Work with client teams
We work alongside your business, product and engineering teams, in your tools, on your problems. We're not an external delivery shop with a black box.
Operating principles
Approach
How we work, and why we work that way.
01
Philosophy
OverviewMost AI work fails for non-technical reasons: unclear use cases, weak ownership, demo-shaped prototypes, no evaluation. We work in a way that addresses those failure modes first. Senior people, embedded with your team, focused on a small number of things that matter.
FIG. 01 — FAILURE MODES
02
Principles
Four commitmentsStrategy before tooling
We start with the use case and the system, not with a vendor or a model. The right tool falls out of the design — not the other way around.
Real use cases only
If a use case won't survive a serious feasibility and value check, we say so early. Better to kill it in week two than in production.
Capability transfer
By the end of every engagement, your team should be more capable than when we started — with playbooks, evaluations, and ownership clearly held internally.
03
How Engagements Work
Engagement model
E.01
Small & senior
Engagements are run by partners. No layered teams between us and the work.
E.02
Time-boxed
Most engagements are 6–12 weeks, with explicit checkpoints and clear exit criteria.
E.03
Outcome-anchored
Every engagement has a small set of named outcomes — and we measure ourselves against them.
FIG. 02 — ENGAGEMENT TIMELINE
04
What We Avoid
Negative space- AI projects without a clear value case.
- Architectures that are more complex than the problem.
- Strategy work that ends in a deck nobody implements.
- Generic "AI literacy" theatre disconnected from your product and operations.