From an AI pilot to a workflow your team can run
2 min read
An AI pilot can depend on its creators to fix a prompt, rerun a task, or interpret an unclear result. Production requires those decisions to become visible responsibilities and repeatable operating steps.
An AI FDE engagement connects the workflow to the systems and people who will operate it. This note focuses on access, exceptions, and handoff: the work that remains after the demonstration succeeds.
Work beside the people running the process
A forward deployed engagement starts with the operational workflow. Watch how a task moves through the team and make the constraints explicit before introducing automation.
Choose a bounded first use case and agree on an owner who can make decisions about the process.
Build the operational edges
Connect identity, data access, review, and logs alongside the core capability. Document which actions the system can take and which need a person.
Keep a practical fallback available. The team needs a way to continue working when a dependency is unavailable or an input cannot be processed.
Hand over a system people can operate
Deliver a runbook, representative evaluation cases, and a clear maintenance owner. Walk through an exception with the team before considering the handoff complete.
Use the pilot to decide what to improve next. Expansion should follow observed value and operational readiness.
Put this into practice
Explore the related work and delivery scope.
- Related project: KIMEO
Inspect the published product workflow and delivery context.
- Explore the relevant service
See the engagement scope and start a specific project conversation.
Plan the handoff as part of the build
Share the pilot, connected systems, exceptions, and the team expected to run the workflow.
Discuss AI FDE delivery
