Summary

In this conversation, the founders of Bauplan, Jacopo and Ciro, share their extensive backgrounds in AI and data infrastructure, discussing the evolution of NLP and the challenges faced in the industry. They highlight the importance of data pipelines in AI effectiveness and the complexities of building data infrastructure.

The discussion also covers lessons learned from previous ventures, the shifting dynamics of the AI market, and the need for collaboration between data scientists and engineers. They emphasize the significance of simplicity in data tools and the future of data management focusing on standardization and accessibility.

In this episode

• Bauplan was founded by experienced professionals in AI and data.
• Data challenges remain significant despite advancements in AI.
• Lessons from previous ventures inform current strategies.
• Building data infrastructure is complex and requires careful planning.
• Collaboration between data scientists and engineers is essential.
• Data engineering will resemble more and more software engineering.
• Simplicity in data tools can enhance user experience.
• The future of data management will focus on standardization and accessibility.

If you care about making AI features shippable by regular software teams—not just data specialists—this conversation maps the terrain and the trade-offs.

Chapters

00:00 Introduction to Bauplan and Founders' Background
02:27 The Evolution of NLP and AI Challenges
05:05 Shifts in Data and AI Application
07:56 Lessons from Previous Ventures
10:20 The Search Market Landscape
13:05 Behavioral Data's Role in Search
15:52 Building Data Infrastructure vs. Applications
18:22 The Complexity of Data Management
21:03 Bridging the Gap Between Data Science and Engineering
23:39 Challenges in Infrastructure Development
29:52 Navigating the Infrastructure Landscape
32:19 The Pendulum of Centralization and Decentralization
34:00 The Need for Standardization in Data Infrastructure
36:52 Simplifying Data Workflows
40:29 Radical Simplicity in Data Management
45:28 Overcoming Resistance to Change
48:50 The Future of Data Abstractions and Git for Data

Summary

Brett — founder & CEO of Micro — joins Nitay and Kostas to share how he’s turning email into a knowledge graph and rebuilding CRM right inside the inbox. He traces a path from Google’s M&A and Allo product team to Clearbit and Launch House, then digs into why most “inbox zero” workflows fail, how interoperability and AI agents shift power to the interface, and what it takes to design an email experience people actually live in.

What you’ll learn

• Why email is a system of record—and how Micro converts threads into people, companies, attachments, tasks, and “updates”
• The wedge: founders’ real workflows (fundraising, hiring, sales) and why CRM belongs in the inbox
• Product & UX lessons: skeuomorphic first, flexible theming (consumer vs. enterprise), and copy-the-UI-before-evolving-it
• M&A realities from Google: talent vs. tech vs. business acquisitions, and why culture kills most deals
• Burnout and agency: why founders report less burnout than big-company roles
• The next phase: cross-app “updates” (email, LinkedIn DMs, etc.), Salesforce/HubSpot read–write, and agentic automation

Chapters

00:00 Brett's Journey: From Consulting to Tech Innovator

02:41 The Role of Strategy in Tech Companies

05:16 Understanding M&A: Successes and Failures

07:55 The Evolution of AI in Corporate Strategy

10:26 Transitioning to Product Management

13:19 Lessons from Clearbit: Culture and Growth

15:50 The Impact of Burnout on Career Choices

18:15 Finding Fulfillment in Entrepreneurship

21:09 Navigating the B2B Landscape

23:34 The Necessity of Products in a Crisis

33:24 The Unexpected Layoff and New Beginnings

34:39 The Launch House Experience

37:16 Transforming Reality into an Accelerator

39:17 The Evolution of Founders and Content Creation

41:52 Introducing Micro: A New Email Experience

47:02 Extracting Information for Better Workflows

53:49 Integrating with Existing Ecosystems

01:01:16 The Future of Email and AI

Summary

Steve Klabnik has spent the last 15 years shaping how developers write code—from teaching Ruby on Rails to stewarding Rust’s explosive growth. In this wide-ranging conversation, Steve joins Kostas and Nitay to unpack the forces behind Rust’s rise and the blueprint for developer-first tooling.

• From Rails to Rust: How a web-framework luminary fell for a brand-new systems language and helped turn it into today’s go-to for memory-safe, zero-cost abstractions.
• Community as UX: The inside story of Cargo, humane compiler errors, and why welcoming IRC channels can matter more than benchmarks.
• Standards vs. Shipping: What Rust borrowed from the web’s rapid-release model—and why six-week cadences beat three-year committee cycles.
• Three tribes, one language: How dynamic-language devs, functional programmers, and C/C++ veterans each found a home in Rust—and what they contributed in return.
• Looking ahead: Steve’s watch-list of next-gen languages (Hylo, Zig, Odin) and the lessons Rust’s journey holds for anyone building tools, communities, or startups today.

Whether you’re chasing segfault-free code, dreaming up a new PL, or just curious how open-source movements gain momentum, this episode is packed with insight and practical takeaways.

Chapters

00:00 Introduction and Personal Connection
00:59 Journey from Ruby on Rails to Rust
02:21 Early Programming Experiences and Interests
07:20 Community Dynamics in Programming Languages
13:59 The Importance of Community in Open Source
14:37 How Ruby on Rails and Rust Built Their Communities
21:44 Standardization vs. Unified Development Models
30:55 Community Debt in Programming Languages
36:24 Release Cadence vs. Feature Development
37:36 Rust's Unique Selling Proposition
43:30 Attracting Diverse Programming Communities
52:31 The Future of Systems Programming Languages