#105
October 13 · 45 min
TP
The Pragmatic Embedded Podcast
Luca Ingianni, Jeff Gable
Pragmatic engineering for embedded systems.
Luca Ingianni and Jeff Gable talk about the craft of building embedded products: architecture, testing, requirements, team process, and how AI tools are changing everyday development work. Agile methods still come up, next to everything else that helps a team ship reliable devices, with a particular eye on safety-critical fields such as medical devices.
Formerly The Agile Embedded Podcast.
- 24 episodes
- fortnightly
- Avg 45 min
- English
Counted on this page — what you have heard stays on this device, so it is not something the list can be paged by.
- TP#104September 30 · 45 min
TDD: The Hard Parts - Getting Started with Test-Driven Development
We're back talking about Test-Driven Development, just 10 episodes after our last TDD discussion. This time, Jeff and Luca tackle the practical challenges that trip up developers trying to adopt TDD - especially that awkward moment staring at a blank screen wondering "what do I even type first?"
- TP#103September 23 · 16 min
The Big Rename: From Agile to Pragmatic
After five years and 101 episodes, we're doing something we never thought we'd do: renaming the podcast. The Agile Embedded Podcast is now the Pragmatic Embedded Podcast: having the title reflect where we've been heading for quite a while.
- TP#100August 24 · 59 min
100 Episodes! Break Out the Champagne! A Retrospective
We flip the script for episode 100! Instead of hosting, Luca and Jeff become the guests as Joe Schneider and Jacob Beningo take over the interview chair. We look back at how two consultants from opposite sides of the world accidentally started a podcast, share war stories about the hardest bugs we've ever chased (spoiler: weeks of work for one-line fixes), and discuss why "Agile" might not be the buzzword it once was. The conversation touches on everything from helicopter avionics to the future
- TP#99August 4 · 43 min
From Vision to Reality: Product Roadmaps in Embedded Development
In the third installment of our requirements engineering series, Luca and Jeff shift focus from requirements themselves to the bigger picture: how do you actually turn ideas into working products? We explore the journey from product vision through roadmaps to backlogs, discussing what makes a good roadmap and—perhaps more importantly—the surprisingly common mistakes that even experienced teams make.
- TP#98June 9 · 50 min
Factory Firmware Flashing with Pete Staples
We talk with Pete Staples, founder of Blue Clover Devices, about the often-overlooked challenge of flashing firmware in production. Pete shares insights from running a contract manufacturing operation in Shenzhen and explains why the handoff from engineering to manufacturing is more like "hucking it over a fence" than a smooth relay race.
- TP#97May 27 · 50 min
Requirements Engineering, part 2: A Practical Process for Safety-Critical Development
In this second part of our requirements engineering series, Jeff walks us through his preferred process for developing safety-critical products, particularly medical devices. We explore the crucial distinction between prototyping and design-controlled development, discussing when to start formal requirements work and how to keep your first version minimal yet complete. Jeff emphasizes the importance of deeply fleshing out requirements before implementation—including error handling, which often
- TP#96May 13 · 48 min
Fuzzing and Dynamic Analysis for High-Integrity Software with Paul Butcher
We sit down with Paul Butcher, Unit Director of Dynamic Analysis at AdaCore, to explore verification techniques beyond basic compliance in safety-critical software. Paul shares his experience from Eurofighter to automated trains, explaining how dynamic analysis—from unit testing to coverage analysis to fuzzing—helps find bugs that traditional testing misses. The conversation dives deep into fuzzing: how it works, why it's so effective at finding corner-case bugs (even in well-tested systems), a
- TP#95April 30 · 46 min
Linux Profiling with Mohammed Billoo
We sit down with Mohammed Billoo, founder of Mab Labs and author of the Embedded Linux Essentials Handbook, to explore the world of embedded Linux profiling and optimization. Mohammed shares hard-won lessons from the field, including debugging a scientific instrument that mysteriously crashed after 60-minute runs and optimizing a sophisticated MANET platform that took a 20% throughput hit. The conversation reveals a fundamental truth: in embedded Linux, the CPU is rarely the bottleneck. Mohamme
- TP#94April 15 · 47 min
E94 Requirements Engineering, part 1: Fundamentals
We kick off a multi-part series on requirements engineering by exploring what requirements actually are and why they matter - even for Agilists. Jeff shares his medical device expertise while Luca brings his automotive and aerospace background to discuss the different levels of requirements (from high-level user needs to testable system requirements), the importance of traceability, and why proper tooling beats Word and Excel every time. We dig into practical aspects like the EARS format for wr
- TP#93April 1 · 52 min
Hardware-Software Co-Development with Tobias Kästner
We talk with Tobias Kästner, a physicist-turned-software-architect and technical consultant at Inovex, about his journey from painfully slow hardware-software integration cycles to achieving three-week hardware sprints. Tobias shares hard-won lessons from medical device development, where fuzzy requirements and constant feedback from life scientists forced his team to rethink traditional approaches.
- TP#92March 18 · 42 min
Test-Driven Development in the Age of AI
We explore how test-driven development (TDD) remains essential—perhaps more than ever—when working with AI coding tools. Luca shares his evolved workflow using Claude Code, breaking down how he structures tests in three phases: test ideas, test outlines, and test implementations. We discuss why TDD provides the necessary control and confidence when AI generates code, how it prevents technical debt accumulation, and why tests serve as precise specifications for AI rather than afterthoughts.
- TP#91March 4 · 43 min
Engineering Organizations Part 2: Product Companies and Market-Driven Focus
In this second part of our series on engineering organizations, Jeff and Luca explore how companies that build products should focus their efforts differently depending on their stage and scope. We start with startups and early-stage companies desperately searching for product-market fit, where the brutal truth is: quality doesn't matter yet. Your MVP should embarrass you—if it doesn't, you waited too long. We discuss the critical mental shift from throwaway prototypes to proper engineering once
- TP#90February 18 · 43 min
Engineering Organizations Pt 1: Service Firms - When You Are the Product
In this first part of a two-part series, Jeff and Luca explore how different types of service-oriented engineering organizations should focus their learning and improvement efforts. Drawing from their consulting experience, they examine three distinct categories: product development firms that turn client ideas into reality, engineering development firms that sell specialized technical expertise, and solo engineers who package all necessary knowledge into one person.
- TP#89January 19 · 35 min
Rust with Milica Kostic
In this episode, we sit down with embedded software architect Milica Kostic to discuss her journey from C/C++ to Rust and what it means for embedded development. Milica shares her experience adopting Rust in production environments, starting with an embedded Linux project using a microservice architecture that allowed for clean isolation of Rust code.
- TP#88January 5 · 57 min
MicroPython with Matt Trentini
We talk with Matt Trentini, Principal Software Engineer at Planet Innovation, about using MicroPython for professional embedded development—including medical devices. Matt shares how he was drawn back to embedded development after becoming jaded with traditional C-based workflows, and explains why MicroPython's interactive REPL and rapid development cycle have become game-changers for his team.
- TP#87Dec 16, 2025 · 53 min
Terrible Habits of the Solo Developer
In this episode, Jeff and Luca tackle the unique challenges faced by solo embedded developers. Drawing from their own experiences as consultants, they explore why working alone makes it harder to maintain good development practices - from the constant pressure to multitask across different stakeholder demands, to the difficulty of wearing multiple hats as leader, manager, and contributor simultaneously.
- TP#86Dec 3, 2025 · 50 min
Agile Hardware Development with Gregor Gross
In this fascinating episode, we dive deep into the world of agile hardware development with Gregor Gross, a civil engineer who runs Alpha-board, a PCB design service company in Berlin, Germany. Gregor shares his unique perspective on applying agile principles to hardware projects, where you can't just hit compile and get a new increment.
- TP#85Nov 18, 2025 · 55 min
Crossover with Embedded AI Podcast
In this special crossover episode with the brand-new Embedded AI Podcast, Luca and Jeff are joined by Ryan Torvik, Luca's co-host on the Embedded AI podcast, to explore the intersection of AI-powered development tools and agile embedded systems engineering. The hosts discuss practical strategies for using Large Language Models (LLMs) effectively in embedded development workflows, covering topics like context management, test-driven development with AI, and maintaining code quality standards in s
- TP#84Nov 12, 2025 · 28 min
AI-enhanced Embedded Development (May 2025 Edition)
In this episode, Jeff interviews Luca about his intensive experience presenting at five conferences in two and a half days, including the Embedded Online Conference and a German conference where he delivered a keynote on AI-enhanced software development. Luca shares practical insights from running an LLM-only hackathon where participants were prohibited from manually writing any code that entered version control—forcing them to rely entirely on AI tools. The conversation explores technical challenges in AI-assisted embedded development, particularly the importance of context management when working with LLMs. Luca reveals that effective AI-assisted coding requires treating prompts like code itself—version controlling them, refining them iteratively, and building project-specific prompt libraries. He discusses the economics of LLM-based development (approximately one cent per line of code), the dramatic tightening of feedback loops from days to minutes, and how this fundamentally changes agile workflows for embedded teams. The episode concludes with a discussion about the evolving role of embedded developers—from code writers to AI supervisors and eventually to product owners with deep technical skills. Luca and Jeff address concerns about maintaining core software engineering competencies while embracing these powerful new tools, emphasizing that understanding the craft remains essential even as the tools evolve. Key Topics [02:15] LLM-only hackathon constraints: No human-written code in version control [04:30] Context management as the critical skill for effective LLM-assisted development [08:45] Explicit context control: Files, directories, API documentation, and web content integration [11:20] LLM hallucinations: When AI invents file contents and generates diffs against phantom code [13:00] Economics of AI-assisted coding: Approximately $0.01 per line of code [15:30] Tightening feedback loops: From day-long iterations to minutes in agile embedded workflows [17:45] Rapid technical debt accumulation: How LLMs can create problems faster than humans notice [19:30] The essential role of comprehensive testing in AI-assisted development workflows [22:00] Challenges with TDD and LLMs: Getting AI to take small steps and wait for feedback [26:15] Treating prompts like code: Version control, libraries, and project-specific prompt management [29:40] External context management: Coding style guides, plan files, and todo.txt workflows [32:00] LLM attention patterns: Beginning and end of context receive more focus than middle content [34:30] The evolving developer role: From coder to prompt engineer to AI supervisor to technical product owner [38:00] Code wireframing: Rapid prototyping for embedded systems using AI-generated implementations [40:15] Maintaining software engineering skills in the age of AI: The importance of manual practice [43:00] Software engineering vs. software carpentry: Architecture and goals over syntax and implementation Notable Quotes "One of the hardest things to get an LLM to do is nothing. Sometimes I just want to brainstorm with it and say, let's look at the code base, let's figure out how we're going to tackle this next piece of functionality. And then it says, 'Yeah, I think we should do it like this. You know what? I'm going to do it right now.' And it's so terrible. Stop. You didn't even wait for me to weigh in." — Luca Ingianni "LLMs making everything faster also means they can create technical debt at a spectacular rate. And it gets a little worse because if you're not paying close attention and if you're not disciplined, then it kind of passes you by at first. It generates code and the code kind of looks fine. And you say, yeah, let's keep going. And then you notice that actually it's quite terrible." — Luca Ingianni "I would not trust myself to review an LLM's code and be able to spot all of the little subtleties that it gets wrong. But if I at least have tests that express my goals and maybe also my worries in terms of robustness, then I can feel a lot safer to iterate very quickly within those guardrails." — Luca Ingianni "Roughly speaking, the way I was using the tool, I was spending about a cent per line. Which is about two orders of magnitude below what a human programmer roughly costs. It really is a fraction. So that's nice because it makes certain things approachable. It changes certain build versus buy decisions." — Luca Ingianni "You can tighten your feedback loops to an absurd degree. Maybe before, if you had a really tight feedback loop between a product owner and a developer, it was maybe a day long. And now it can be minutes or quarters of an hour. It is so much faster. And that's not just a quantitative step. It's also a qualitative step." — Luca Ingianni "Some of my best performing prompts came from a place of desperation where one of my prompts is literally 'wait wait wait you didn't do what we agreed you would do you did not read the files carefully.' And I'd like to use this prompt now, even before it did something wrong. And then it apologizes as the first step. And I feel terrible because I hurt the LLM's feelings. But it is very effective." — Luca Ingianni "As you tighten your feedback loops, quality must be maintained through code review and tests. Test first, new feature, review, passing tests—you need to go through that red-green-refactor loop. You can just hopefully do it much more quickly, and maybe in slightly bigger steps than you did before manually." — Jeff Gable "A lot of what I'm doing is really intended to rein in an LLM's propensity to sort of ramble. It's very hard to get them to practice TDD because you can ask them to write the test first, then they will. And then they will just trample on and write the implementation right with it without stopping and returning control back to you." — Luca Ingianni "Those prompts tend to be to some degree specific to the particular code base or the particular problem domain. Every now and then you stumble across ways of making an LLM do exactly what you want it to do within the context of the particular code base. And once you find a nugget like this, you keep it. You don't just keep it in the generic library. Some of those tricks will be very specific to a particular code base." — Luca Ingianni "Just like humans, LLMs tend to pay more attention to the stuff at the beginning of the context and at the end, and the middle sort of gets not quite forgotten but kind of fuzzy. You really need to have a way to extract all of that before it becomes fuzzy and store it in a safe place where it can't be damaged, like a file." — Luca Ingianni "I think we will hit this weird valley in the coming five years where everyone's just using LLMs and no one knows how to write code anymore. And there will be a need for people who can leverage the tools, but still have the skills that serve as the solid foundation." — Jeff Gable "Maybe this is essentially software engineering finally becoming true to its name. At the moment, software engineering is sort of more like software carpentry. You're really doing the craft. You're laboring to put the curly brackets at the right places. And maybe now it's more about taking a step back and thinking in terms of architecture, and thinking in terms of goals, as opposed to knowing how to swing a hammer." — Luca Ingianni Resources Mentioned Embedded Online Conference - Premier online conference for embedded systems professionals featuring talks on AI integration, development practices, and cutting-edge embedded technologies. All sessions are recorded and available for on-demand viewing. Aider - AI pair programming tool mentioned for its ability to integrate web content into context using commands like '/web [URL]' to incorporate API documentation and other online resources directly into the development workflow. GitHub Copilot - AI-powered code completion tool integrated with VS Code and other IDEs, enabling context-aware code generation and assistance for embedded development workflows. Jeff runs BaseRef, a Requirements Management and Documentation tool for medical device startups, at https://getbaseref.com. You can find Luca at https://luca.engineer. Want to join the Pragmatic Embedded Slack? Click here Are you looking for embedded-focused trainings? Head to https://agileembedded.academy/ Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/