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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 between multiple back-ends. A significant portion of the discussion is dedicated to the Query/Compute layer, specifically how Apache Druid addresses the unique demands of real-time analytics on observability data, including indexing strategies and unifying results across hot and cold storage. They also delve into operational survival, covering critical topics like smart sampling to preserve high-value signals, best practices for buffering and backpressure, and the governance models required for multiple teams to safely access the same data lake. The episode concludes with an honest look at the complexity trade-offs and a roadmap for organizations considering a migration from a coupled vendor stack.

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 AI writing that "regresses to the mean." Finally, they consider how to communicate uncertainty to users without degrading the experience, as well as methods for evaluating ambiguity resolution through offline and online signals.

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 discusses the role of modularity, APIs, and strong typing in making both humans and AI more effective. The episode concludes with guidance on rollout, evaluation metrics, cultural readiness, and why AI-driven development shifts the engineer's role toward problem definition, system design, and long-term maintainability rather than raw code production. Brought to you by IEEE Computer Society and IEEE Software magazine.

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

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.