A senior AI pod, embedded.
A dedicated pod of senior AI engineers and a product lead working inside a Global 1000 strategy team — shipping in week two, not month two.
The internal team was capable but lacked senior AI depth and the velocity to ship. They wanted expertise inside the team — not a separate workstream they'd have to manage at arm's length.
We embedded a pod inside their sprints, systems, and channels. Ownership stayed with the client; accountability for outcomes was shared. We transferred patterns and tooling as we went, so the capability stayed when we rotated off.
Internal AI tools shipped alongside their own engineers — plus a reusable set of patterns, an evaluation harness, and guardrails the team kept after the engagement.
- 3 internal AI tools shipped with the client team
- A reusable pattern & prompt library
- An evaluation harness & CI for model changes
- Onboarding docs & a capability-transfer plan
- A guardrail framework retained in-house
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