In this episode of the Embedded Frontier podcast, Jacob Beningo and Kyle Dando from NXP discuss the modernization of embedded software and firmware, focusing on the MCU Xpresso SDK. They explore the significant changes made to the SDK, including the adoption of CMake and KConfig, the introduction of West for managing software repositories, and the overall impact on developer workflows. The conversation also covers the migration path for existing users and future trends in embedded software development, emphasizing the importance of user feedback in shaping the SDK's evolution.

Takeaways

- Modern build systems are essential for embedded software development.
- The MCU Xpresso SDK packages low-level drivers and middleware for ease of use.
- Accessibility improvements were a primary focus in SDK modernization.
- CMake was adopted for its universal build capabilities and customer demand.
- West allows for efficient management of software from multiple repositories.
- KConfig simplifies project configuration and dependency management.
- Developers can choose between command line and IDE workflows.
- Migration to the new SDK is designed to minimize disruption for users.
- Future trends include support for new operating systems and ecosystems.
- User feedback is vital for continuous improvement of the SDK.

In this episode of the Embedded Frontier Podcast, Jacob Beningo discusses the importance of modernizing build systems in embedded software development. He outlines a seven-step framework for developing faster and smarter firmware, focusing on the need to overhaul build systems to keep pace with contemporary development practices. The conversation covers containerization, the adoption of tools like CMake and West, and the integration of AI technologies to enhance build processes and ensure flexibility and scalability in software development.

Takeaways

- Overhauling your build system is crucial for modern development.
- Build systems must adapt to contemporary software practices.
- Containerization provides a consistent build environment.
- CMake offers flexibility and modularity in builds.
- West helps manage multiple repositories effectively.
- Modern build systems should integrate with CI/CD workflows.
- Flexibility in workflows enhances developer productivity.
- AI can assist in transitioning to modern build systems.
- Scalability is essential for long-term software projects.
- A modern build system reduces stress and increases efficiency.

Keywords

embedded systems, build system, DevOps, CMake, containerization, software development, AI, firmware, modern architecture, CI/CD

Summary

In this episode of the Embedded Frontier Podcast, Jacob Beningo introduces a comprehensive framework for modernizing embedded systems development. He discusses the importance of adapting to modern techniques in firmware development, emphasizing the need for a shift in workflows, architectures, and tools. The episode outlines a seven-step process that includes modernizing build systems, improving software architecture, implementing DevOps practices, embracing test-driven development, leveraging simulation, adopting AI and machine learning, and establishing a metrics scoreboard to track progress. Each step is designed to help teams develop faster and smarter firmware, ultimately leading to more efficient and effective embedded systems development.


Takeaways

• Modernizing firmware is essential for efficient development.
• The seven-step modernization framework includes build systems, architecture, DevOps, testing, simulation, AI, and metrics.
• Modern build systems should support various developer tools and environments.
• Software architecture must be scalable and flexible, separating application code from hardware.
• DevOps is crucial for improving collaboration and speeding up development cycles.
• Testing should be prioritized, with an emphasis on test-driven development (TDD).
• Simulation can help developers test application code without hardware dependencies.
• AI and machine learning can enhance both on-chip processing and development workflows.
• Metrics are essential for tracking progress and identifying areas for improvement.

The framework aims to help teams deliver better products on time and within budget.

Keywords

embedded systems, firmware development, modernization framework, build systems, DevOps, test-driven development, simulation, AI, machine learning, metrics

In this episode of the Embedded Frontier podcast, Jacob Beningo explores the evolving role of artificial intelligence (AI) in embedded systems development. He discusses the potential applications of AI, including code review, documentation, and generating code, while emphasizing the importance of adopting AI technologies to enhance productivity and efficiency in the field. Beningo also addresses the challenges and risks associated with AI, advocating for its integration into development workflows to stay competitive in the industry.

Takeaways

• AI has a unique role to play in embedded systems development.
• Documentation is a critical area where AI can assist developers.
• AI can help automate code reviews, making them more efficient.
• Using AI for generating code can speed up the prototyping process.
• AI can help document architectural decisions and trade-offs.
• The rapid evolution of AI technology presents both opportunities and risks.
• AI can serve as an augmentation tool for developers, enhancing their capabilities.
• Understanding how to effectively prompt AI is crucial for getting desired results.
• AI can help reduce technical debt by improving documentation practices.
• The integration of AI into workflows can lead to significant productivity gains.

Summary

In this episode of the Embedded Frontier, Jacob Beningo discusses the key trends observed at Embedded World 2025, focusing on the integration of commercial tools with modern workflows, the rise of Zephyr as a dominant RTOS, the pervasive influence of AI in embedded systems, the necessity of multi-core processors, and the mainstream adoption of DevOps practices. Beningo emphasizes the importance of adapting to these trends to enhance development efficiency and product reliability.

Takeaways

• Commercial tools are starting to support open source development.
• Zephyr is becoming a dominant player in the embedded systems industry.
• AI technologies are increasingly being integrated into embedded devices.
• Multi-core processors are becoming essential for complex IoT applications.
• DevOps practices are being adopted more widely in embedded development.
• Security and compliance must be automated in development workflows.
• The integration of AI can significantly enhance embedded system capabilities.
• Open source and commercial tools can work together effectively.
• Modern workflows are essential for efficient embedded software development.
• The industry is evolving rapidly, and developers must adapt to stay competitive.

Keywords

embedded systems, trends, Zephyr, AI, multi-core processors, DevOps, modern workflows, commercial tools, open source, Embedded World 2025

Summary

In this conversation, Jacob Beningo interviews John Taylor about his extensive experience in embedded systems and his new book, 'The Embedded Project Cookbook.' They discuss the inspiration behind the book, its target audience, and key themes such as the importance of building and testing software before hardware. John shares insights on challenges in requirements gathering, the use of a reference design, and the transition from C to C++ in embedded projects. They also explore future trends in the industry, particularly the impact of AI, and conclude with key takeaways from the book.

Takeaways

• John Taylor has over 30 years of experience in embedded systems.
• The Embedded Project Cookbook was inspired by the need for better documentation and processes.
• The primary audience for the book includes software architects and tech leads.
• Building and testing software before hardware can save time and improve code quality.
• Requirements gathering is a critical yet challenging aspect of embedded systems development.
• The GM 6000 digital heat controller serves as a relatable reference design in the book.
• Source code and frameworks provided in the book can help developers bootstrap their projects.
• C++ offers advantages in type safety and encapsulation for embedded systems.
• AI is becoming part of embedded workflows, but its understanding of embedded systems is still limited.
• Quality in projects requires planning and discipline beyond just writing code.

Keywords

Embedded Systems, Embedded Project Cookbook, Software Development, Requirements Gathering, C++, AI in Embedded Systems, Software Architecture, Project Management, Hardware Development, John Taylor

In this episode of Embedded Frontier, Jacob Beningo discusses the top trends in embedded systems for 2025. He highlights the increasing role of AI and machine learning, the dominance of open-source software, the critical importance of security, and the ongoing relevance of programming languages like C and C++. Beningo also emphasizes the rise of simulation technologies, the integration of DevOps and observability, and the expansion of edge AI, providing insights into how these trends will shape the future of embedded systems development.

Takeaways

·      AI will enhance embedded systems development.

·      Machine learning applications are still underutilized.

·      Open-source software is becoming increasingly dominant.

·      Security is a top priority for embedded systems.

·      C remains the most widely used programming language.

·      Simulation technologies will modernize development processes.

·      DevOps practices are essential for improving software quality.

·      Edge AI will allow for local data processing.

·      Modern programming languages will see increased adoption.

·      2025 will bring significant changes to embedded systems.

Keywords

embedded systems, AI, machine learning, open source, security, programming languages, DevOps, edge AI, simulation technologies

Curious about the future of embedded systems? In this episode, Jacob Beningo is joined by Shawn Prestridge from IAR Systems to tackle the pressing challenges developers face today. From real-world insights into AI’s role in embedded devices to the overlooked pitfalls of security in connected systems, Shawn shares practical lessons learned from his decades in the field. Whether you’re interested in how AI can transform your development process, or you're navigating the complexities of modern code quality and security, this conversation offers actionable strategies that every embedded developer needs. Don't miss this chance to learn from the cutting edge of embedded systems development.

In this episode, Jacob Beningo interviews François Baldassari, Memfault CEO, about IoT security compliance demands. They discuss embedded manufacturers' readiness for new security regulations, the challenges they face, and potential solutions.

They also explore the differences between the EU's Cyber Resilience Act and the US's Cyber Trust Mark. François emphasizes the importance of OTA updates, using open-source software, and building security teams within hardware companies. He also highlights the need for collecting the right data and observability to improve security posture.

Takeaways

• Embedded manufacturers are not fully ready for new IoT security compliance demands.
• Regulatory frameworks like the EU's Cyber Resilience Act and the US's Cyber Trust Mark are coming into effect and will require certification of cybersecurity guidelines.
• Challenges include the uncertainty of the regulations, the additional costs and effort required, and the lack of established infrastructure and best practices.
• Recommendations for compliance include implementing OTA updates, using open-source software, adopting SBOM scanning, and ensuring observability of devices.
• AI is not currently a solution for compliance, but it may play a role in the future as more data is collected and analyzed.
• Joining the conversation around open-source products and following security best practices can help improve device security.

Summary

In this conversation, Jacob and Daniel Situnayake discuss the future of AI and machine learning in embedded software development. They explore the challenges and opportunities of implementing AI and machine learning at the edge, and how tools like TensorFlow Lite for Microcontrollers and Edge Impulse are making it easier for developers to deploy models on resource-constrained devices. They also discuss the importance of balancing model accuracy with resource constraints and the potential for AI-generated models in the future. Overall, the conversation highlights the growing interest and potential of AI and machine learning in the embedded space.

Keywords

AI, machine learning, embedded software development, TensorFlow Lite, Edge Impulse, resource constraints, model accuracy, AI-generated models

Takeaways

• AI and machine learning are being increasingly applied to embedded software development, opening up new possibilities for edge devices.
• Tools like TensorFlow Lite for Microcontrollers and Edge Impulse are making it easier for developers to implement AI and machine learning on resource-constrained devices.
• Balancing model accuracy with resource constraints is a key consideration in embedded AI development.
• The future of embedded AI and machine learning holds the potential for AI-generated models and more sophisticated applications at the edge.