Three starting points · one operating thesis
Start with the uncertainty you actually have.
Some leaders know the bottleneck. Others only know that good people are losing time inside a bad system. Development teams face a different problem again. We start at the point that is real, then move toward measured operational change.
Impact Diagnostic
Over two weeks, we spend one or two days inside the operation, then continue through remote interviews, evidence review and analysis. The result is a grounded decision on where AI can move a business metric without creating another disconnected pilot.
You leave with
- Ranked workflow opportunities
- Evidence and baseline for the first one
- Sprint scope and success metric
- Prioritized 90-day opportunity map
AI Workflow Sprint
We build on the real systems with the team that owns the result, harden the exceptions and approvals, measure what changed, and transfer the system into daily use.
You leave with
- One production workflow
- Before-and-after measurement
- Human boundaries and operating rules
- Internal owners who can extend it
AI Engineering Working Day
Using one active repository and one real task, we establish a shared AI-assisted delivery loop with your team: task framing, implementation, testing, review and merge. This is not tool training. It is the first working version of a faster engineering process that preserves the team’s quality bar.
You leave with
- One real task taken through the complete new loop
- One repository configured with shared instructions and checks
- Agreed boundaries for agent action and human review
- A named owner and 30-day adoption plan
04Good fit
- A CEO, COO or functional leader owns the result
- A workflow has visible cost, delay or rework, or leadership wants evidence to find it
- The operating team can work with us directly
- You want internal capability, not permanent dependency
Not the work
- A generic AI-awareness workshop
- An innovation-theatre pilot
- A strategy deck without implementation
- A chatbot added without changing the workflow
05The boundary
None of these ends with awareness.
The Diagnostic ends with a decision grounded in evidence. The Sprint ends with a changed production workflow. The AI Engineering Working Day ends with a real repository and task working through a shared delivery loop.
We do not sell generic AI training, maturity scores or strategy decks waiting for another team to implement them.
06Start here
You do not need to choose the offer before we speak.
Bring the constraint you can see. We will tell you directly whether it needs a Diagnostic, a Sprint, an AI Engineering Working Day, or no engagement at all.