The AI Collective
23 episodes listed below
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The Collective Intelligence Community Podcast takes the same great discussions we have at each of our events and makes them available for all! Curated for the community by the community, we are bringing the brightest minds in generative AI to the table to discuss the field’s hottest topics and more. Join us in this special opportunity to peek into the minds of the founders, funders, and thought leaders shaping the generative AI revolution as we answer your most pressing questions.
Based on 6 episodes we listened to · September 2026
Founder and investor interviews turn AI product strategy, model training and software development choices into practical, intelligible conversations.
Collective Intelligence Community Podcast builds its interviews around the decisions AI companies face when turning models into products. The host moves comfortably between company strategy and technical practice, asking Bain Capital Ventures partner Slater Stich about the…
A website in 20 seconds sounds nice; Thomas asks what you'd charge for it.
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Short reviews from the PlayNext desk, based on the episodes we processed.
Cloud browsers are presented as infrastructure, and the scaling challenge lands clearly.
The episode frames headless browsers as cloud infrastructure, with Paul laying out how BrowserBase handles the hard work of running browsers on servers at scale for hundreds of AI and non-AI companies.
Postgres is framed as the practical core for AI systems that still need joins, filters, and access control.
The episode makes a focused case for Postgres as the backbone for RAG, semantic search, and AI agents. Timescale's AI lead frames the appeal in practical terms: keep permissions, business data, filters, and joins in one place, and the system stays easier to reason about.
A measured look at where the modern data stack may go next.
The episode uses Slater Stitch, a partner at Bain Capital Ventures, to ask what happens after the first wave of modern data stack enthusiasm starts to fade.
A practical look at how smaller models can outperform larger ones on the right task.
David Corbitt treats reinforcement learning as a product decision, asking when a smaller model becomes the better choice because it is cheaper, faster, or stronger on a specific task.
A Jasper AI conversation that moves from product pitch to harder questions about creative work, authorship, and value.
The episode treats Jasper AI less like a novelty and more like a working tool, with Shane Orlick framing it as something that can help with writer's block and push new ideas forward.
A practical take on exits, speech AI, and the work of buying data.
Ofer Ronen moves from early startup inspiration to exits with two companies, then through Google, IAC, Tomato AI, and contact center AI. The strongest material stays grounded: specialized industry models can shift where the bottleneck sits, language can work as an instruction…
A practical look at the tooling layer behind shipping production LLM apps.
Akash Sharma, co-founder and CEO of Vellum, presents the company as infrastructure for getting LLM apps into production. The discussion stays on the work that matters once the demo is over: orchestration, evals, monitoring, and comparing models on quality, cost, and latency.
A practical look at scaling, ownership, and how a fast company stays coordinated.
Henry Shi traces a familiar founder arc, from Junior Achievement and a gift bag basket company to super.com, which he says reached a billion dollars in annual sales.
Markets, macro, AI, and crypto in motion.
Pritika Mehta, co-founder of Butternut AI, says the platform can build websites and apps in under 20 seconds from prompts.
David explains what OpenPipe is trying to build.
Shane Orlick joins host Thomas Josh for a conversation about Jasper and the promise of AI as a creative partner.
Akash presents Vellum as tooling for teams shipping LLM products.
Bain Capital Ventures partner Slater Stitch discusses the evolution of the modern data stack, AI infrastructure challenges, and strategic frameworks for startups navigating rapid technological change.
The host asks what Timescale is and what the Timescale AI lead does there.
Paul starts with the browser layer.
Prasanna from Machinify joins Collective Intelligence to talk through his background and the ideas shaping his approach at Machinify.
Collective Intelligence opens its first in-person recording with a wine tasting.
Collective Intelligence opens by asking Ofer from Tomato AI about the path that brought him here.
Quinn Slack traces his path from open source work on Chromium, OpenSSL, and Curl to Sourcegraph.
Henry talks through how early exposure to entrepreneurship shaped the way he builds.