The Illusion of Coherence (and the Search for Better Explanations) Part II
How Naval Ravikant and David Deutsch Shaped the Birth of InContextAble
For all the talk about dashboards, AI, “data-driven decision making,” and digital transformation, the real crisis inside modern organizations is something far more fundamental:
We no longer share a common explanation of reality.
Different teams see different worlds.
Different tools encode different assumptions.
Different metrics tell different stories.
Different AI agents invent different interpretations.
Organizations aren’t misaligned —
they’re living in parallel universes.
And leadership is expected to reconcile them.
This is the core problem that led to the creation of InContextAble, and its roots trace directly back to the ideas of Naval Ravikant and David Deutsch.
1. Naval Ravikant: Judgment Doesn’t Scale Without Context
Naval Ravikant has argued for years that real leverage comes from:
clear thinking
specific knowledge
sound judgment
simple systems that compound
But judgment doesn’t scale in organizations because context doesn’t scale with it.
Leaders make decisions with “judgment,” but every team interprets that judgment inside a different model of the world. The context that made the decision make sense at the top rarely survives its journey down the org chart.
Naval often emphasizes clarity as the foundation of good decisions.
Modern organizations have the opposite problem:
They have information abundance and clarity scarcity.
More data does not create shared understanding.
More dashboards do not create coherence.
AI-generated summaries can actually multiply interpretations instead of unifying them.
Judgment may be the highest form of leverage —
but only when everyone shares the same explanatory frame.
2. David Deutsch: Problems Demand Better Explanations
David Deutsch changed the intellectual landscape by reframing progress around explanations:
Good explanations solve problems.
Problems are inevitable.
Knowledge grows when contradictions are illuminated.
Systems fail when explanations fail.
If you apply this lens to modern organizations, something becomes obvious:
Organizational problems aren’t failures of effort or competence —
they’re failures of explanation.
The metrics don’t line up because the explanations behind them don’t line up.
Teams disagree because they’re operating from incompatible explanatory models.
Leaders issue strategy memos that seem clear but fragment rapidly upon interpretation.
Deutsch’s insight is that explanations are the foundation of reality — or at least of our ability to act effectively in it.
Organizations today are not suffering from a lack of effort or talent.
They are suffering from explanatory entropy.
Meaning drifts faster than we can stabilize it.
3. Organizations Have Become Quantum Systems (Without Realizing It)
Deutsch’s work on quantum information shows something profound:
A system can contain many possible interpretations
until a coherent explanatory framework collapses them into one.
That’s exactly what’s happening in companies today.
Before a decision:
every team has a plausible story.
After a decision:
leadership attempts to collapse those stories into a single explanation.
But there’s a catch:
We no longer have the mechanisms to maintain coherent collapse.
The system is too large.
The information flows too fast.
The interpretations multiply too quickly.
The context doesn’t propagate.
The meaning decays before it can be stabilized.
Companies used to be “classical systems,” where one narrative could dominate.
Now they’re “quantum systems,” where meaning is observer-dependent and unstable.
The old tools weren’t built for this environment.
4. The True Bottleneck: We Don’t Share the Same World Anymore
This is the problem InContextAble is designed to address.
Not productivity.
Not AI adoption.
Not alignment theater.
The real bottleneck is:
shared explanation.
You can’t scale judgment without shared context.
You can’t scale strategy without shared assumptions.
You can’t scale AI without shared meaning.
You can’t scale coherence without shared interpretation.
Organizations keep improving tools when what they need are better explanatory substrates:
shared definitions
shared assumptions
shared causal models
shared lineage of decisions
shared meaning across systems and teams
This isn’t philosophy — it’s operational physics.
Until an organization shares an explanation of reality, no amount of data will save it.
If anything, more data only accelerates interpretive divergence.
5. This Is Why InContextAble Exists
InContextAble is not a publication about AI, productivity, or organizational culture.
It is about something more fundamental:
How humans and AI maintain coherence in a world where context is infinite, interpretations are unstable, and explanations are the only true source of leverage.
Naval Ravikant provided the lens:
Judgment is leverage, and clarity is its foundation.
David Deutsch provided the engine:
Good explanations are the only thing that solve problems.
InContextAble exists to apply these insights to the one domain that desperately needs them and rarely receives them:
the everyday operating systems of organizations.
The goal is simple:
To build better explanations,
so organizations can build better decisions,
so humans and AI can share a coherent world.
6. A Quiet Acknowledgment
InContextAble stands on the work of many thinkers, but two in particular:
Naval Ravikant, whose thinking on clarity, judgment, and leverage exposed how brittle organizational decision-making really is.
David Deutsch, whose explanation-first worldview revealed why organizations collapse when their explanatory substrate decays.
Their ideas don’t just influence this project —
they form the intellectual bedrock for it.
Closing Line
In an age of infinite information and multiplying interpretations, the strongest advantage any organization can have is not speed, talent, or even AI.
It is a shared, evolving explanation of reality — one that compounds.
That is the mission of InContextAble.