DCP-AI protocol launches open-source tool to audit AI agents' decisions — adds quantum-resistant security for accountability

DCP-AI Protocol, a new open-source framework posted to GitHub, creates a portable audit layer (a record-keeping system) for AI agents (autonomous AI systems that make decisions and take actions without constant human input). The tool logs agent behavior in a way that survives future quantum computers, which could otherwise break current encryption standards.

Unlike existing AI logging tools that are locked into one AI framework, DCP-AI works across different AI agent platforms. This means an engineer can move an audited agent from one system to another without rebuilding the accountability layer — similar to how a USB drive works with different computers.

For teams deploying AI agents in regulated industries (finance, healthcare, law), this addresses a concrete liability problem: proving to auditors and courts exactly why an AI made a risky decision. Currently, most AI systems lack tamper-proof logs; DCP-AI's quantum-resistant encryption means records cannot be forged even if computing power increases dramatically in 10–20 years.

The code is open-source and available now on GitHub with zero adoption cost — teams can integrate it immediately into existing agent deployments.