Keep AI-assisted development inside the PCI boundary
Encode your PCI DSS coding standards into every AI-assisted session so the cardholder data boundary stays tight while engineers keep their speed.
Use Cases
Fifteen worked examples, by industry. Each one starts from a control somebody in your organization already has to satisfy: a PCI boundary, a SOX change record, a NERC CIP evidence request, a licensed engineer's personal liability on a stamped drawing. Then it sets out what AI-assisted development has to do differently for that control to hold up when somebody asks.
Encode your PCI DSS coding standards into every AI-assisted session so the cardholder data boundary stays tight while engineers keep their speed.
Give auditors a structured record of how AI contributed to each code change, tied to your controls, instead of a story reconstructed after the fact.
Model documentation that arrives review-ready, because your validation-evidence standards are encoded into the sessions that produce it.
Development work that touches CIP-scoped systems produces its own audit evidence as it happens, instead of being reconstructed before the audit.
AI velocity on corporate IT and business systems, with the operational technology boundary respected by design rather than tested by accident.
Conventions and design rationale get encoded once and carried forward, so retirements and system separations stop taking knowledge with them.
Minimum-necessary PHI handling encoded into every AI-assisted session, instead of left to each developer's memory of the HIPAA training module.
A structured record of how AI contributed to each regulated software change, feeding your design history file with less manual reconstruction.
Your organization's FHIR profiles become the default every AI-assisted session builds to, so resource mappings stop diverging team by team.
The development-facing controls in your NAIC-driven AI governance program become working rules in every session, not shelfware in a policy binder.
Your maintained list of prohibited and known-proxy variables is checked in the code engineers write, at the point of change, not after deployment.
Actuarial documentation standards encoded once and applied in every session, so the work arrives review-ready instead of bouncing back for rework.
A licensed PE carries personal liability for what they stamp. Give them a reviewable account of how AI contributed to the work under their seal.
The firm's building-code and specification interpretations become the shared default across structural, civil, and MEP work.
Each client's security, data-handling, and deliverable requirements are encoded and applied automatically on that client's work.
30-minute discovery call with the founding team. We'll show you how context engineering works with your stack.
No sales pitch. Just a technical conversation. Live demos available.
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The Practice is a full-service implementation, not a self-serve subscription. We require an executive sponsor for every engagement because AI adoption is organizational change, not a technology deployment.