Help with the groundwork
Exploring an unfamiliar codebase, drafting scaffolding, suggesting refactors and proposing test cases. Suggestions are a starting point for an engineer, never a finished change.
AI-assisted engineeringAI-assisted.
AI-assisted.
Human-owned.
We use AI tools to help explore, draft and check code and documentation. Engineers decide what ships. They review every change, test it against agreed acceptance criteria and stay accountable for the system.
How we use itAssistance,
Assistance,
not autopilot.
AI is one tool inside an engineering process that already has review, testing and handover. It does not replace that process or the people responsible for it.
A person reviews every change
AI-assisted code goes through the same human review as any other code. An engineer reads it, understands it and can explain why it is correct before it moves on.
Tested against agreed criteria
Browser testing, automated tests and relevant regression checks apply whoever or whatever wrote the first draft. A change is ready when the evidence says so.
Sensitive data stays inside the boundary
Credentials, tokens, health information and personal customer data are not shared with tools outside the agreed boundary. Tool use is agreed per engagement.
No productivity percentage, speed multiplier or ROI figure is claimed. The value of any tool is judged by the same evidence as any other engineering change.
OwnershipThe engineer stays
The engineer stays
accountable.
Whoever drafts a line of code, an engineer owns the result: the design decision, the test evidence and the handover notes that explain how it runs.
Read the FAQ Book a call
Cortex partnersAccountable AI,
Accountable AI,
with Cortex.
WFA Labs are Cortex partners. Cortex helps us manage AI-assisted work and keep it accountable and compliant.
- Traceability. What an AI tool or agent did, and in which system.
- Audit trail. Who requested an action and who approved it.
- Oversight. Human review and control over AI agents and tools.
Book a callHave a system that
Have a system that
needs careful engineering?
Tell us the operating context, the delivery stage and the question the engineering needs to answer. We will start with the system, not a sales metric.