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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.
More of this in the newsletter → [2nd Order Thinkers URL]
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
By Jing HuEvery 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.
More of this in the newsletter → [2nd Order Thinkers URL]
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