Most enterprise AI pilots fail because companies treat agent development like legacy software projects. Woodson Martin, CEO of OutSystems and former Salesforce executive who led the Krux acquisition, explains why deterministic platforms beat "vibe coding" for production deployments. He breaks down agentic workflow architecture that gives enterprises control over which processes stay human-supervised versus fully automated, shares specific productivity metrics from oil rig safety inspections that prove ROI, and reveals why mortgage underwriting automation hits 98% straight-through processing while preserving customer relationships.

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Most AI pilots fail because founders are retrofitting old playbooks instead of rebuilding revenue architecture. Mark Roberge, founding CRO at HubSpot who scaled from $0 to $100M revenue, breaks down how AI compresses traditional sales cycles and transforms go-to-market execution. He reveals why selling time will jump from 25% to 75% of a rep's week, how AI enables real-time ICP refinement and account targeting, and why sustainable moats now depend on owning the point of work rather than systems of record.

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Most vertical AI companies fail because they're building features, not businesses. Rachel ten Brink, GP at Red Bike Capital and former Scentbird co-founder (scaled to 500K+ subscribers, $29M raised), breaks down how to build defensible vertical AI that survives the regulatory gauntlet. She reveals her operator's test for distinguishing product businesses from services wrappers, explains how winning data network effects emerge from proprietary processing of public data, and shares the specific go-to-market playbook that works for enterprise AI sales cycles.

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Most AI adoption in finance is just automation theater—real transformation requires rethinking entire workflows. George Lee, former CTO and M&A head at Goldman Sachs, explains why AI won't replace bankers but will compress deal cycle times from weeks to days. He breaks down how junior talent using AI companions can eliminate rote tasks while expanding analytical surface area, and why the "Boyle's law" principle means human capital will always find new problems to solve for clients.

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Most AI investment flows to infrastructure while founders ignore energy constraints that will determine who survives. George Lee, Co-Head of Goldman Sachs Global Institute, breaks down the bottlenecks choking AI deployment from silicon to grid capacity.

George reveals flexible demand management frameworks that could unlock 75-125 gigawatts of slack capacity, eliminating energy bottlenecks. He and Tom go on to discuss why Middle Eastern sovereign wealth funds are building strategic energy advantages, and how nondeterministic AI systems require continuous sampling protocols.

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AI startups fail because founders obsess over models, not company building. Harrison Miller is a former VP/GM from Amazon.com’s early years, and former MD of Summit Partners, which over 40+ years has invested $40B in more than 550 tech companies.

He explains why execution, not algorithms, determines survival.

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Tom Chavez, Founding General Partner at super{set}, in conversation with his brother - R. Martin Chavez, Partner and Vice Chairman, Sixth Street, Board Member at Google, and former CFO of Goldman Sachs.

Tom and Marty discuss their brief stint as roommates, their brotherly relationship, and R. Martin's experiences as an investor, entrepreneur, and corporate leader. Listen for insights on startups, leadership, investing, artificial intelligence, ethical technology, and being part of the early LGBTQ+ community on Wall Street.

Listen to The Brothers Chavez in Conversation!

Watch the full conversation here.

***

Listen (or watch) all episodes of The {Closed} Session at www.theclosedsession.com

super{set} is a startup studio where great data+AI ideas become transformational software companies. With our people-first performance culture and company-building playbooks, we found, fund, and scale high-potential businesses.

Learn more about super{set} - including co-founding with us and open roles across our portfolio of companies - at

www.superset.com

Learn more about our VECTOR program - a 12-week fully-paid launchpad for technical product leaders to receive direction, build magnitude, and co-explore company creation alongside super{set} - at superset.com/vector

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super{set} Celebrates First Exit: LiveRamp to Acquire Data Collaboration Software Startup Habu for $200M!

Joining Tom and Vivek in the studio today are Habu co-founders Matt Kilmartin (CEO) and Mike Moreau (COO) to give the full story behind how Habu was conceived, built out, scaled, and sold.

Habu is a leader in the data collaboration category with innovative data clean room technology. Habu enables companies to share, make sense of, and act on insights on decentralized data without compromising privacy or data ownership – enabling companies to realize the full value of their data regardless of where it resides. In January 2024, Habu entered a definitive agreement to be acquired by LiveRamp for $200 million in a highly strategic transaction.

But Habu wasn't a category leader and a $200 million company from day one. Matt, Mike, Tom and Vivek started selling before even slinging code, bringing together a kick-ass team in the beginning that saw the company through pivots to growth. Early customers like Pepsi and Disney played a crucial role in co-innovating with Habu as design partners. And Matt and Mike developed a rapport as leaders and co-founders to power the company through to exit. Learn how Habu became super{set}'s first win in the latest episode of The {Closed} Session!

Learn more about the Habu exit here: https://www.superset.com/feed/super-set-celebrates-first-exit-liveramp-acquires-data-collaboration-software-startup-habu

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