Open Reasoning explores how we think, build, and organise around intelligence, both human and artificial.
It’s a field journal for understanding clarity itself: how ideas move from confusion to coherence, and how systems—organisational or computational—either amplify or erode that clarity.
At its core, the project studies reasoning in the open: how decisions are made when outcomes are uncertain, incentives misaligned, and language overloaded.
The aim isn’t to predict the future of AI, but to make sense of the present—how intelligence is already being redistributed across people, processes, and machines.
Recurring themes include:
Clarity before code — why most AI initiatives fail before they begin, and how alignment, not algorithms, is the real differentiator
Signal vs noise — how organisations lose meaning as they scale, and what it takes to restore it
Agentic AI systems — lessons from building workflows and architectures that make reasoning operational
Decision design — how clarity turns into leverage in high-stakes environments
This publication is part notebook, part essay series, part map for those navigating the intersection of AI, systems, and strategy.
It’s written for builders, executives, and thinkers who suspect that intelligence—whether artificial or collective—starts with better questions, not bigger models.
I’m hopeful that the Clarity Before Code series that I’m currently writing will help us get to the book.
