Consulting / Legible systems
I work with AI and developer-tool companies whose products are technically powerful, strategically important, and hard to explain.
Together we sharpen the mental model, build credible proof, and create the materials and experiences that help people adopt the product with sound judgment.
The method follows the actual adoption problem: people need a model, evidence, and a way to learn.
What is this, really?
Find the simplest honest model for the product: who it is for, what changes for them, how it behaves, and which tradeoffs deserve to stay visible.
Work may include
Why should anyone believe it?
Build or shape the artifact that proves the product can do the important thing under real constraints, with enough visibility for people to evaluate it.
Work may include
How will people learn to use it well?
Turn the model and proof into documentation, workshops, technical content, and feedback loops that help developers build sound judgment.
Work may include
Start with the shape of the problem. The engagement should leave a useful artifact behind.
Engagement shape
Diagnose where a complex product loses people across the concept, developer journey, evidence, and explanation.
Leaves with
A prioritized map of the core model, friction points, and high-leverage changes.
Engagement shape
Turn an important product claim into a reference application, prototype, evaluation, or working demonstration.
Leaves with
An inspectable artifact and the technical story required to present it credibly.
Engagement shape
Create the learning path around a product launch, new capability, or changed developer workflow.
Leaves with
A connected set of documentation, workshop, content, and feedback-loop recommendations.
Show how the important thing works.
Leave something teams can use and test.
Design for judgment, not content volume.
Credibility grows when constraints remain inspectable.
Start with the difficult part
I’ll respond with the questions I would investigate and the smallest useful engagement shape.
