Global scale
I run AI where trust, adoption, and economics all matter.
Five concurrent enterprise programs, a $30M portfolio, 120+ contributors, and CEO-active platforms across a global public company.
D. Brian Letort, Ph.D.
AI strategy for people who have to operate it.
I write about the systems layer of enterprise AI: the models, data foundations, agentic workflows, economics, governance, and operating patterns that turn experiments into durable capability.
- Global enterprise AI operator
- $30M AI and data portfolio
- Hands-on builder and coder
- AI industry intelligence
- PhD-level teaching
- 1,000+ member AI community
- 5 U.S. Patents
- Context Compilation trilogy
- 16 Pluralsight courses
- 2 books
Follow the operating layer
Board-ready AI strategy, operator-grade technical depth, and weekly signal from the AI market.
Start reading
What to read next.
Industry intelligence
AI market signal, organized weekly.
Cross-stack flywheel
AI Stack Weekly
For officers tracking AI market movement.
Latest / Issue 17
Everything financed this week has a longer duration than the contract underneath it — and that mismatch now runs through all three lenses at once
Model layer
The Model Pulse
For architects tracking model capability shifts.
Latest / Issue 17
Six releases in five days, and the model you can benchmark stopped being the model you can run
Operating layer
Agent Techniques Weekly
For builders operationalizing agentic work.
Latest / Issue 17
Human approval finally got measured, and it caught 13.6% of dangerous commands — the control most enterprises built their agent policy on is the one that just failed its first published test
Procurement surface
The Application Layer
For buyers watching AI reshape software.
Latest / Issue 16
Two opposite answers shipped in three days to the same question: does an agent come in through the front door as a user, or get assigned work inside the system of record?
Research
Context Compilation Theory.
A foundational paper and three-paper trilogy on the systems layer between retrieval and reasoning — the governed, measurable, optimizable layer where reliability lives, where provenance is enforced, and where token economics becomes a design surface rather than an accounting line.
Why trust the signal
Strategic altitude. Technical depth. Global scale.
Technical depth
I can move from boardroom framing to code-level architecture.
Data, data science, machine learning, software engineering, agents, RAG, model routing, evals, and the operating layer between them.
Public body of work
I write, teach, publish, and build in the open.
A Context Compilation research program, PhD teaching, 16 Pluralsight courses, two books, and a weekly AI industry corpus.
Where to go next
Choose your path.
Speaking and executive briefings
I accept a small number of speaking, board, press, and executive briefing requests each year.