Agent Infrastructure
AutoDevOps
AI Agent Governance for the Regulated SDLCHypothesis
Coding agents will reach regulated engineering organizations faster than the evidence trail examiners require. Rollouts stall on proving what the agent did, not on the model.
The Thesis
Coding agents are already inside regulated engineering organizations, often ahead of any decision to allow them. The rollout stalls the first time someone asks the question every regulated change process is built around: prove what changed, who changed it, and under what authority. For agent-written code, most organizations cannot answer.
AutoDevOps makes that question answerable. It captures every Claude Code, Cursor, and Codex session inside the SDLC, down to each tool call and decision. Policy gates each action before it runs: allow it, require confirmation, or block it.
The record lands in an append-only audit log in institution-controlled storage and exports as evidence packages that verify offline. An examiner checks integrity without seeing raw prompts or source code. The separation matters because the institutions with the strictest evidence requirements are the least able to ship their codebase to a third party.
The test: whether evidence-first governance converts coding-agent pilots into sanctioned production rollouts at regulated organizations. If engineering leaders attest to agent-written change without verifiable evidence, the bet fails. Examination history suggests they will not.
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