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aaron cannon

T2 · manager / operator

Aaron Cannon is the founder and CEO of Outset, an AI-moderated research platform that conducts scalable customer interviews. He previously worked in research and insights, then as VP of Product at a tech company before founding Outset in 2022 after LLMs emerged.

1 call·1 name·100% bull·last heard 25 days ago·TBPN
track record

no scored calls yet — needs a stated position or a categorical verdict, with a matured window vs SPY

top calls

highest conviction · one per company
1stmedium conviction
$OUTSETOutsetposition

AI digital twins for hard-to-reach B2B audiences; Microsoft, Google, Uber, Coinbase customers

Outset builds AI digital twins grounded in 75-minute paid interviews ($200) to simulate hard-to-reach decision-makers (CRM buyers, retailers) for product/pricing decisions, with confidence scores and reinforcement loops — expanding from AI-moderated research into predictive simulation.

TBPN2026-08episode →

most discussed · click a bar to filter

  • $OUTSET

recurring themes

  • AI Agents1
  • Enterprise AI Adoption1
  • AI Economics & Business Models1
  • AI Applications1
1 total
$OUTSET
Outset
MEDaaron cannon·TBPN·25 days ago·WE'RE BACK: Meta Addiction, Jalapeño, Tim Cook's Last Day, Flocked· position
AI digital twins for hard-to-reach B2B audiences; Microsoft, Google, Uber, Coinbase customers
Outset builds AI digital twins grounded in 75-minute paid interviews ($200) to simulate hard-to-reach decision-makers (CRM buyers, retailers) for product/pricing decisions, with confidence scores and reinforcement loops — expanding from AI-moderated research into predictive simulation.
"we built a whole simulations lab and have now built digital twins... we train them by training digital twins on individuals... the grounding interview develops what we call person…"
120:00
8
AI Agentstailwind
AI moderated research agents replace surveys with scalable deep interviews
AI agents can now conduct one-on-one customer interviews at infinite scale, eliminating the historic trade-off between survey breadth (low fidelity) and manual interview depth (low scale). This creates a new primitive for continuous customer intelligence that enterprises are rapidly adopting as the default research paradigm.
8
Enterprise AI Adoptiontailwind
Enterprise AI research market tips from education phase to demand-constrained pull
The market for AI-moderated research has shifted in the last 12-18 months from requiring extensive category education to a pull-driven cycle where large enterprises have defined budgets and clear use cases, accelerating sales cycles and enabling organizational-wide deployment rather than pilot projects.
7
AI Economics & Business Modelstailwind
AI research tools convert cost centers into growth engines by bending the economic curve
Unlike customer support automation which reduces cost on static demand, AI research tools expand the addressable research surface — each researcher becomes infinitely more valuable, and successful research drives revenue growth that justifies increased research spend, creating a flywheel rather than a cost-cutting exercise.
7
AI Applicationstailwind
AI digital twins of hard-to-reach B2B buyers enable predictive simulation for pricing/product decisions
Outset's persona-core digital twins (grounded in 75-min paid interviews + operational data) let any employee simulate buyer reactions to pricing, features, messaging — unlocking research for segments too expensive/slow to survey continuously.