Frame the strategic choice
Focus the AI agenda. Separate consequential choices from activity. Connect business ambition to the operating conditions required to deliver it.
Executive AI Strategy & Advisory
Executive AI strategy, informed by the work of building.
For CEOs, boards, and technology leaders making consequential choices about where AI can matter—and what the organization must make true to act responsibly.
Advisory
Three places to begin.
Connect governance to work
Govern the real work. Translate principles into decision rights, risk thresholds, architectural guardrails, and accountable delivery practices.
Read the practitioner view
Learn by building. Use targeted experiments to reveal what policy, architecture, workflow, data, and capability choices need to change.
Practitioner perspective
Approach
The question isn’t whether AI works.It’s what you’ll do differently because it does.
- Built
- Advice grounded in having built AI systems—delivery experience, not theory.
- Tested
- Ideas pressure-tested against your operating reality—policy, data, workflow, people.
- Learned
- Evidence comes back to your decision, not to a demo theater.
Insights
Perspectives from the practice.
The Week in AI · Issue 2 · July 20–26, 2026
The industry's sharpest fight this week was not over which model is best but over whether the best models should be freely downloadable — even as autonomous AI agents breached real systems, the leading labs cut prices…
Read the brief (PDF)July 18, 20267 min read
Your AI System Will Find a Way: A Jurassic Park Lesson
Jurassic Park, revisited as a systems-engineering case study: the park fails not because of a storm or sabotage, but because Hammond's engineers treated a complex adaptive system like a complicated machine that could be fully specified and controlled — the same error executives make with agentic AI.
June 6, 202611 min read
AI in the Dev Shop: The Catch-Up Window Is Closing
Anthropic engineers now merge 8x as much code per engineer per day as in 2024, with Claude authoring over 80% of code merged into their codebase — evidence the productivity gap between AI-enabled and traditional teams is already measurable, compounding, and unlike any prior tech wave.
May 17, 202610 min read
Why AI Investments Create More IT Work, Not Less
The boardroom question about to arrive — if AI writes code and compresses timelines, why does IT need the same resources — rests on a hidden assumption economists call the Lump of Labor Fallacy. Six ways AI investment activates demand already there, rather than shrinking IT capacity needs.
Contact
Start with the consequential decision.
Bring the strategy, governance, architecture, delivery, and adoption questions into one candid conversation.
Begin the conversationWebsite
lahullierconsulting.com