Welcome to In-context-able
Escaping the Noise: A New Way to See Work, Information, and AI
Something clicked for me recently.
For years I’ve been circling around a set of big ideas about how organizations actually work — ideas about information, context, ambiguity, coordination, and the strange ways people make decisions in the real world (not the world depicted in slide decks). Ideas borrowed from Lean Thinking, Theory of Constraints, Behavioral Economics, Disruptive Innovation, Digital Minimalism, organizational psychology, and a lifetime of watching good people struggle inside bad information environments.
Then it hit me:
The biggest problem in modern organizations is not technology.
It’s not tools.
It’s not AI.
It’s not even data.
It’s the collapse of context.
We’ve built systems that can store everything except the meaning.
We’ve built dashboards that tell us everything except why it really matters.
We’ve built teams that communicate constantly but don’t necessarily build common understanding.
We’ve built sophisticated, smart collaboration tools but we still can’t find the latest version of a document.
Everyone is drowning in inputs yet starving for clarity. Everyone is creating new content, yet people barely have time to look at it, let alone absorb it and figure out what it really means.
And in that gap — the gap between information and understanding — is where the real organizational pain lives:
misalignment, rework, friction, busywork, politics, duplicated effort, slow decisions, and the creeping feeling that somehow the organization is working against itself.
If you’ve ever looked at the tools you’re expected to use and felt a subtle sense of “this can’t possibly be the best way to work,” you’re in the right place.
What In-context-able Is
In-context-able is my attempt to put language, structure, and practical tools around the thing most organizations ignore:
Context is the real operating system of work.
Not departments.
Not job descriptions.
Not workflows.
Not hierarchies.
Not software features.
Context.
Who needs what, when, why, and how it connects to everything else.
When context flows, organizations move.
When context gets trapped, work becomes a slow-motion traffic jam.
This publication is an ongoing exploration of how to:
See context with fresh eyes
Map the real (not idealized) flow of work
Understand the hidden patterns that create drag
Use AI in ways that amplify judgment rather than automate noise
Design information systems around humans, not around fields and forms
Escape the gravitational pull of complexity
My goal is not to build a new tech stack.
It’s to restore clarity.
Why Now?
We’re at a strange moment: the tools are more powerful than ever, yet the experience of working inside organizations has never been more cognitively overwhelming.
Too much information coming at you from too many directions. We are in the world where we can produce information way faster than it can be sensibly consumed, interpreted, understood and acted upon.
Individually, we often feel paralyzed by information, not empowered by it.
Organizations are no different.
When the cognitive burden exceeds the cognitive capacity, everything blends together and feels murky, decisions get shaky, and people default to the safety of process over the reality of context.
AI won’t fix this by itself.
In fact, without context, AI will make it worse.
Which is why a context-first mindset is no longer optional.
It’s the new literacy.
What to Expect Here
This publication will offer:
Big ideas about information, context, and organizational intelligence
Practical tools you can use immediately
Experiments in context mapping
Essays on the collapse of hierarchy and the limits of traditional IT
Frameworks like the Information Utility Index, The Big Mismatch, and Essential Productivity
Real talk about AI that goes beyond hype
A perspective that is subversive enough to matter, but grounded enough to use
Some posts will be sharp.
Some will be generous.
Some will be a little dangerous.
All will be anchored in one belief:
Work gets better when context becomes visible.
Thank you for being here
If these ideas resonate — if you sense there’s a deeper layer underneath all the dashboards, apps, and AI demos — you’re not alone. There is a growing community of people who can feel the gap between how work happens and how work should happen.
In-context-able is for you.
Let’s map the context.
Let’s rebuild the understanding.
And let’s rethink how organizations think.
Welcome.