Open Data Infrastructure
Agentic AI Data Write Paths and Human Review
How agents can propose data changes, attach evidence, and route approval without bypassing controls.
Read-only agents are hard enough. The moment an agent can propose a data change, the architecture needs to stop pretending chat history is a control plane.
The practical problem
Tool-calling agents can take actions through application tools. When those tools touch data, the write path needs guardrails: proposed change, source evidence, affected table, policy check, human review, commit path, and rollback evidence.
The risky pattern is letting the agent write directly because the action looks small. Small writes can break contracts, change semantics, bypass access review, or poison future retrieval.
Human review should review evidence
A useful review flow should show the proposed write, the reason, the source data, the data product contract, the policy decision, the lineage impact, and the expected downstream effect. The reviewer should approve a specific change, not a vague agent intention.
The write should land through the same infrastructure path a human change would use. That means catalog registration, contract checks, lineage capture, and audit logs. Agent work should not be special because it came from an agent.
Core idea: Agentic write paths need evidence packets, not blind trust in the agent output.
The ODI write pattern
Open Data Infrastructure gives teams a way to separate proposal from commit. The agent can draft a change. The platform can test it against contracts. The policy layer can evaluate access. A human can approve. The table can record the committed state.
That pattern also supports rejection. A denied write should create a clear explanation and a safe alternative when possible.
What breaks first
- The agent writes through an application endpoint that bypasses catalog and lineage controls.
- Reviewers see the proposed text but not the source evidence or affected contract.
- Rollback depends on manual cleanup because the write path never captured table state.
- Policy checks only validate user identity and ignore purpose or downstream effect.
Questions to ask
Ask whether agent writes are proposals or commits. Ask who reviews them, which evidence they see, and how the final write is recorded. Ask whether the same path supports rollback and incident review.
For related context, read agentic data contracts for tool calls, explainable data access failures, and data product versioning.
Sources to start with
These primary sources anchor the technical claims in this guide.
- OpenAI function calling documentation
- OpenAI tools documentation
- NIST AI Risk Management Framework
- OpenLineage documentation
The agent can propose the change. The infrastructure still has to earn the commit.