It's usually an articulation problem

I help founders, operators, and product teams turn AI opportunities into software.

Send a workflowSee proof patterns

Who this is for

Teams with real work, unclear requirements, and no patience for AI theater.

There is a workflow everyone knows is broken.

Manual triage, expert review, fragmented data, repeated judgment calls, and hidden operational cost.

The opportunity is obvious, but the product is not.

You need someone who can talk to users, map the system, design the loop, and build the first version.

The work sits close to customers and constraints.

This is FDE-shaped work: fast discovery, pragmatic architecture, clear communication, and shipped artifacts.

Engagement shapes

Concrete ways to start.

01

AI Workflow Audit

Map a process, identify high-leverage automation points, and leave with a build plan grounded in the work.

02

Prototype Sprint

Turn a candidate workflow into a demo with synthetic or approved data, clear assumptions, and next-step decisions.

03

Build Partner

Design and implement internal AI tools, LLM-backed product features, retrieval workflows, and human-in-the-loop systems.

Stories

How specific problems got solved.

Decision Memo

Build vs. managed platforms

The AI capability gap between layers has largely closed. The infrastructure gap has not. The right question is where the hard part of your problem actually lives.

Decision Memo

Eval dimensions and what they're for

Comprehensiveness feels like rigor. It produces noise. The eval suite should reflect what success looks like for each interaction type, not what the framework can expose.

How I work

Start with the work. Then choose the model, interface, and system boundary.

  1. Discover: interview users, observe the workflow, and name the real decision points.
  2. Map: turn ambiguity into process diagrams, data requirements, risks, constraint boundaries, and evaluation criteria.
  3. Prototype: build the smallest useful loop with feedback, auditability, and a clear failure path.
  4. Operationalize: harden the parts that deserve production, measure what the system actually does under real conditions, and cut what does not survive contact with users.

Start here

Bring a messy workflow, an AI product idea, or an FDE-shaped role.

The strongest first message includes the workflow, the people involved, the current bottleneck, and what a useful first version would change.

seth@verbalagency.com