In this episode, in association with the ACM ByteCast, Scott talks with Eric Allman, one of the foundational figures of the early internet. Best known for creating Sendmail, the mail transfer agent that powered a large portion of global email infrastructure through the formative years of the network, Allman helped shape how messages move across the internet. Their conversation explores the origins of internet email, the messy realities of building software that must operate at planetary scale, and what lessons today’s engineers can learn from the systems and design decisions that quietly underpin modern computing.

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Building the Internet with sendmail's Eric Allman

Scott Hanselman sits down with Allen Stewart, Partner Director of Software Engineering at Microsoft, to explore how AI agents with persistent memory are transforming scientific research and software engineering. Allen explains how his team built an AI system that learns from every investigation turning a 12-day autonomous drug discovery run into reusable knowledge that makes future research exponentially faster. Instead of starting from scratch each time, the AI inherits hypotheses, methodologies, and findings from previous work, saving hundreds of millions of tokens and weeks of effort.

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A cognition engine for science with Allen Stewart

In this episode, in association with the ACM ByteCast, Scott talks with Eric Allman, one of the foundational figures of the early internet. Best known for creating Sendmail, the mail transfer agent that powered a large portion of global email infrastructure through the formative years of the network, Allman helped shape how messages move across the internet. Their conversation explores the origins of internet email, the messy realities of building software that must operate at planetary scale, and what lessons today’s engineers can learn from the systems and design decisions that quietly underpin modern computing.

In this episode, Scott talks with Don Syme about the emerging world of agentic developer workflows and what it means when coding tools move from autocomplete helpers to collaborators. They explore how modern tools like GitHub Copilot and GitHub Agentic Workflows are evolving into systems that can plan, execute, and iterate on tasks across a codebase, and what that means for software design, type systems, and developer responsibility.

https://github.github.com/gh-aw/

Agentic Workflows with Don Syme

This week on the show, Scott talks to Philip Kiley about his new book, Inference Engineering. Inference Engineering is your guide to becoming an expert in inference. It contains everything that Philip has learned in four years of working at Baseten. This book is based on the hundreds of thousands of words of documentation, blogs, and talks he's written on inference; interviews with dozens of experts from our engineering team; and countless conversations with customers and builders around the world.

https://www.baseten.co/inference-engineering/

Check out https://textcontrol.com for document editing, reporting, and PDF processing SDKs for .NET

Inference Engineering with Baseten's Philip Kiely Inference Engineering with Baseten's Philip Kiely

Scott Hanselman sits down with Allen Stewart, Partner Director of Software Engineering at Microsoft, to explore how AI agents with persistent memory are transforming scientific research and software engineering. Allen explains how his team built an AI system that learns from every investigation turning a 12-day autonomous drug discovery run into reusable knowledge that makes future research exponentially faster. Instead of starting from scratch each time, the AI inherits hypotheses, methodologies, and findings from previous work, saving hundreds of millions of tokens and weeks of effort. 

In this episode, Scott talks with Don Syme about the emerging world of agentic developer workflows and what it means when coding tools move from autocomplete helpers to collaborators. They explore how modern tools like GitHub Copilot and GitHub Agentic Workflows are evolving into systems that can plan, execute, and iterate on tasks across a codebase, and what that means for software design, type systems, and developer responsibility. 

https://github.github.com/gh-aw/

What does it take to design a programming language from scratch when the target isn’t just CPUs, but GPUs, accelerators, and the entire AI stack? In this episode, I sit down with legendary language architect Chris Lattner to talk about Mojo — his ambitious attempt to rethink systems programming for the machine learning era.

We trace the arc from LLVM and Clang to Swift and now Mojo, unpacking the lessons Chris has carried forward into this new language. Mojo aims to combine Python’s ergonomics with C-level performance, but the real story is deeper: memory ownership, heterogeneous compute, compile-time metaprogramming, and giving developers precise control over how AI workloads hit silicon.

Chris shares the motivation behind Modular, why today’s AI infrastructure demands new abstractions, and how Mojo fits into a rapidly evolving ecosystem of ML frameworks and hardware backends. We also dig into developer experience, safety vs performance tradeoffs, and what it means to build a language that spans research notebooks all the way down to kernel-level execution.

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That's good Mojo - Creating a Programming Language for an AI world with Chris Lattner

AI is making developers dramatically more productive...so why is everyone so exhausted? In this episode, Scott talks with Steve Yegge, legendary blogger and creator of Gas Town, a multi-agent orchestrator he describes as "Kubernetes for coding agents." Steve shares his theory of the "AI Vampire," that working alongside AI drains human energy Colin Robinson-style (What We Do In The Shadows), even as output skyrockets. They dig into what happens when you're managing ten or twenty Claude Code instances at once, who actually captures the value of a 10x productivity boost, and why the most important thing developers can do right now might be to close the laptop and go for a walk.

The AI Vampire with Gas Town's Steve Yegge

This week on the show, Scott talks to Philip Kiley about his new book, Inference Engineering. Inference Engineering is your guide to becoming an expert in inference. It contains everything that Philip has learned in four years of working at Baseten. This book is based on the hundreds of thousands of words of documentation, blogs, and talks he's written on inference; interviews with dozens of experts from our engineering team; and countless conversations with customers and builders around the world.

 * https://www.baseten.co/inference-engineering/

Inference Engineering with Baseten's Philip Kiely

Hanselminutes is Fresh Air for Developers. A weekly commute-time podcast that promotes fresh technology and fresh voices. Talk and Tech for Developers, Life-long Learners, and Technologists.

Scott Hanselman

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