Should American companies be worried about Chinese open-source AI models?

Lin Qiao, CEO of Fireworks, doesn't think so.

In this episode, she joins Lukas Biewald to talk about why she believes the industry is at a turning point, one that calls for more open intelligence, not less.

They cover how Fireworks now processes more tokens a day than OpenAI's API, why she thinks the future belongs to specialized models built on private company data rather than general-purpose ones, and why she believes OpenAI and Anthropic should be open-sourcing their own models too.

Connect with us here:

• Lin Qiao
• Fireworks
• Lukas Biewald
• Weights and Biases

"We are going to switch from the problem in AI being that nothing works to the problem being that everything works."

Dan Klein has been studying language models for over two decades and is now a professor of computer science at Berkeley. His new company, Scaled Cognition, is built around one question: how do you build a system that will not lie to you?

In this episode, Dan joins Lukas Biewald to talk about why every LLM output is technically a hallucination, how reinforcement learning can quietly teach AI to deceive you, and what it actually takes to build models that check their own work.

He also gets into why reliability is the one part of AI that hasn't kept pace and why that matters more than most people realize.

Connect with us here:

• Dan Klein
• Scaled Cognition
• Lukas Biewald
• Weights and Biases

Samuel Rodriques left physics because there were no unsolved problems left.

Instead, he built an AI scientist named Kosmos to cure every disease, solve aging, and map the human brain.

In this episode:

• The cure his AI proposed for blindness
• Why he would never touch a peptide
• Whether we'll need human scientists in 20 years
• What's stopping America in drug discovery

Connect with us here:

• Samuel Rodriques
• Edison Scientific
• Lukas Biewald
• Weights & Biases

"Every vehicle is capable of driverless operation. That's clearly the steady state of where we're going."

Wayve started in a rented house in Cambridge with $1.5M, a car in the garage, and an aim to integrate end-to-end AI into driving. A decade later it's driven across 506 cities without a single HD map and is worth over $8.6 billion.

In this episode, CEO Alex Kendall joins Lukas Biewald to talk about how he built the AI driver Uber, Nvidia, Mercedes, and Nissan all backed, and why putting self-driving AI into 100 million cars a year is a far bigger bet than 10,000 robotaxis.

Waymo and Tesla both come up. He doesn't shy away.

Connect with us here:

• Alex Kendall
• Lukas Biewald
• Wayve
• Weights and Biases

"Companies designing for agents, not humans, are going to get a lot of lift."

ClickHouse started as an internal tool at Yandex. Today it's the database Anthropic, OpenAI, Meta and Tesla all run on.

In this episode, CEO Aaron Katz joins Lukas Biewald to talk about how he turned an open source project into a $15B company, why he acquired LangFuse knowing it could cost him customers, and what he's actually building for the agent era.

Snowflake, Datadog and Databricks all come up. He doesn't shy away.

Connect with us here:

Aaron Katz: https://www.linkedin.com/in/aaron-katz-5762094

ClickHouse: https://www.linkedin.com/company/clickhouseinc/

Lukas Biewald: https://www.linkedin.com/in/lbiewald/

Weights and Biases: https://www.linkedin.com/company/wandb/

00:00 Trailer

00:57 The Origin Story: From Yandex to ClickHouse Inc.

04:43 Building ClickHouse Cloud & Raising $300M

10:36 Growing Up Around Xerox PARC

12:51 Salesforce, Mark Benioff & the Dot-Com Bust

15:32 Cloud Skeptics vs. AI Skeptics | History Repeating

18:05 Building a Modern Go-To-Market Playbook

21:57 The SaaS Crash, Agents & the Future of Infrastructure

27:09 The Datadog Love-Hate Story

35:21 Hardest Moments: Russia, SVB & Sleepless Nights

43:16 Outro

Formal verification already consumes years of human effort.

In this episode, Lukas Biewald talks with Carina Hong, Founder & CEO of Axiom, about why verification is becoming the real bottleneck in high stakes AI systems.

They discuss how Axiom uses AI to take on the tedious checking that stretches verification cycles across years, starting with formal mathematics and extending to hardware and software.

Carina also explains why Axiom’s approach to auto-formalization mirrors spec driven models like Kiro from AWS.

Connect with us here:

Carina Hong: https://www.linkedin.com/in/carina-hong/

Axiom: https://www.linkedin.com/company/axiommath/

Lukas Biewald: https://www.linkedin.com/in/lbiewald/

Weights & Biases: https://www.linkedin.com/company/wandb/

“I don't worry about being replaced by AI. I worry about being replaced by someone who's really good at using AI.”

Atlassian has 10,000+ engineers currently split-testing the world’s top AI coding tools, from GitHub Copilot and Cursor to Claude Code.

In this episode, Co-Founder & CEO Mike Cannon-Brookes joins Lukas Biewald to share what their data reveals about the world's best AI tools today.

Hear how 24 years of building a tech giant and a massive internal study on AI productivity have shaped Mike's vision for the future of dev jobs.

Connect with us here:

Mike Cannon-Brookes: https://www.linkedin.com/in/mcannonbrookes/?originalSubdomain=au

Atlassian: https://www.linkedin.com/company/atlassian/?viewAsMember=true

Lukas Biewald: https://www.linkedin.com/in/lbiewald/

Weights & Biases: https://www.linkedin.com/company/wandb/

00:00 Trailer

01:08 Introduction

03:11 Connecting Technology and Business Teams

07:22 The Impact of AI on Business Workflows

13:26 Developer Productivity and AI

21:03 Measuring Developer Efficiency

25:41 Future of AI in Development

34:59 Legacy Technology and Code Changes

39:29 AI's Role in Developer Productivity

47:40 AI and Junior Developers

52:30 Product-Led Growth and Business Strategy

01:00:29 Core Metrics for Sustainable Growth

01:06:56 Staying Creative in the Tech Industry

The future of AI training is shaped by one constraint: keeping GPUs fed.

In this episode, Lukas Biewald talks with CoreWeave SVP Corey Sanders about why general-purpose clouds start to break down under large-scale AI workloads.

According to Corey, the industry is shifting toward a "Neo Cloud" model to handle the unique demands of modern models.

They dive into the hardware and software stack required to maximize GPU utilization and achieve high goodput.

Corey’s conclusion is clear: AI demands specialization.

Connect with us here:

Corey Sanders: https://www.linkedin.com/in/corey-sanders-842b72/

CoreWeave: https://www.linkedin.com/company/coreweave/

Lukas Biewald: https://www.linkedin.com/in/lbiewald/

Weights & Biases: https://www.linkedin.com/company/wandb/

(00:00) Trailer

(00:57) Introduction

(02:51) The Evolution of AI Workloads

(06:22) Core Weave's Technological Innovations

(13:58) Customer Engagement and Future Prospects

(28:49) Comparing Cloud Approaches

(33:50) Balancing Executive Roles and Hands-On Projects

(46:44) Product Development and Customer Feedback