TDDGuard
Prompt-guided compliance checks that reinforce test-first development with AI coding assistants, helping teams restore and maintain TDD practices during software delivery.
The Problem
“AI coding assistants accelerate delivery but erode test-first discipline”
Organizations face these key challenges:
Developers accept AI-generated code before defining expected behavior
Code reviews catch TDD violations too late in the lifecycle
Coverage metrics do not prove tests were written first
Engineering managers lack visibility into AI-induced workflow drift
Impact When Solved
The Shift
Human Does
- •Define and communicate test-first development expectations
- •Write tests and implementation during coding sessions
- •Review pull requests for signs of implementation-first work
- •Request missing tests or rework before approving changes
Automation
- •Generate implementation code from developer prompts
- •Suggest tests when explicitly requested by developers
- •Assist with code completion during implementation work
Human Does
- •Confirm intended behavior and approve test-first workflow exceptions
- •Review flagged TDD compliance issues and decide corrective action
- •Approve pull requests with unresolved risk or policy deviations
AI Handles
- •Monitor prompts, code changes, and workflow order for TDD compliance
- •Detect implementation-first patterns and flag risky work in real time
- •Generate failing tests and corrective prompts before implementation proceeds
- •Score and report TDD adherence across changes and teams
Operating Intelligence
How it works
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
TDDGuard must not approve a pull request with unresolved TDD risk or policy deviation without a developer or reviewer decision [S1].
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in TDDGuard implementations:
Key Players
Companies actively working on TDDGuard solutions: