Benny Chen is the cofounder of Fireworks AI, an AI infrastructure platform. They have raised $327M in funding from Benchmark, Sequoia, Lightspeed, Index, and others.

Benny's favorite book: Principles (Author: Ray Dalio)

(00:01) Intro and why AI infrastructure is having a moment
(00:06) Training vs inference: what’s working and where the real bottlenecks are
(01:25) Why inference is the hard problem in production
(03:30) What breaks at scale when AI systems hit real users
(05:29) GPUs, hardware constraints, and why power is now a first-class concern
(06:02) What you’re actually paying for in inference
(07:21) Reliability, compliance, and enterprise expectations
(09:49) Training and inference capacity: when they blur together
(11:06) How to make inference fast in practice
(13:06) System design choices behind modern inference platforms
(15:28) Inference economics and cost tradeoffs
(18:02) When fine-tuning actually makes sense
(21:58) What “best model” really means for real companies
(24:25) Production LLM architectures that actually work
(27:46) Building an AI infra company customers can trust
(29:27) Shipping fast without breaking reliability
(31:14) Go-to-market lessons for infra startups
(34:17) Where inference platforms are heading next
(36:32) Rapid fire round

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Where to find Benny Chen:

LinkedIn: https://www.linkedin.com/in/benny-yufei-chen-2238575a/

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Where to find Prateek Joshi:

Website: https://prateekj.com
Research Column: https://www.infrastartups.com
LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite
X: https://x.com/prateekj

Surojit Chatterjee is CEO of Ema, an agent platform build AI employees. They have raised $61M in funding from Accel, Section 32, and others. Before Ema, he was the chief product officer at Coinbase. And before that, a VP at Google.

Surojit's favorite book: Man's Search for Meaning (Author: Viktor Frankl)

(00:01) Welcome
(00:07) Defining the “AI Employee”
(02:23) Lessons from Google: Building for Scale
(06:59) Coinbase CPO: Hypergrowth & Product Leadership
(09:24) Market Framing: Why “AI Employee” vs Copilot
(14:29) Platform Building Blocks (Agents, Orchestrator, Fusion, Governance)
(19:26) Trust, Security, and On-Prem Deployment
(23:11) Model of Models: How Fusion Picks & Combines LLMs
(29:10) What Infra Is Still Missing (Eval at Scale, Speed)
(32:10) Rapid Fire Round

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Where to find Surojit Chatterjee:

LinkedIn: https://www.linkedin.com/in/surojitchatterjee/

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Where to find Prateek Joshi:

Website: https://prateekj.com
Research Column: https://www.infrastartups.com
LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite
X: https://x.com/prateekj

Rishi Bhargava is CEO of Descope, an identity management platform for customers and AI agents. They've raised $88M in funding from investors such as Notable Capital, Lightspeed, Unusual Ventures. The two previous he founded were acquired by Palo Alto Networks and McAfee.

(00:01) Introduction
(00:08) Origin story: why identity and passwords needed a rethink
(02:59) Passwords vs passkeys explained in plain English
(05:06) Why logging in is still painful (and why passwords persist)
(09:06) Account takeovers explained: how hacks actually happen
(11:59) Building security products: philosophy vs regular software
(14:24) The ideal login experience: from frustration to seamless access
(16:40) What is an AI agent? Defining agent identity simply
(21:54) Good bots vs bad bots: trust, access, and control in an agent world
(25:03) Breaches and blast radius: security before vs after Descope
(27:55) Company building lessons from Demisto to Descope
(30:15) AI trends that matter most for enterprise products
(32:40) Rapid Fire Round

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Where to find Rishi Bhargava:

LinkedIn: https://www.linkedin.com/in/bhargavarishi/

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Where to find Prateek Joshi:

Website: https://prateekj.com
Research Column: https://www.infrastartups.com
LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite
X: https://x.com/prateekj