AI Research Leader •Ex-Meta, Uber, Apple

Rich Dad, Poor Dad wasn't about money. It was about two ways of seeing the same asset that produce completely different outcomes. This is that — for research intelligence.
Your AI research produced something this week that felt confident, organized, and thin. It confirmed what you already suspected. It found the trend that's already in the press headlines.
That's factory logic. And it's the default setting of every AI research tool on the market.
Listening logic is different. It treats data as living intelligence that's distributed across communities, carried in language people reach for when the proper vocabulary doesn't exist yet, buried in places people speak when nobody important is listening.
Same tools. Same data. Completely different results.
In 3 hours, you'll see this difference demonstrated. Three times. Side by side. On real research questions from the room.
Then you start building it yourself.
Your AI agreed with you this week. Told you your idea was great. That's not a model problem — it's a philosophy problem. We name it here, then fix it.
You bring a real question. We run it two ways. One takes it at face value. The other interrogates the assumption underneath. Both on screen. You choose.
Same findings, two approaches. One returns five clean themes. The other finds something you didn't go looking for. Same data. You decide which earns its place.
You've ignored a persona by slide three. Your Synthetic users sound robotic. This one speaks human. You test your positioning live and hear what no demographic field would ever say.
What do you believe about your data that no generic prompt knows? That belief becomes architecture. Draft the conviction, the cognitive functions, the opening instruction.

Author of 'How Not To Use AI' • AI Research Leader • Ex-Meta, Uber, Apple

Researchers and insights pros whose intelligence got thinner when AI got faster. You know what depth feels like. This brings it back.
Consultants, marketers and strategists tired of AI outputs that confirm what the room already believes. You need the signal 12 months early.
Product and innovation teams who need to find what the market hasn't named yet; not validate what it already knows.

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