Prepare a live demo with a recovery plan
In this article (3 sections)
A strong demo explains the user problem, shows the important path and handles failure honestly. Recovery is part of the product story.
Inspect a demo plan
The delivery lab defines a local-only fictional plan.
from delivery_cases import demo_recovery_case
result = demo_recovery_case()
assert result["normal_and_failure"] is True
assert result["recovery_present"] is True
assert result["plan"]["timebox_minutes"] == 8
assert result["external_deployment_claim"] is FalseRehearse with the exact release and versioned synthetic fixtures. Preflight credentials, network, screen sharing, data reset and monitoring. Script the narrative around user decision, evidence and limitations rather than every feature.
Show one exception and recovery deliberately. Keep a recorded normal path or screenshots as labelled backup, but state when the live environment failed. Do not switch to hidden mocks without disclosure. End with results, unresolved risk and next decision.
The FDE for Freshers course includes recorded and reviewed client-demo roleplays.
Exercise
Prepare an eight-minute capstone demo, disconnect one dependency at minute four and recover using the runbook. Review the recording against a rubric.
Continue learning
This article is part of the FDE career entry and client-delivery practice sequence. Use the neighbouring tasks when you need the prerequisite or the next application.
- Review the prerequisite or neighbouring task in Demonstrate a broken workflow before proposing AI.
- Continue with Handle a client request that changes the scope.
Reference: GOV.UK service assessment walkthrough guidance.
Pankit Kumar has 10 years in Data Science & AI, building and shipping production systems in regulated pharma and clinical environments. He is a freelance trainer at Boston Institute of Analytics, AnalytixLabs and Scaler, and has taught this material to thousands of working professionals.
This article is part of our FDE for Freshers programme — 6–7 months. Build your engineering foundations, then take AI from discovery to delivery.
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