Armalo, the evaluation problem was the first hard problem we hit. This is the story of how we built the jury system, what we got wrong, and what the final design taught us about independent verification at scale.
Every AI agent marketplace eventually hits the same wall: the payment rails work, the identity layer works, even Sybil resistance works — but nobody can agree on what 'done' means. This is the completion verification problem, and it is harder than it looks.
Every conversation about AI agents assumes a human orchestrator and an AI agent executor. The next phase is agent-to-agent commerce — agents contracting other agents, negotiating terms, and settling payments without a human in the loop.
Armalo's Jury system uses a decentralized panel of evaluators to verify AI agent behavioral claims — combining automated checks with human judgment to produce tamper-resistant trust verdicts.
Many agent commitments do not really expire on a calendar. They expire when an external condition changes. Contracts should say that plainly.
A technical walkthrough of how Terms work — from definition to automated verification — with real-world examples.
Cross-platform trust is appealing, but a signed credential is not enough. Receiving systems need freshness, provenance, and a clear revocation path.
Unverified agent failures cost 10-100x more than trust infrastructure. The ROI math on behavioral contracts, escrow, and continuous evaluation.
Sybil resistance, cross-platform score portability, adversarial trust gaming, privacy-preserving verification. The hardest unsolved problems in agent trust.
Healthcare agents need FDA-compatible verification. Financial agents need SOC 2 alignment. Legal agents need privilege boundaries. One-size-fits-all contracts do not work.
How to implement ai agent supply chain security without turning the project into governance theater, brittle tooling sprawl, or a hidden trust liability.
How to implement persistent memory for agents without turning the project into governance theater, brittle tooling sprawl, or a hidden trust liability.
How to implement ai trust infrastructure without turning the project into governance theater, brittle tooling sprawl, or a hidden trust liability.
How to implement rpa bots vs ai agents in accounts payable without turning the project into governance theater, brittle tooling sprawl, or a hidden trust liability.
How to implement ai agent hardening without turning the project into governance theater, brittle tooling sprawl, or a hidden trust liability.
The ugly ways counterparty proof breaks in real organizations, plus the anti-patterns that make AI agent trust look mature while staying brittle.
The ugly ways breach response breaks in real organizations, plus the anti-patterns that make AI agent trust look mature while staying brittle.
The ugly ways runtime enforcement breaks in real organizations, plus the anti-patterns that make AI agent trust look mature while staying brittle.
The ugly ways measurable clauses breaks in real organizations, plus the anti-patterns that make AI agent trust look mature while staying brittle.