Jacob Visovatti and Conner Goodrum of Deepgram speak with host Kanchan Shringi about testing ML models for enterprise use and why it's critical for product reliability and quality. They discuss the challenges of testing machine learning models in enterprise environments, especially in foundational AI contexts. The conversation particularly highlights the differences in testing needs between companies that build ML models from scratch and those that rely on existing infrastructure. Jacob and Conner describe how testing is more complex in ML systems due to unstructured inputs, varied data distribution, and real-time use cases, in contrast to traditional software testing frameworks such as the testing pyramid.

To address the difficulty of ensuring LLM quality, they advocate for iterative feedback loops, robust observability, and production-like testing environments. Both guests underscore that testing and quality assurance are interdisciplinary efforts that involve data scientists, ML engineers, software engineers, and product managers. Finally, this episode touches on the importance of synthetic data generation, fuzz testing, automated retraining pipelines, and responsible model deployment—especially when handling sensitive or regulated enterprise data.

Brought to you by IEEE Computer Society and IEEE Software magazine.

Samuel Colvin, the CEO and founder of Pydantic, speaks with host Gregory M. Kapfhammer about the ecosystem of Pydantic’s Python frameworks, including Pydantic, Pydantic AI, and Pydantic Logfire.

Along with discussing the design, implementation, and use of these frameworks, they dive into the refactoring of Pydantic and the follow-on performance improvements. They also explore ways in which Python programmers can use these three frameworks to build, test, evaluate, and monitor their own applications that interact with both local and cloud-based large language models.

Brought to you by IEEE Computer Society and IEEE Software magazine.

Brian Demers, Developer Advocate at Gradle, speaks with host Giovanni Asproni about the importance of having observability in the toolchain. Such information about build times, compiler warnings, test executions, and any other system used to build the production code can help to reduce defects, increase productivity, and improve the developer experience. During the conversation they touch upon what is possible with today’s tools; the impact on productivity and developer experience; and the impact, both in terms of risks and opportunities, introduced by the use of artificial intelligence.

Brought to you by IEEE Computer Society and IEEE Software magazine.

Vilhelm von Ehrenheim, co-founder and chief AI officer of QA.tech, speaks with SE Radio's Brijesh Ammanath about autonomous testing.

The discussion starts by covering the fundamentals, and how testing has evolved from manual to automated to now autonomous. Vilhelm then deep dives into the details of autonomous testing and the role of agents in autonomous testing.

They consider the challenges in adopting autonomous testing, and Wilhelm describes the experiences of some clients who have made the transition. Toward the end of the show, Vilhelm describes the impact of autonomous testing on the traditional QA career and what test professionals can do to upskill.

This episode is sponsored by Fly.io.

In this episode of Software Engineering Radio, Abhinav Kimothi sits down with host Priyanka Raghavan to explore retrieval-augmented generation (RAG), drawing insights from Abhinav's book, A Simple Guide to Retrieval-Augmented Generation.

The conversation begins with an introduction to key concepts, including large language models (LLMs), context windows, RAG, hallucinations, and real-world use cases. They then delve into the essential components and design considerations for building a RAG-enabled system, covering topics such as retrievers, prompt augmentation, indexing pipelines, retrieval strategies, and the generation process.

The discussion also touches on critical aspects like data chunking and the distinctions between open-source and pre-trained models. The episode concludes with a forward-looking perspective on the future of RAG and its evolving role in the industry.

Brought to you by IEEE Computer Society and IEEE Software magazine.

Luca Palmieri, author of Zero to Production in Rust and Principal Engineering Consultant at MainMatter, speaks with SE Radio host Gavin Henry about Rust in production.

They discuss what production Rust means, how to get Rust code into production, specific Rust issues to think about when getting an application into production, what Rust profiles are, expected performance, telemetry options, error handling and what parts of Rust to use and avoid.

Palmieri discusses docker containers, tracing, robust Rust error handling, how performant Rust is in the real world, p50, p99, docker build techniques, project layouts, crates, speeding up Rust build times, unwrap(), panics, budgeting resources, inner development loops, the Facade Pattern, structured logging, and how to always use clippy.

Brought to you by IEEE Computer Society and IEEE Software magazine.

Will McGugan, the CEO and founder of Textualize, speaks with host Gregory M. Kapfhammer about how to use packages such as Rich and Textual to build text-based user interfaces (TUIs) and command-line interfaces (CLIs) in Python. Along with discussing the design idioms that enable developers to create TUIs in Python, they consider practical strategies for efficiently rendering the components of a TUI. They also explore the subtle idiosyncrasies of implementing performant TUI frameworks like Textual and Rich and introduce the steps that developers would take to create their own CLI or TUI.

This episode is sponsored by Fly.io.

In this episode, SE Radio host Sriram Panyam explores HTMX with its creator, Carson Gross, who is also creator of Hyperscript, the mind behind the Grug Brained Developer, a professor of software engineering at Montana State University, and co-author of Hypermedia Systems.

HTMX is a modern JavaScript library that allows developers to access AJAX, WebSockets, CSS Transitions, and Server-Sent Events directly in HTML using attributes. It represents a return to hypermedia-driven application architecture while supporting modern user experiences. The episode starts with a look at the current complexity in web development and how HTMX offers an alternative approach. Carson explains the core philosophy of "HTML as the interface" and how hypermedia principles influenced HTMX's design. From there, they dive into HTMX's technical concepts, including its attribute system, server-side integration, event handling, and state management approach.

Carson shares some real-world implementation strategies, including migration paths from JavaScript frameworks, architectural patterns, and performance considerations -- as well as a few scenarios in which HTMX might not be the best fit. Finally, they look at the growing HTMX ecosystem, community contributions, and future development roadmap. Throughout the episode, Carson provides concrete examples and case studies of HTMX in production environments.

Brought to you by IEEE Computer Society and IEEE Software magazine.