AI Workflow Production Sprint
A bounded implementation for putting one AI-assisted workflow into production inside the existing operating stack with evaluation, human controls and monitoring.
Definition
A bounded implementation for putting one AI-assisted workflow into production inside the existing operating stack with evaluation, human controls and monitoring.
Why it matters to the business
It is designed for a specific repetitive information workflow with clear inputs, outputs, review rules and representative examples.
How it works
The implementation integrates the agreed model/API, workflow and existing systems, tests real inputs, applies controls and instruments usage/cost and operational visibility.
Where it appears in real systems
The standard package is $3,500 implementation plus $1,000/month managed maintenance after stabilization; qualification is required before checkout.
Common failure modes
- The operating problem is broader than the written package boundary.
- Required client access or decisions are unavailable.
- New functionality is added without re-scoping.
Implementation considerations
- Confirm standard-package fit before checkout.
- Keep implementation and maintenance boundaries visible.
- Use acceptance criteria before stabilization.
When it is appropriate
Use it where AI has a defined operational role; do not use it as a vague business-wide AI transformation project or unattended high-stakes decision system.
When it is not appropriate
Choose another package, discovery or a custom scope when the standard boundary does not fit.
Relationship to BYFORCE
This is the Docs explainer for the AI Workflow Production Sprint.
Source basis
- docs/commercial/BYFORCE_PACKAGE_BIBLE.md
- docs/website/BYFORCE_SELF_SERVICE_INTAKE_SPEC_2026-09-23.json