Resources / Guide · 9 min read
The AI Sprint Playbook
How we ship a working AI system in a two-week sprint — Day 5 demo, Day 10 ship — and what we ask of you to make it possible.
Why two weeks, not a quarter
Most AI projects fail because they are scoped like enterprise software. A clean two-week sprint — bounded, fixed-fee, owner-on-call — beats a six-month roadmap nine times out of ten. The sprint forces decisions, kills scope creep, and produces something running in production by Day 10.
Day-by-day shape
Day 1 is interviews and data discovery. Days 2–4 we wire the spine — model choice, prompts, retrieval if needed. Day 5 is the first end-to-end demo with you in the loop. Days 6–9 are hardening based on demo feedback: evals, monitoring, edge cases, integration. Day 10 is ship: docs, training, and a working system pushed to your stack.
What we need from you
One owner with calendar authority. Access to the data the system will use. A real workflow with a current cost. That is it. We bring the architecture, the prompts, the evals, and the deployment.
What you walk away with
A production system, not a slide. The codebase, the prompts, the eval set, the runbook. Plus a 30-day improvement plan and the option to bring us back for the next workflow.
When this is the wrong shape
If the workflow needs a six-month data migration first, or compliance approval that takes weeks, or buy-in from twelve stakeholders — start with a Strategy Sprint instead. We will tell you upfront.
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Want help applying this to your stack?
That's exactly what an AI Sprint is for. Bounded scope, fixed price, working system in two weeks.
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