Coding agents can produce changes faster than a team can explain why those changes were authorized, how they were verified, and who accepted the risk of putting them into production.
Git identifies commits. Agent transcripts record activity. Tickets describe work. These records often fail to identify the responsible decision, the constraints that shaped it, and the evidence used to approve it.
This is a traceability problem. Greater agent autonomy makes the missing links more consequential.
Responsibility follows the decision
Authorship identifies who or what produced the code. Production responsibility requires a record of who authorized the work, defined where the agent could act, decided which evidence was sufficient, and accepted the change.
Those decisions remain human responsibilities when an agent performs the implementation. The organization must be able to reconstruct them from business intent through to production.
A transcript is not a decision record
Agent platforms can preserve prompts, tool calls, terminal output, and patches. These records can help diagnose failures. They rarely establish organizational authority on their own.
A useful record answers six questions:
- Who authorized the work?
- What outcome and constraints did they define?
- Which repositories, tools, data, and environments could the agent access?
- Which exact change was reviewed?
- What evidence did the reviewer inspect?
- Which approved change reached production?
The full transcript may provide supporting detail. The primary record should remain small enough to review.
The minimum chain
An agent-assisted production change needs a traceable path from intent to authority, agent boundary, change, verification, human acceptance, and deployment.
Intent records the problem, desired outcome, and fixed constraints.
Authority identifies who commissioned the work and the unit of work they approved.
Agent boundary records where the agent could act, including tools, data, network access, repository paths, and actions requiring approval.
Change identifies the immutable commit or patch that was reviewed.
Verification ties tests and other checks to that exact change.
Human acceptance records who approved the change and which evidence supported the decision.
Deployment connects the accepted commit to the artifact and environment that received it.
The chain must work in both directions. Starting from production, a team should be able to find the intent and approval. Starting from the intent, it should be able to find the deployed result. Neither investigation should depend on the person who still remembers what happened.
The regulatory boundary
The EU Digital Operational Resilience Act requires financial entities to maintain a documented ICT risk management framework and assess risk around major ICT changes. It does not prescribe a universal record for coding-agent sessions.
The European Central Bank's priorities for 2026 to 2028 include ICT change management and banks' AI governance and risk controls. The traceability chain described here is an engineering response to those concerns. It is not legal advice or a compliance certificate.
Keep the links close to the code
Most teams already have an issue tracker, Git, pull requests, CI, and deployment records. The links between them are weak or optional.
Start with a few enforceable conventions:
- Give every production change a stable work identifier.
- Record intent and fixed constraints before implementation.
- Put the identifier in commits, checks, approvals, and deployment metadata.
- Preserve the agent boundary used for the work.
- Approve an immutable commit rather than a moving branch.
- Record which artifact and environment received that commit.
I built Warrant to implement this model in a Git-native form. Other issue trackers and source-control platforms can preserve the same chain. The model matters more than the tool.
Start with one team, one codebase, and one recent production change. Try to reconstruct it in both directions. The missing links will show which controls, integrations, or ownership decisions need attention.
If your team is introducing coding agents into a regulated or operationally sensitive delivery process, I offer a two-week Agentic Engineering Control Review. We follow one real change from intent to production and leave you with a control model and a 30-day implementation plan.
Discuss an Agentic Engineering Control Review