The scenario:
Varex Industries is a Tier 1 automotive supplier headquartered outside Detroit, supplying powertrain components to three major OEM customers. With 2,400 engineers spread across six global sites, Varex runs 14 active programs simultaneously — and two of them are at risk of missing critical OEM delivery milestones. The root cause is familiar: dependencies that exist in people's heads, not in any system; decisions made in one meeting that never surface to the teams who need them; and a cross-functional escalation process that runs on slide decks and tribal knowledge. The program managers know something is wrong. They don't know exactly where.
You've identified Marcus Chen, VP of Engineering at Varex, as your target. Marcus oversees all active programs and sits on the OEM delivery scorecard review every quarter. He is accountable for what ships and when. He has no awareness of Empwr.ai yet.
Record a video walkthrough that opens with a short personal intro then walks through your sales playbook approach to this scenario.
Required: Upload a video walkthrough of your approach to this scenario directly on the Provn platform. See File Upload Requirements below.
Speak naturally and conversationally in your video — as if you're debriefing your CEO on what you'd do in this account. Strategic clarity and executive-peer tone matter more than production quality.
Optional: Upload sales playbook and README files
We expect you to use AI tools. We evaluate how you use them — not whether you use them. Evidence of iteration, redirection, and critical evaluation scores higher than a polished output with no visible process.
The single highest-signal indicator: your video answer to the mandatory AI question below. If you cannot name a specific moment where you redirected AI output, evaluators will assume you did not.
Mandatory AI question for your video: Walk me through one specific moment where you disagreed with, pushed back on, or redirected what the AI gave you. Name the moment. Explain what the AI produced that didn't meet the bar, what you did differently, and why.
For this challenge, AI tools are helpful for drafting and research — but they will default to generic enterprise SaaS language and miss what makes Varex's world distinct. Your job is to catch that, correct it, and produce something that would actually land with a manufacturing VP. That process of catching and correcting is what we're evaluating.
Prospect into a cold enterprise manufacturing account by writing a first outbound message calibrated to the buyer's world — not generic SaaS language
Plan and execute a discovery call that surfaces the business stakes of coordination failures, not just the symptoms
Navigate a multi-stakeholder enterprise buying committee and advance the deal past two objections: "we already have a tool" and "general AI already does this"
Demonstrate mature, critical AI usage in a sales workflow — showing where AI helps and where it needs to be corrected
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