Most AI 'innovation' is just workflow automation disguised as intelligence. Benjamin Shapiro, founder of I Hear Everything and creator of AI-powered podcast production systems, talks with Tom Chavez about the brutal realities of building defensible AI companies versus riding the hype cycle.

Tom and Ben dissect why proprietary data virtuosity trumps LLM wrappers, how outcome-oriented AI solutions kill traditional left-to-right workflows, and why founders must quintuple their execution speed or face extinction in the compressed imagination-to-execution timeline.

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Most enterprises burn millions on idle GPUs while developers wait weeks for access. Haseeb Budhani, CEO of Rafay Systems, built a global GPU orchestration platform after exits at Soha Systems (acquired by Akamai) and brings deep infrastructure expertise to solving the $100B GPU waste crisis. He reveals why 93% of Fortune 500 companies achieve sub-85% GPU utilization, how sovereign AI requirements are driving hundreds of "Neo clouds" globally, and the specific multi-tenancy frameworks that transform expensive compute from sunk cost into competitive advantage.

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Most operators fail as investors because they can't scale their expertise beyond one-on-one advice calls. Leyla D. Seka, former Salesforce EVP who built the multi-billion dollar AppExchange ecosystem, explains how Operator Collective structures 200+ operators as LPs with carry to systematically deploy operational knowledge across portfolio companies. She reveals why she never invests in founders who think they're going public, how 30-minute operator calls save companies three months of execution time, and why the current AI gold rush mirrors the early cloud adoption cycle at Salesforce.

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Most payment startups treat compliance like a checkbox instead of survival strategy. Richie Serna, CEO of Finix, sold his previous payments company to Stripe and now competes directly against them, winning 60% of head-to-head deals.

In this conversation with Tom Chavez, Richie breaks down why payments requires 95% feature completeness before product-market fit clicks, how to build abstraction layers that prevent vendor lock-in with legacy processors, and why focusing on non-technical power users beats pure developer experience when scaling payment infrastructure.

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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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