Software Engineering Radio is a podcast targeted at the professional software developer. The goal is to be a lasting educational resource, not a newscast. SE Radio covers all topics software engineering. Episodes are either tutorials on a specific topic, or an interview with a well-known character from the software engineering world. All SE Radio episodes are original content — we do not record conferences or talks given in other venues. SE Radio is brought to you by the IEEE Computer Society and IEEE Software magazine.
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August 19, 2026Episode 73442 min
SE Radio 734: Sathiesh Veera on Engineering Data-Protection Guardrails with LLMs
Sathiesh Veera , a GenAI Solutions Architect at At&T, speaks with host Brijesh Ammanath about the data-protection guardrails required when using LLMs. The core issue is that LLMs sit outside the cloud tenant in most enterprise AI deployments, which means that data leaves the company's perimeter with every prompt, RAG retrieval, and tool call. Contractual agreements can restrict the data that LLM vendors are allowed to use for training and audits, but they don't stop prompt injection or unintended exposure as company data is often shared to LLMs via natural language queries, APIs, tool and function calls, and MCPs. Sathiesh discusses ways to employ security measures and data filtering at each layer to conform to data security policies and protect the data.
August 13, 2026Episode 7331 hr 0 min
SE Radio 733: Max Corbridge on Securing AI Agents
Max Corbridge, an ethical hacker and red teamer who is co-founder and CEO of Secure Agentics, speaks with SE Radio host Amey Ambade about how AI agents get attacked and what engineers can actually do to defend them. Drawing on years of offensive security work, Corbridge frames agents as a new and largely undefended attack surface: the industry has handed AI systems autonomy and the ability to act in the real world while carrying forward prompt injection, a flaw the frontier labs themselves describe as effectively unsolvable. He likens the moment to the early, lawless days of the web, when SQL injection was everywhere and adoption ran far ahead of security. The conversation builds from first principles as Corbridge explains what separates an agent from ordinary software and why three properties make them hard to secure: they are non-deterministic, their language-model core can be coerced, and they are increasingly interconnected through MCP servers, other agents, databases, and email. Turning to the attack surface, Corbridge lays out his "lethal trifecta" (a vulnerable core, dense interconnection, and security tooling that has not caught up) and contrasts the decades of layered defenses protecting an ordinary email inbox with the thin protection around agents that take autonomous actions on critical systems. The heart of the episode is defense. Corbridge orders practices by leverage: least-privilege access and privilege separation, sandboxing where feasible, imperfect-but-useful guardrails as one layer of defense in depth, and human-in-the-loop for irreversible actions (which he notes is contentious and does not scale). The discussion closes on detecting a compromised or drifting agent, the value of watching an agent's chain-of-thought reasoning alongside its actions, the open-source tooling landscape (including Corbridge's own project, Adrian), and his central advice: build security in proactively, define what good agent behavior looks like up front, and avoid bolting it on after agents have already spread across the business.
August 5, 2026Episode 73257 min
SE Radio 732: Jason Gorman on The Effective Use of AI For Software Development
Jason Gorman , a software development expert and founder of Codemanship, joins host Giovanni Asproni to explore how best to use AI in software development. They start by considering how established technical practices — test-driven development, modularization, continuous integration, and continuous reviews — become more important, not less, when working with AI assistance. These practices help address several key limitations of LLMs, including keeping context windows as small as possible. Looking at AI's impact on team productivity, Jason offers some practical advice for teams to introduce AI tools into their workflows. The episode also explores spec-driven development, agentic programming, and the importance of writing readable, understandable code — even when it's AI-generated. Finally, Jason and Giovanni look at emerging research into the cognitive downsides of over-reliance on AI, and what developers can do about it.
July 29, 2026Episode 73150 min
SE Radio 731: Sonali Varde on AI and the Engineering Manager Role
Sonali Varde , Senior Software Engineering Manager at LinkedIn, joins host Kanchan Shringi to discuss how AI is changing the role of the engineering manager. They explore how AI is showing up in day-to-day management work, including operational reviews, planning, communication, workflow automation, and preparation for leadership discussions. The conversation looks at how engineering teams are adopting AI tools and agents, what kinds of skills and practices are becoming more important, and how managers can think about context, review, testing, and operational rigor as AI-assisted development becomes more common. They also discuss how AI affects coaching, performance conversations, hiring, onboarding, team composition, and collaboration with peers and leadership. The episode considers both the opportunities and limits of AI for engineering management, with attention to human judgment, curiosity, ownership, and the continuing importance of technical and organizational understanding.
July 22, 2026Episode 73054 min
SE Radio 730: Birgitta Boeckeler on Harness Engineering for AI Agents
Birgitta Boeckeler, a Distinguished Engineer and consultant focused on AI-assisted software delivery at Thoughtworks , joins host Priyanka Raghavan for a deep dive into harnesses for AI agents. The episode begins by unpacking the concept of harnesses and harness engineering before exploring the core building blocks — guides and sensors — that help AI agents operate more reliably in engineering environments. Priyanka and Birgitta discuss practical implementations of harnesses in real-world workflows, including the use of guides with .MD files and sensors with tools such as SonarQube and Semgrep, which steer agent behavior. The episode also explores how harnesses integrate with existing CI/CD pipelines and pull-request processes. Birgitta describes how stronger harnesses can improve trust in AI-generated code, while emphasizing that harnesses themselves require continuous maintenance as underlying foundation models evolve. The episode concludes with a thoughtful discussion on accountability between humans and agents, along with future directions for harness engineering and AI-assisted software development.
July 15, 2026Episode 72948 min
SE Radio 729: Garth Mollett on AI Supply Chain Security
Garth Mollet , Senior Principal Product Security Engineer and Technical Advisor for Product Security at Red Hat, joins host Robert Blumen for a discussion of AI supply chain security. They start with the basics of supply chain security, including the key components of the AI supply chain, and how it differs from the conventional software supply chain. Garth discusses whether the attacks target model weights or inference, and describes the most common attacks and what's in it for the attacker, whether exfiltration, credentials, sabotage, or resources. The episode also considers SPIFFE, SPIRE, attestation, workload identity, and whether AI has the equivalent of "reproducible builds." Brought to you by IEEE Computer Society and IEEE Software magazine.
July 8, 2026Episode 7281 hr 8 min
SE Radio 728: Clare Liguori on AWS Strands SDK for AI Agents
Clare Liguori , a Senior Principal Engineer who works on developer tooling and agentic AI at Amazon Web Services, speaks with host Sri Panyam about the Amazon Strands Agents SDK. This episode explores the philosophy, design decisions, and emerging patterns behind building production-grade AI agents. Clare frames any agent as three core components: a model, a set of tools, and a prompt. During this interview, she describes the origin story of Strands, the model-driven approach vs. workflows and custom orchestration, steering hooks, tools and MCP, sub-agents and multi-agents, memory layers, production readiness, testing and evaluation starting with use cases where trajectories can be evaluated deterministically, and anti-patterns for newcomers. She describes what's next for Strands, and offers some closing advice for getting results from working with agents
July 2, 2026Episode 7251 hr 2 min
SE Radio 727: Jeroen Janssens and Thijs Nieuwdorp on Using Polars
Jeroen Janssens , Head of Developer Relations at Posit, and Thijs Nieuwdorp , a developer relations engineer at Polars, speak with host Gregory M. Kapfhammer about Polars, a Python package for transforming, analyzing, and visualizing data. After discussing the key features, they explore the implementation and use of the expressions data type provided by Polars. Along with comparing Polars to other data-manipulation packages like Pandas, they also share best practices for performing data analysis in Python with Polars. Jeroen, Thijs, and Gregory also discuss topics such as how to interface Polars with a SQL database.
June 24, 2026Episode 72652 min
SE Radio 726: Scott Kingsley on the Swagger Ecosystem
Scott Kingsley, a VP of Engineering at SmartBear, speaks with host Gregory Kapfhammer about the Swagger ecosystem. They discuss the user interface, editor, and Swagger CodeGen and how these tools support the creation and documentation of OpenAPI-compatible APIs. Scott describes how Swagger fits into frameworks like FastAPI, as well as how Swagger APIs can be exposed through the Model Context Protocol (MCP). The discussion closes with best practices for designing and testing APIs and the role that APIs play in a landscape in which AI agents are building and interacting with APIs.
June 18, 2026Episode 72554 min
SE Radio 725: Danny Yang and Sam Goldman on the Pyrefly Type Checker
Danny Yang and Sam Goldman, both Software Engineers at Meta, speak with host Gregory M. Kapfhammer about the Rust-based Pyrefly type checker for Python. After a look at the foundational concepts for annotating and checking types for Python programs, Danny and Sam present a deep dive of the implementation of Pyrefly. While comparing and contrasting against various type checkers, they also describe how Pyrefly implements the language server protocol (LSP) for Python. The episode explores a range of other topics, including how to balance the features, performance, and language integrations of a type checker.
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