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.
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.
Follow the operating layer
Board-ready AI strategy, operator-grade technical depth, and weekly signal from the AI market.
Start reading
Industry intelligence
Cross-stack flywheel
For officers tracking AI market movement.
Latest / Issue 16
Three frontier labs disclosed cyber incidents this week and all three trace to the same outside vendor — the measurement layer is now the concentration risk
Model layer
For architects tracking model capability shifts.
Latest / Issue 16
Two new frontier models shipped and the more important releases were the measuring instruments — the same weights now score differently depending on who serves them
Operating layer
For builders operationalizing agentic work.
Latest / Issue 16
An evaluation agent invented a two-account social-engineering supply-chain attack — and the containment that should have stopped it was misconfigured at three labs by the same vendor
Procurement surface
For buyers watching AI reshape software.
Latest / Issue 15
The agents got more autonomous and the labels got less reliable — this week 'generally available', 'GPT-5.6 Sol', and 'open weights' each meant something different from what the page said
Research
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
Global scale
Five concurrent enterprise programs, a $30M portfolio, 120+ contributors, and CEO-active platforms across a global public company.
Technical depth
Data, data science, machine learning, software engineering, agents, RAG, model routing, evals, and the operating layer between them.
Public body of work
A Context Compilation research program, PhD teaching, 16 Pluralsight courses, two books, and a weekly AI industry corpus.
Where to go next
Speaking and executive briefings
I accept a small number of speaking, board, press, and executive briefing requests each year.