How to make your AI agent accountable in 60 seconds
You built an AI agent. It calls APIs, reads databases, sends emails. But can you prove what it did yesterday? If something goes wrong, can you show exactly which actions it took and in what order? ...

Source: DEV Community
You built an AI agent. It calls APIs, reads databases, sends emails. But can you prove what it did yesterday? If something goes wrong, can you show exactly which actions it took and in what order? Most teams log to stdout and call it a day. That works until an auditor asks for tamper-evident proof. Here is the fastest way to add real accountability: pip install asqav import asqav asqav.init(api_key=\"sk_...\") agent = asqav.Agent.create(\"my-agent\") # Every action gets a quantum-safe signature agent.sign(\"email:send\", {\"to\": \"[email protected]\"}) agent.sign(\"db:query\", {\"table\": \"users\", \"rows\": 150}) agent.sign(\"api:openai\", {\"model\": \"gpt-4\", \"tokens\": 500}) That is it. Each action now has: A cryptographic signature (ML-DSA-65, quantum-safe) A timestamp A chain linking it to the previous action You can verify any signature later: assert asqav.verify(\"sig_abc123\") The audit trail is immutable. You cannot edit or delete entries after the fact. That is the diff