Software Engineering Radio - the podcast for professional software developers

Sowjanya Pandruju, Cloud Application Architect with Amazon Web Services, Vice Chair of the IEEE Computer Society Madison Section, and Chair of the IEEE Women in Engineering (WIE) Madison Section (Region 4), speaks with SE Radio host Gavin Henry about managing agent state. Sowjanya discusses what agents are and are not, what agent state is, the role an LLM actually plays, why agents need state, the different types of state, where to store agent state, how multi-agents change things, and the solutions to the various challenges created by managing agent state. Brought to you by IEEE Computer Society and IEEE Software magazine.

Tim Varelmann, the founder of Bluebird Optimization, which helps companies automate complex decision-making, speaks with host Sriram Panyam about mathematical optimization. The episode begins by differentiating optimization from what software engineers usually mean by the word. Making something faster or smaller is improvement, whereas optimization means finding the provably best solution after which no further improvement is possible unless the problem's parameters change. The conversation examines the difference between simulation and optimization, where optimization is already running, optimization and AI, key software engineering principles, and how you can get started with mathematical optimization.

Sahil Walia, a senior technical architect at Snowflake, joins host Robert Blumen for a conversation about schema migration and data migration. Together, they discuss the basics of schema: do all data sets have schema?; what drives schema change?; are data migration and schema migration the same thing? Must they happen at the same time? They then talk about the challenges and failure modes of schema migration, including challenges at scale, migrating without downtime, the concept of "safety" in data migrations, and safety patterns for data migration - double writes, read repair, replication, ending on the Apache Iceberg case study.

Raju Dandigam speaks with host Amey Ambade about building robust AI agents for production. Raju recommends treating an agent as a software subsystem rather than a standalone model call. That means designing decision contracts and tool boundaries, choosing between predictable workflows and multi-agent orchestration, and managing the runtime, state, and streaming that make agents durable. A recurring theme is that the model should not own the system: the right architecture is usually the simplest one that meets the product need while preserving reliability and control, with the language model placed inside a controlled runtime that settles authentication, policy, data freshness, and idempotency before it is ever asked to reason. They focus largely on how teams can be sure that an agent works and how to debug it when it does not. The episode covers behavioral testing against contracts, golden scenarios, and observability that captures the full execution path rather than flat logs, which is the gap behind…

Erin Catto of Kintsugiyama, veteran video game developer who worked on the Tomb Raider series at Crystal Dynamics and later contributed to Diablo III, Overwatch, and other franchises at Blizzard, discusses video game physics engines with host Jason Davey. Erin created the popular open-source Box2D library used in titles including Angry Birds and Noita, and he released Box3D in 2026, bringing the much-loved physics engine to the third dimension. Underpinning everything from platformers and racing games to industrial robotics simulations, modern physics engines present a host of interesting engineering challenges, including the need to balance accuracy, stability, determinism, and performance. Catto describes the core concepts, the various trade-offs and factors that influence the design of these systems, and how they fit into the broader software architecture of a video game.

Milan Milanovic, Microsoft MVP for Developer Technologies and author of the book, Laws of Software Engineering, joins host Giovanni Asproni for a conversation based on the content of his book—a collection of 53 empirical and mathematical laws governing modern software engineering. The book includes some well-known laws, such as Conway's and Brooks's laws, as well as other lesser-known but just as important, including Gilb's and Tesler's laws. The episode starts with an introduction to the laws and the criteria that Milan used to choose them. The episode continues with some practical hints on how to apply the laws and concludes with thoughts on the importance of the laws for teams using artificial intelligence tools in their day-to-day work.

Owen McGirr, creator of SayIt!, Switchify, and an entrepreneur who builds inclusive technology, speaks with SE Radio host Gavin Henry about software accessibility. For this episode, Gavin emailed the questions to Owen, who prepared his answers and generated the audio programmatically using text-to-speech. Owen discusses what accessibility is, different ways a user might interact with software, how accessibility is currently handled between various operating systems, the technical challenges of creating SayIt! and Switchify, plus what developers can do to improve accessibility. This episode explores access methods, what good accessibility means, eye gaze, touch, voice, keyboards, scanning, switches, radaring, screen overlays, iOS accessibility, Android accessibility, which OSes have better support, AI testing, what vendors can do to improve, what developers can do to improve and what two things a developer can do immediately to test their software accessibility.

Sahil Walia, Senior Technical Architect at Snowflake, joins host Robert Blumen for a deep dive into Apache Iceberg. The conversation covers OLAP, data formats, data lakes and lake houses, Iceberg as a data format, columnar storage, use cases, reference implementation, read/write, how Iceberg structures metadata, indexing, query planning and performance issues.

Vivek Yadav, an engineering manager at the payment company Stripe, speaks with host Adi Narayan about building regression testing for microservices. Drawing on his work estimating network costs for card payments, Vivek explains why unit and integration tests fall short when a single transaction's cost can depend on 100+ parameters across card networks, countries, and merchant types. He describes Stripe's approach: structuring services so that core logic is stateless and separated from I/O, then wrapping that logic in an Apache Spark job that replays historical transactions from cold storage to compare old versus new outputs at a granular, per-transaction level. This allows Stripe to validate major migrations with far more confidence and speed than a traditional shadow-rollout, and it now doubles as a tool for assessing network rule changes, debugging incidents, and even showing customers how a pricing change will affect their costs. The episode closes by noting the same pattern applies wherever AI-driven…

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.

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…

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.

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.

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…

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.

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

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.

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.

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.

Jure Leskovec, Professor of Computer Science at Stanford University and Chief Scientist at Kumo.ai, speaks with host Sriram Panyam about relational and graph language models and their transformative impact on enterprise decision-making and predictive modeling. Jure begins by establishing the critical importance of predictive modeling across industries - from fraud detection in financial institutions to customer churn prediction, lifetime value estimation, product recommendations, and healthcare risk assessment. He notes that while AI has made remarkable advances in natural language understanding and computer vision, predictive modeling over enterprise operational data stored in relational databases has been largely left behind, still relying on 30-year-old machine learning approaches that are expensive, time-consuming, and require manual feature engineering. His proposed solution to the fundamental problem with current approaches is relational deep learning and relational transformers. The discussion…

Dave Airlie, a Distinguished Engineer at Red Hat, speaks with host Gregory M. Kapfhammer about Linux kernel maintenance. After over-viewing the scale and structure of the Linux kernel, they dive deep into the review and validation of kernel patches, drawing on examples from the GPU subsystem. After discussing the features and benefits of the Linux kernel's maintenance model, they also explore kernel maintenance best practices and the supporting tools for these practices. Dave and Gregory also discuss topics such as the integration of Rust code in the Linux kernel and the ways in which AI-driven code review are influencing kernel maintenance.

Dwayne McDaniel, developer advocate at GitGuardian.com, joins host Priyanka Raghavan to talk about the engineering challenges of secrets management. They explore what "secrets" really are in modern systems—far beyond passwords—including API keys, tokens, certificates, and machine identities, and how "secret sprawl" emerges across the SDLC. Drawing on reports from GitGuardian and Verizon, they discuss the growing scale of secret leaks and why credential abuse and phishing remain dominant attack vectors. They examine common leak points—from code repos and logs to CI/CD pipelines, containers, and SaaS integrations—and how cloud, DevOps, and AI tooling are amplifying risks. Priyanka quizzes Dwayne about recent supply chain attacks from pyPi and trivy ecosystems, highlighting recurring root causes like poor access control, long-lived credentials, and weak security hygiene. Finally, they consider detection, response, and modern solutions—short-lived credentials, secret scanning, and identity-based approaches like…

In this episode, Rob Moffat, author of Risk-First Software Development and chief technical architect at the FinTech Open Source Software Foundation (FINOS), speaks with host Brijesh Ammanath about how all of software development is actually risk management. Rob introduces the concept of 'risk-first software development,' which sits in the context of existing methodologies like scrum and kanban. Showcasing multiple real-world project patterns to illustrate how things can go wrong when risk is ignored, he makes the case for why risk should be the primary lens behind every development decision, from architecture to prioritization. Through various examples, he shows how every developer action can be viewed as a risk trade-off and why making that explicit can lead to better outcomes. The conversation takes a deep dive into the risk-first framework and how teams can apply it in their existing processes.

Martin Dilger, founder and CEO of Nebuilt GmbH, speaks with host Giovanni Asproni about event sourcing -- a software architecture pattern in which, rather than storing just the current state of your data, you store a sequence of events that represents every change that has ever happened in the system. This episode starts by introducing the vocabulary around event sourcing, highlighting its relationship with event modeling, event streaming, and event storming. Martin describes some of the pros and cons of the approach, including which systems it is most suitable for. The conversation ends with guidance how to get started with event sourcing, for both greenfield and legacy systems.

Birol Yildiz, CEO and co-founder of iLert, joins host Kanchan Shringi to explore how iLert built an AI SRE — an autonomous agent for handling production incidents — and what the experience revealed about building AI agents in the real world. Birol explains why incident response is a fundamentally agentic problem, where the unpredictability of novel incidents makes rule-based runbooks insufficient and reasoning models essential. He describes how the AI SRE evolved from an early browser-based approach to its current architecture, built around two key ingredients: reasoning models and the Model Context Protocol. The conversation examines the four layers of the AI SRE in depth: an orchestration layer that routes requests and abstracts model providers; a knowledge layer built on plain text memory and agentic search rather than vector databases; an evaluation framework based on recorded live investigations replayed against new model versions; and a human-in-the-loop constraint layer. The episode concludes with…

Will Sentance, educator and co-founder of Codesmith, joins SE Radio's Adi Narayan to discuss the evolution of JavaScript and modern best practices. They begin with JavaScript's origins as a simple scripting language and its growth into the backbone of modern web development, highlighting the core theme of the "don't break the web" constraint. The requirement that JavaScript must remain backward-compatible has shaped everything from naming decisions (e.g., flat instead of flatten) to the introduction of Symbols as a collision-safe way to extend objects. Will explains how the TC39 group uses the open-source community as a filtration system, absorbing user land patterns (like those from Lodash or Moment) into the standard library only once demand is proven. The upcoming Temporal API is highlighted as a major win for native date/time handling. On the engine side, Will discusses the shift toward monomorphic object shapes in the V8 JavaScript engine for better just-in-time (JIT) compiler performance, and how…

In this episode, host Amey Ambade sits with Eric Tschetter, co-founder of Apache Druid and Chief Architect at Imply, to dissect the critical move toward Decoupling Observability. To begin, they define three pillars—logs, metrics, and traces—and consider why the rise of microservices has made traditional, tightly coupled stacks a major source of pain. Such coupled systems can lead to issues such as vendor lock-in, prohibitive scaling costs, and operational complexity. Drawing parallels to the Business Intelligence world's separation, Tschetter presents an architectural solution with four distinct layers: Ingest/Route, Data Storage, Query/Compute, and Visualization. This framework aims to provide flexibility to combat the limitations of monolithic observability tools. The conversation moves into the practical challenges and significant benefits of this decoupled model, focusing heavily on data portability and the role of technologies such as OpenTelemetry in standardizing schemas so that data can flow freely…

Martin Kleppmann, Associate Professor at the University of Cambridge and author of the best-selling O'Reilly book Designing Data-Intensive Applications, talks to host Adi Narayan about local-first collaboration software. They discuss what the term means, how it leads to simpler application architectures compared to the cloud-first model, and the benefits to developers and users from keeping all of their data on their own devices. Martin goes into detail about how applications can synchronize data with and without a server, as well as conflict-resolution techniques, and the open-source library Automerge, which implements CRDTs and developers can use out-of-the-box. He also clarifies what kinds of applications would be suitable for the local-first approach. In the context of AI, they discuss vibe coding, local-first apps, and how the conflict-resolution work that enables data to be synchronized between users can also work with human-AI collaboration.

Sahaj Garg, co-founder and CTO of Wispr, a voice-to-text AI that turns speech into polished writing, talks with host Amey Ambade about designing systems for the ambiguity that's inherent in human input (text, voice, multimodal). Sahaj focuses on concrete architectural and training strategies for building robust AI systems. This episode examines the problem of ambiguity, where it shows up, building robust systems, personalization, communicating uncertainty, and evaluation. The conversation starts by exploring the difference between inherent and reducible ambiguity, major categories of ambiguity including lexical, syntactic, and pragmatic, and the additional sources of ambiguity in voice, such as homophones and accents. Garg details how to build systems through model training, including providing additional context and constructing datasets for good annotation. They discuss personalization with a focus on "revealed preferences"—learning from user behavior without explicit feedback—and fighting the problem of…

Costa Alexoglou, co-founder of the open source Hopp pair-programming application, talks with host Brijesh Ammanath about remote pair programming. They start with a quick introduction to pair programming and its importance to software development before discussing the various problems with the current toolset available and the challenges that tool developers face for enabling pair programming. They consider the key features necessary for a good pair-programming tool, and then Costa describes the journey of building Hopp and the challenges faced while building it.

Héctor Ramón Jiménez, creator of iced, an Elm-inspired, cross-platform GUI toolkit for Rust, speaks with SE Radio host Gavin Henry about building a GUI library in Rust. Héctor discusses why he created iced, what was needed, the process required to paint on the screen across different operating systems, how multi-operating systems are handled, and what the iced testing ecosystem is like. This episode explores the Elm architecture, how iced compares to other frameworks, what the core components of iced are, Elements, asynchronous functions, state, threads, 3d rendering, headless mode testing, end-to-end testing, test recorders, runtime emulators, ice test syntax, example apps, tiny-skia, DirectX, Vulkan, Metal, winit, wgpu, egui, tauri, comet, and why Android and iOS support is hard.

Dan Lorenc, co-founder and CEO of Chainguard, joins host Priyanka Raghavan to explore Sigstore and its role in securing the software supply chain. They unpack the challenges of supply chain security, including verifying the origin and integrity of software artifacts, and explain the problems Sigstore is designed to solve. The conversation goes under the hood to examine how Sigstore works, covering key components such as code signing, verification, the certificate authority model, and transparency logs—often compared conceptually to blockchain for their auditability. The episode also highlights real-world adoption, community resources for getting started, and closes with a discussion of Chainguard Images and how development teams can use them to build with more secure base images. This episode is sponsored by IEEE Computer Society.

Scott Hanselman, the VP of Developer Community at Microsoft, speaks with host Jeremy Jung about AI-assisted coding. They start by considering how the tools are a progression from syntax highlighting and autocomplete. Scott describes the ambiguity and non-determinism of agentic loops, why vague high-level prompts usually don't give good results, and the need to express intent and steer the models. He explains how knowing fundamentals helps you create better plans and know what to ask the models, and how to treat agents differently based on your knowledge level. He discusses his experience porting Windows Live Writer to a modern .NET stack, and defining success and providing tools for models to verify their work. Finally, he explains why you need to read and understand generated code in production environments, plus methods for sandboxing agents.

Marc Brooker, VP and Distinguished Engineer at AWS, joins host Kanchan Shringi to explore specification-driven development as a scalable alternative to prompt-by-prompt "vibe coding" in AI-assisted software engineering. Marc explains how accelerating code generation shifts the bottleneck to requirements, design, testing, and validation, making explicit specifications the central artifact for maintaining quality and velocity over time. He describes how specifications can guide both code generation and automated testing, including property-based testing, enabling teams to catch regressions earlier and reason about behavior without relying on line-by-line code review. The conversation examines how spec-driven development fits into modern SDLC practices; how AI agents can support design, code review, documentation, and testing; and why managing context is now one of the hardest problems in agentic development. Marc shares examples from AWS, including building drivers and cloud services using this approach, and…

Bryan Cantrill, the co-founder and CTO of Oxide Computer company, speaks with host Jeremy Jung about challenges in deploying hardware on-premises at scale. They discuss the difficulty of building up Samsung data centers with off-the-shelf hardware, how vendors silently replace components that cause performance problems, and why AWS and Google build their own hardware. Bryan describes the security vulnerabilities and poor practices built into many baseboard management controllers, the purpose of a control plane, and his experiences building one in NodeJS while struggling with the runtime's future during his time at Joyent. He explains why Oxide chose to use Rust for its control plane and the OpenSolaris-based Illumos as the operating system for their vertically integrated rack-scale hardware, which is designed to help address a number of these key challenges. Brought to you by IEEE Computer Society and IEEE Software magazine.

Jens Gustedt, author of Modern C, senior scientist at the French National Institute for Computer Science and Control (INRIA), deputy director of the ICube lab, and former co-editor of the ISO C standard, speaks with SE Radio host Gavin Henry about the past 5 years in C, C2Y, and C23. They discuss what has happened in the C world since we last spoke 5 years ago, including how the latest C standard is going and what to expect. Jens discusses how the latest changes in the Modern C book apply to you, how a C transition header can help you get up to C23 if you're not there already, and presents a comprehensive approach for program failure. This episode explores C2Y, C23, bit-precise types, stdckdint.h, stdbit.h, 128 bit types, enumeration types, nullptr, Syntactic annotations, auto and typeof keywords, if let, as well as what's being added and removed in C2Y (possibly called "C28"), and Gustedt's four categories of program failure. Brought to you by IEEE Computer Society and IEEE Software magazine.

In this episode, Subhajit Paul joins SE Radio host Kanchan Shringi to discuss how enterprise resource planning (ERP) systems work in practice and where machine learning and generative AI are beginning to fit into real-world ERP environments. Subhajit grounds the conversation in ERP fundamentals, explaining core business flows such as order-to-cash, procure-to-pay, and plan-to-produce, and why ERP systems are central to running large enterprises. He then walks through the realities of ERP implementation, sharing examples of both successful and failed projects and highlighting common challenges around testing, process coverage, integrations, and change management. The discussion also explores how AI is being applied in ERP today, including practical ML use cases such as inventory optimization and anomaly detection, as well as emerging generative AI and agent-based approaches. Brought to you by IEEE Computer Society and IEEE Software magazine.

Yechezkel "Chez" Rabinovich, CTO and co-founder at Groundcover, joins SE Radio host Brijesh Ammanath to discuss the key challenges in migrating observability toolsets. The episode starts with a look at why customers might seek to migrate their existing Observability stack, and then Chez explains some approaches and techniques for doing so. The discussion turns to OpenTelemetry, including what it is and how Groundcover helps with the migration of dashboards, monitors, pipelines, and integrations that are proprietary to vendor products. Chez describes methods for validating a successful migration, as well as metrics and signals that engineering teams can use to assess the migration health. Brought to you by IEEE Computer Society and IEEE Software magazine.

Murat Erder, CTO for Financial Services at Valtech in Europe, and Eoin Woods, independent consultant in the field of software architecture, join host Giovanni Asproni to talk about Continuous Architecture—an approach to software design where architectural decisions are made and refined continuously throughout the lifecycle of a system, instead of up front in a big design phase. The show starts with a definition of Continuous Architecture and a description of the six principles underpinning it. Following that is an explanation of the main reasons and advantages of this approach, which finishes with some hints on how to get started using it. During the conversation, they explore several key points, including how to empower teams to take architectural decisions and recording those decisions; using feedback loops to refine the architecture; the role of software architects and architectural governance; the importance of focusing on quality requirements; and the impact of artificial intelligence on the field.…

Sriram Panyam returns to the show to discuss the system design interview (SDI) with host Robert Blumen. This challenging part of the hiring process is included in the interview loop for many jobs across tech, including management and for all levels from entry to senior. The conversation starts with a look at what the SDI is, who will face it, and how critical this interview is for hiring and leveling. Sriram shares some common system design questions and what the interviewers are generally looking for, including stated versus unstated requirements and ambiguity in the questions. He offers recommendations on how candidates should disambiguate their designs and manage their time. He shares some personal stories of interview failures and successes, and even discusses some mistakes that interviewers make. Brought to you by IEEE Computer Society and IEEE Software magazine.

In this episode, Sahaj Garg, CTO of wispr.ai, joins SE Radio host Robert Blumen to talk about the challenges of building low-latency AI applications. They discuss latency's effect on consumer behavior as well as interactive applications. The conversation explores how to measure latency and how scale impacts it. Then Sahaj and Robert shift to themes around AI, including whether "AI" means LLMs or something broader, as they look at latency requirements and challenges around subtypes of AI applications. The final part of the episode explores techniques for managing latency in AI: speed vs accuracy trade-offs; speed vs cost; latency vs cost; choosing the right model; reducing quantization; distillation; and guessing + validating. Brought to you by IEEE Computer Society and IEEE Software magazine.

Derick Schaefer, author of CLI: A Practical Guide to Creating Modern Command-Line Interfaces, talks with host Robert Blumen about command-line interfaces old and new. Starting with a short review of the origin of commands in the early unix systems, they trace the evolution of commands into modern CLIs. Following the historic rise, fall, and re-emergence of CLIs, they consider innovative examples such as git, github, WordPress, and warp. Schaefer clarifies whether commands are the same as CLIs and then discusses a range of topics, including implementation languages, packages in the golang ecosystem for CLI development, CLIs and APIs, CLIs and AIs, AI tooling versus MCP, the object-command pattern, command flags, API authentication, whether CLIs should be stateless, and output formats - json, rich text. Brought to you by IEEE Computer Society and IEEE Software magazine.

Max Geurnsey III and Luniel de Beer, co-authors of the book Ready: Why Most Software Projects Fail and How to Fix It, discuss the concept of readiness in software engineering with host Brijesh Ammanath. Although Agile workflows and technical practices help delivery, many software efforts still struggle to achieve desired outcomes. Rework, shifting requirements, delays, defects, and mounting technical debt can plague software delivery and impede or altogether halt progress toward goals. The problem is often that implementation begins prematurely, before the team is properly set up for success. A strict system of explicit readiness work and gating, called Requirements Maturation Flow (RMF), has the potential to solve this problem in an SDLC-independent way. Teams that adopt RMF can dramatically improve progress toward real goals while reducing stress on engineering teams. In this episode, Max and Luniel deep dive into RMF and explain its foundational pillars. Brought to you by IEEE Computer Society and IEEE…

Mojtaba Sarooghi, a Distinguished Product Architect at Queue-it, speaks with host Jeremy Jung about virtual waiting rooms for high-traffic events such as concerts and limited-quantity product releases. They explore using a virtual queue to prevent overloading systems, how most traffic is from bots, using edge workers to reduce requests to the customer's origin servers, and strategies for detecting bots in cooperation with vendors. Mojtaba discusses using AWS services like Elastic Load Balancing, DynamoDB, and Simple Notification Service, and explains why DynamoDB's eventual consistency is a good fit for their domain. To explain the approach, he walks us through how his team resolved an incident in which a traffic spike overloaded their services. Brought to you by IEEE Computer Society and IEEE Software magazine.

In this episode, Benjamin Brial, CEO and co-founder of Cycloid, speaks with host Sriram Panyam about internal developer platforms (IDPs) and internal developer portals. The conversation explores how these platforms address the growing challenges of DevOps scalability, multi-cloud complexity, and cloud waste, all of which organizations face as they grow. Benjamin begins by framing the core problems that IDPs solve: DevOps struggling to scale beyond small teams, the complexity of managing hybrid environments across on-premises, public cloud, and private cloud infrastructure, and the significant issue of cloud waste (averaging 35-45% according to major analysts). IDPs can serve as a bridge between DevOps teams and developers, providing access to tools, cloud resources, and automation for users who aren't DevOps or cloud experts. The technical discussion covers essential IDP components including service catalogs, versioning engines, platform orchestration, asset inventory, and FinOps/GreenOps modules. The…

In this episode of Software Engineering Radio, Srujana Merugu, an AI researcher with decades of experience, speaks with host Priyanka Raghavan about building LLM-based applications. The discussion begins by clarifying essential concepts like generative vs. predictive AI, pre-training vs. fine-tuning, and the transformer architecture that powers modern LLMs. Srujana explains diffusion models and vision transformers, highlighting how multimodal AI is reshaping content creation. The conversation then moves to practical aspects—where LLMs make sense, where they don't, and a decision framework for evaluating use cases. They explore common application patterns such as retrieval-augmented generation (RAG) and agentic architectures, breaking down components like planners, orchestrators, memory, and tools. Key considerations for model selection, evaluation metrics, and safety guardrails are discussed in depth. The episode also touches on prompting strategies, automated prompt optimization, and emerging trends like…

Philip Kiely, software developer relations lead at Baseten, speaks with host Jeff Doolittle about multi-agent AI, emphasizing how to build AI-native software beyond simple ChatGPT wrappers. Kiely advocates for composing multiple models and agents that take action to achieve complex user goals, rather than just producing information. He explains the transition from off-the-shelf models to custom solutions, driven by needs for domain-specific quality, latency improvements, and economic sustainability, which introduces the engineering challenge of inference engineering. Kiely stresses that AI engineering is primarily software engineering with new challenges, requiring robust observability and careful consideration of trust and safety through evals and alignment. He recommends an approach of iterative experimentation to get started with multi-agent AI systems. Brought to you by IEEE Computer Society and IEEE Software magazine.

Flavia Saldanha, a consulting data engineer, joins host Kanchan Shringi to discuss the evolution of data engineering from ETL (extract, transform, load) and data lakes to modern lakehouse architectures enriched with vector databases and embeddings. Flavia explains the industry's shift from treating data as a service to treating it as a product, emphasizing ownership, trust, and business context as critical for AI-readiness. She describes how unified pipelines now serve both business intelligence and AI use cases, combining structured and unstructured data while ensuring semantic enrichment and a single source of truth. She outlines key components of a modern data stack, including data marketplaces, observability tools, data quality checks, orchestration, and embedded governance with lineage tracking. This episode highlights strategies for abstracting tooling, future-proofing architectures, enforcing data privacy, and controlling AI-serving layers to prevent hallucinations. Saldanha concludes that data…

Dave Thomas, author of The Pragmatic Programmer, The Manifesto for Agile Software Development, Programming Ruby, Agile Web Development with Rails, Programming Elixir, Simplicity, and co-founder of the Pragmatic Bookshelf, speaks with SE Radio host Gavin Henry about building infrastructure for eBooks. They discuss what an eBook is, the various formats, what infrastructure is needed to build them, how an author writes an book, the history of the Pragmatic Bookshelf, how they have evolved, how to handle links within eBooks, why humans are so important in the writing process, and why AI can help with your writing -- once you've written your content. Thomas discusses PDFs, eBooks, Mobi files, ePub files, CI/CD pipelines, WYSWYG, Markdown files, Pragmatic Markup Language, embedding code, AI agents, images, printing PDFs, JVMs, Java, jRuby, and how Markdown won the plain text writing format wars. Brought to you by IEEE Computer Society and IEEE Software magazine.

Jennings Anderson, a Software Engineer with Meta Platforms, and Amy Rose, the Chief Technology Officer at Overture Maps Foundation, speak with host Gregory M. Kapfhammer about the Overture Maps project, which creates reliable, easy-to-use, and interoperable open map data. After exploring the foundations of geospatial information systems, Gregory and his guests dive deep into the implementation of Overture Maps through features like the Global Entity Reference System (GERS). In addition to discussing the organizational structure of the Overture Maps Foundation and the need for a unified database of geospatial data, Jennings and Amy explain how to implement applications using data from Overture Maps. Brought to you by IEEE Computer Society and IEEE Software magazine.