About
Founder of Real World AI Design. Forty-plus years of enterprise IT, systems design, and software engineering — now applied to the work of building AI systems that actually ship.
Most AI consultants come at it from the model side. They learned ML in the last few years, can speak fluently about transformers and embeddings, and can build a demo. What they often haven't done is run an enterprise data pipeline that didn't break, integrate two systems whose owners disagreed about ownership, design for security and audit from day one, or hand off a production system to someone else and have it keep working.
Forty years of enterprise IT teaches you those things. Painfully, sometimes. The work that makes AI succeed in production isn't the model. It's the data discipline, the integration patterns, the governance, the observability, and the people-and-process scaffolding around the whole thing. AI is genuinely powerful. It's also fragile in production unless you build the system around it deliberately.
That's what Real World AI Design exists to do. Architect AI as a complete system — data, intelligence, decision, action, feedback — in organizations that have real operations to protect and real outcomes to improve. Not pilots. Not experiments. Not slide decks of frameworks. Working systems.
Terry also takes on long-term advisory engagements where ongoing AI architecture leadership is needed alongside an internal team — see the Retainer tier on the Services page.
For Build and Architecture engagements that need more than one architect to ship, Real World AI Design sources vetted subcontractors per-engagement — AI engineers, data engineers, ML practitioners. Terry stays accountable for delivery and design oversight; the talent executes under contract. See the Talent Enablement section on the Services page.
Production AI systems built into the operations they're meant to improve — not isolated experiments that demo well and die in pilot.
Data quality, structure, and governance treated as first-class problems — not as the thing we'll figure out after the model works.
Architecture for resilience, scalability, and cost efficiency. The substrate every modern AI system depends on.
Continuous, outcome-driven security — built into the system from day one, not bolted on after deployment.
The work that makes everything usable. The most underrated — and most consequential — discipline in enterprise AI.
Computer vision, sensor fusion, prediction systems, structured data extraction. Working systems, not slide decks.
A working architect has to keep learning. The platforms change. The disciplines deepen. Currently formalizing the AI & robotics work in an academic program, alongside ongoing platform certifications across the major AI ecosystems.
Education is supplemental, not foundational. The foundation is forty years of shipping things that had to work.
Most useful first step is the free assessment — gives us both shared context for the conversation. If you'd rather email or talk first, that's fine too.
Email: terry@realworldaidesign.com
Based: Houston, Texas
Most discovery calls are 30 minutes, no preparation needed.