Lab Notes
Where we think out loud.
Long-form essays on AI strategy, organizational design, and the practical realities of building systems that actually work. We write these to clarify our own thinking, and to share it with people navigating the same questions.
These aren't hot takes or trend summaries. They're essays that take a position: on how organizations should think about AI, where the real risks are, and what it means to build with intention rather than velocity. If you're trying to understand the landscape of applied AI (not the hype, but the hard problems), this is a good place to start.
For write-ups on specific projects, design decisions, and what we learned building them, see Build Notes.
Building Organizational Judgment: A Practical Implementation Framework
AI will give your organization speed by default. What you do not get by default is judgment: the ability to pause at the right moments, interpret meaning, weigh consequences, and stay accountable when plausible outputs look correct but are not right.
Beyond Bloom's Taxonomy: The Post-Cognitive Layer Where Human Value Concentrates
As AI systems perform across all levels of cognitive work, human value shifts beyond cognition into a post-cognitive layer focused on judgment, meaning, and intention.
The Hallucination Imperative: Why AI Fluency Increases Human Responsibility
As generative AI grows more fluent and convincing, human responsibility doesn't shrink, it grows. The organizations that thrive won't be the fastest, but those that design for judgment where it matters most.
From Intelligence to Providence: What Happens When AI Operates in the Probability Layer
As AI makes intelligence fast and ubiquitous, competitive advantage shifts to what remains scarce: human judgment and the ability to govern meaning over time.
Why Judgment Becomes Your Most Valuable Asset in an AI-First World
In a world where AI can execute faster than humans can deliberate, the organizations that win will be those that protect and cultivate human judgment rather than erode it.
The PRD is Dead: Why Enterprises Must Embrace the Autonomous Builder Model
This article argues that the traditional Product Requirements Document (PRD) is obsolete in the age of generative AI, which has collapsed the distance between idea and execution. It proposes the "Autonomous Builder Model," where a single operator, augmented by AI, can ideate, prototype, test, and deploy solutions with minimal reliance on handoffs. For enterprises, embracing this model means empowering domain experts, building secure AI platforms, reframing governance to prioritize outcomes, and measuring speed and impact, ultimately shifting central IT's role from sole builder to enabler of a distributed network of innovators.
The AI Speed Imperative: Why Business Velocity Just Changed Forever
AI is fundamentally reshaping business, accelerating project timelines, democratizing expert capabilities, and enabling simultaneous workflows. This "AI speed" allows organizations to achieve in days what once took months, forcing a strategic rethink. Companies that embrace compressed timelines, democratize tools while centralizing strategy, design for parallel exploration, and map their business logic will gain a significant competitive edge.
The Wisdom and Limits of Apple's AI Caution: Charting a Pragmatic Course in the Age of AI Hype
Apple's new findings cut through the AI fog, pinpointing where "reasoning" models falter and showing why an ontology‑led game plan keeps innovation on solid ground.
What Kind of AI Leader Does Your Organization Really Need?
Is your AI vision inspiring progress or quietly stalling it? Discover the four leadership archetypes that make or break enterprise AI strategy, and see which one your organization truly needs next.
New notes, when they're ready.
No cadence. No filler. Just the next essay when it's worth your time.