Every team that won the Gemini 3 Hackathon built a workaround for something AI can't do. That's not a coincidence — it's the pitch, read backward.

I looked at all three winning products: a supply chain crisis tool, a disaster triage system, and an assistive navigation app. Each one won by designing around an AI failure — and each workaround comes with a cost the sales deck doesn't mention.

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What you'll leave with: A framework for reading any AI pitch in reverse. Stop at the human approval gate, the explainability layer, the memory patch — and ask what it's compensating for. That question is worth more than any demo.

Mentioned in this episode:

Globot (Gemini 3 Hackathon grand prize)

Aegis (2nd prize)

Netra / Memory Palace (3rd prize)

Deloitte / UK Ministry of Defence automation bias report

Carnegie Mellon + Stanford research on human-agent supervision costs

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