Why speed matters
Long AI projects stall, bloat, and lose stakeholder trust. Short, tightly-scoped builds produce proof, surface risks early, and create internal momentum.
The 2-week playbook
- Day 1: Define success. One use case, one metric, one owner. Write refusal rules and data boundaries.
- Day 2: Design the flow. Swimlanes, triggers, systems touched, human approvals, and logging points.
- Days 3–5: Build core path. Orchestration, connectors, retrieval/logic, happy-path demo by Day 5.
- Days 6–8: Guardrails & edge cases. Error handling, rate limits, PII handling, and escalation rules.
- Day 9: UAT with owners. Real data, edge cases, capture fixes.
- Days 10–12: Hardening. Fixes, logging, alerting, runbook creation.
- Days 13–14: Launch & handover. Deploy, train users, share runbook, agree on next sprint.
Guardrails baked in
- Scope and refuse rules to avoid off-topic or risky actions.
- PII scrubbing and private/retrieval-only patterns for sensitive data.
- Alerts, logs, and rollbacks to keep incidents contained.
Tooling we move fast with
What you get at the end
- Live workflow in production with logging and rollback.
- Runbook with triggers, steps, owners, and SLAs.
- Metrics: baseline vs. post-launch (time saved, conversion, error rate).
- Backlog of next 2–3 improvements based on UAT findings.
After-launch support
We monitor in week one, fix quickly, and then either scale the same pattern or move to the next use case. If your team wants to own it, we train them and stay on-call.
Ready to ship fast?
If you need a proof point for your execs or board, a two-week build beats a 6-month roadmap. Let’s ship one, measure it, then decide what’s next.
FAQ
We pick a use case that doesn’t depend on perfect data, or add a lightweight staging step first.
Yes—scoped intents with retrieval and strict refusals can be shipped in this cadence.
We include training, comms templates, and a quick adoption dashboard.
If scope grows, we stack sprints. But the first proof point always ships inside two weeks.