Work with me
The book describes the destination. An engagement starts from where your organization is.
This is for organizations where AI deployments are multiplying faster than the architecture practice can review them: regulated environments, scaling AI estates, or both. The work is pragmatic. No framework is installed on day one, and nothing is proposed that your estate cannot observe, control, or keep stable.
Three ways to engage
The assessment: where is your control gap?
For a CTO or head of architecture who suspects the gap exists but cannot yet name it.
A structured review of your AI estate against the three conditions of working control: what is observable, what is controllable, what is stable, and where the four failure patterns are already forming. You receive a written findings document with a prioritized closing sequence: which decisions belong to humans, which to supervised automation, and what must be true before anything runs autonomously.
The workshop: the gradient applied to your estate
For a leadership or architecture team that has read the book and asks what it means for them.
A working session on your real portfolio, not slides. We route a sample of your actual decisions through the layers, identify which of your standards could carry the machineReadable flag today, and leave the team with a shared vocabulary and a concrete first increment, one that delivers value before any operational tooling exists.
The advisory retainer: a standing second opinion
For an architecture function building continuous control over quarters, not weeks.
Ongoing advisory as your practice evolves: reviewing control designs before they harden, challenging decision-routing choices, and keeping the effort honest against the observable, controllable, stable test. Scope and cadence are agreed per engagement.
There are no prices on this page by design. Every estate is different, and the right first step is a conversation.
Who you would be working with
Sergey Kalinichuk (Ing. arch., Ph.D.) is an Enterprise Architect and the author of the Control Gradient framework. The approach is model-driven and grounded in classical control theory: the same discipline the book applies, applied to your organization at its actual maturity.