One AI support launch path
A workflow, agent behavior, tool action, escalation path, or cost symptom that needs to survive real tickets.
Production AI support
AI support agents, ready for production.
Start with one fragile support-agent workflow and turn it into something your team can operate: eval gates, handoff, guardrails, rollback signals, observability, and cost per resolution before rollout.
One launch path. One failure map. No production changes during diagnosis.
The real problem
The launch is not done until the failure path is owned.
A support agent can answer and still be unsafe to operate. The review asks what happens when the answer is uncertain, when a tool action can hurt a customer, and when the human needs context fast.
readiness signal A demo proves behavior. Operations prove responsibility.
Start with the riskiest workflow and make its failure path visible before rollout.
Method
A short operating review for one launch path.
- 01
Map the workflow
Trace the answer path, tool calls, escalation rule, owner, and customer impact.
- 02
Gate the release
Review eval coverage, guardrails, handoff quality, and the conditions that block action.
- 03
Name the operating gaps
Leave with the gaps that matter first: reliability, observability, ownership, and cost.
Offer
Review one AI support launch path before rollout.
The operating layer around the agent
Eval gates, risky actions, handoff quality, rollback signals, observability, ownership, and cost per resolution.
A production risk map
A clear view of the gaps to fix before wider rollout, written for the team that has to operate the support path.
No production access during diagnosis
The review starts read-only so the launch risk becomes visible before credentials, traffic, or infrastructure change.
Cost control stays in scope when spend is part of the launch risk. The starting point is the readiness review.
Proof model
No borrowed logos. Make the review method visible.
- Read-only first: diagnose the risk before production access changes.
- Evidence over hype: public teardowns and visible method replace logos.
- DevOps for AI support: reliability, release discipline, observability, and ownership.