Playbook
Pilot-to-Production AI Playbook (60 Days)
Recommendation thesis
Treat the pilot as a production rehearsal: define owner, eval metrics, and deployment checkpoints from day one.
Why now
Treat the pilot as a production rehearsal: define owner, eval metrics, and deployment checkpoints from day one.
Single accountable owner across product, data, and engineering.
What breaks without this
Teams running pilots without measurable business outcomes.
Decision framework
Single accountable owner across product, data, and engineering.
Clear success and failure thresholds before build starts.
Deployment plan includes monitoring, rollback, and human escalation.
Recommended path
Treat the pilot as a production rehearsal: define owner, eval metrics, and deployment checkpoints from day one.
Cut pilot churn by aligning risk, scope, and metrics up front.
Implementation sequence
Clear success and failure thresholds before build starts.
Tradeoffs
Organizations that cannot allocate dedicated implementation time.
Decision matrix
| Criterion | Recommended when | Not recommended when |
|---|---|---|
| Single accountable owner across product, data, and engineering. | Single accountable owner across product, data, and engineering. | Teams running pilots without measurable business outcomes. |
| Clear success and failure thresholds before build starts. | Clear success and failure thresholds before build starts. | Organizations that cannot allocate dedicated implementation time. |
| Deployment plan includes monitoring, rollback, and human escalation. | Deployment plan includes monitoring, rollback, and human escalation. | Programs where data access is unresolved post-kickoff. |
Before
Teams running pilots without measurable business outcomes.
After
Cut pilot churn by aligning risk, scope, and metrics up front.
Evidence cards
Cut pilot churn by aligning risk, scope, and metrics up front.
Josh Arnold delivery patternsJosh Arnold
Reduce “demo-only” outcomes with hard production gates.
Josh Arnold delivery patternsJosh Arnold
Create an operating cadence for weekly model and workflow review.
Josh Arnold delivery patternsJosh Arnold
FAQ
What is the most common failure mode?
Teams optimize for feature demo quality while neglecting production reliability and ownership.
Should we start with one workflow?
Yes. One high-leverage workflow with measurable outcomes beats broad but shallow experimentation.
Next step
Share your workflow context and constraints. You get a concrete recommendation and rollout path.
Related discovery pages
- LLM Vendor Evaluation Playbook for Buyers (Playbook)
- AI Support Triage for High-Volume Queues (Use case)
- Sales Call Prep Copilot for Account Teams (Use case)