An agent with a vision performs better
For CTOs, platform leads, and founders deploying AI agents against their own organization: every agent builds its picture of how you work from the data objects it can reach. Where those objects don't carry your vision, the agent fills the gap with a confident guess, at scale. We map where your vision is leaking out of the objects your agents read, and what it takes to close the gap.
The vision gap
Everything valuable in your company begins as leadership vision, and realizing it generates data objects all over the org — specs, code, pipelines, CRM records, support threads. Almost none of those objects were designed to carry the vision that produced them, so they drift: the same entity named three ways, definitions current in one system and stale in another, reasoning that lives in someone's head while the object records only the steps.
Humans absorb drifts in judgment. Agents can't. They act on the objects literally, at scale, and carry every ambiguity into every task downstream. We call the distance between what leadership means and what the objects say the vision gap. Closing it is architecture work, not transcription work. And it's the part of agent-readiness no one in the org chart currently owns.
The full argument — six layers in process order, with seven tests you can run on your own organization this week — is in the Field Guide.
How we engage
The Agent-Readiness Audit
A fixed-scope, fixed-price diagnostic. You get: a scored map of all six layers against our rubric (which you keep); the ten-term diff run across your actual systems, with every divergence documented; a rescue-count baseline on named workflows; a map of which steps in those workflows are deterministic and currently left to agent judgment; and three data contracts your leadership needs to ratify to unblock the program. The fastest way to know where you stand.
Fixed scope, fixed price
The Semantic Architecture Engagement
A defined project to close the gaps the audit found: principles written to be cited, the vocabulary contracted and the domain model ratified as a control surface for agent reasoning, the deterministic boundary drawn and encoded as machinery, workflows rebuilt as execution surfaces from observed runs, and judgment ownership made explicit in the architecture. It integrates with whatever platform you run, and your team owns it after we leave. The project is scoped from the audit, and we bring in senior specialists as the work requires.
Defined project, scoped from the audit
Fractional Knowledge Engineering
Ongoing senior partnership for organizations scaling agent use, where the semantic layer needs continuous architecture, governance, and evals. Not a one-time fix. Monthly retainer, with quarterly leadership briefings that translate rescue counts and consistency metrics into P&L language.
Monthly retainer
Find out how much of your vision your agents can actually see.
The audit is fixed-scope and fixed-price, and tells you exactly where your agents are guessing — and what it's costing you.
Request an Agent-Readiness Audit