01 / Direction
Brief before prompt.
Every article ties back to the same rule: the agent has a named job, receiver, boundary, and source of truth.
Field notes
The first Domanski.AI blog surface.
Five practical notes on the same pattern: AI works when it is installed inside the operator, tied to real work, and checked by proof the room can inspect.
// MethodologyIn-Seat AI
// Buyer surfaceCreative agencies
// First wave5 articles
// 01 · Methodology
In-Seat AI is the credential.
The install is the product. The methodology explains why the agent belongs inside the role that already owns the work.
// 02 · Adoption
Why AI pilots fail.
Pilots drift when nobody owns the workflow, the evidence gate, or the adoption loop after the demo ends.
// 03 · Workshop
An AI workshop for creative agencies.
What the Founding Workshop does, what it refuses to be, and why the room matters more than a deck.
// 04 · Proof
The evidence gate is the adoption mechanic.
The room believes the prototype when it refuses weak input in front of the people who would have shipped it.
// 05 · Operations
Agent discipline beats agent sprawl.
Useful agents need role boundaries, memory, reports, and operator-owned decisions. Otherwise the stack just makes chaos faster.
Start here
Read the methodology, then the case study.
The blog is not a separate content channel. It is the editorial layer around the same proof already on the site: the In-Seat AI methodology, the Founding Workshop, and the client-room moments where the pattern becomes visible.
02 / Memory
Context lives outside chat.
The install is durable only when the operator can reopen the work and see what changed.
03 / Production
The work has to run.
No abstract AI enthusiasm. The standard is whether a real workflow moves faster with a named human still accountable.
04 / Proof
The gate decides.
The useful signal is not fluent output. It is the moment the system stops, cites, refuses, or reports.
// Public proof layer
The posts point back to the operating system.
The blog now behaves like the rest of the site: methodology first, proof second, offer path third. Each article has a route back into the workshop, the case studies, or the In-Seat AI method.