How to Eliminate Architectural Drift in AI-Generated Code

How to Eliminate Architectural Drift in AI-Generated Code

One of the biggest challenges in AI-aided engineering is architectural drift. For example, an LLM might create a new API endpoint but forget to update the database schema, or alter a user story without modifying the QA test suite.

Demiforge eliminates this drift using a coordinated Governance Engine backed by 7 Quality Gates.

The 7 Quality Gates

Every stage in our 15-stage workflow must pass these gates before the deliverable is approved:

1. Syntax Validation: Ensures code snippets (SQL, YAML, JSON) parse correctly.

2. Semantic Review: Evaluates content clarity, logic flow, and completeness.

3. Cross-Artifact Consistency: Verifies that database columns match OpenAPI specs, and that API endpoints support the user stories.

4. Dependency Verification: Assures that downstream nodes have active links in the graph.

5. Governance & Policy: Validates against workspace design constraints.

6. Security & Risk: Checks Row-Level Security policies and STRIDE threat mitigation.

7. Human Approval: The final sign-off, giving developers full control.

By enforcing these gates, Demiforge guarantees that your engineering package is 100% consistent and ready for execution.