Steve Britt

Modified Agile for Electronics Development Electronics development has never been more complex—or more critical. Traditional waterfall methods often slow teams down with long cycles, costly redesigns, and missed deadlines. While software teams have thrived with agile, hardware development requires a different approach. This white paper introduces the Modified Agile for Hardware Development (MAHD) Framework™, designed specifically for electronics teams. By adapting agile principles to hardware’s unique challenges, MAHD enables faster timelines, reduced risk, and higher-value solutions. If your organization struggles with shifting requirements, late-stage changes, or cross-disciplinary silos, this guide provides a smarter way forward.   Why Download This White Paper?   Understand why traditional methods fall short and how hardware-specific agile solves the challenges waterfall and “faux agile” can’t. Get a clear introduction to the MAHD Framework™, a proven model that accelerates development by 25–50% while reducing costly risk. Learn practical strategies and tools—from system-level user stories and tailored prototyping to Altium’s solutions for agile electronics success.   What You’ll Take Away:   A framework purpose-built for hardware and electronics – not a software agile retrofit Practical methods to reduce wated effort, improve predictability, and accelerate time-to-market Real-world examples of how electronics teams can align strategy, execution, and customer…

Special Guest Blog Post written by Matt McKinney, Co-Founder and CEO of Loop   I spend most of my time with supply chain and innovation leaders at major enterprises who are sitting on significant AI budgets but struggling to show measurable business impact in an increasingly complex and volatile supply chain environment.   These conversations have evolved dramatically. A year ago, executives were asking basic questions about AI feasibility. Today, the questions have shifted to strategic implementation at enterprise scale.   Based on hundreds of these discussions, three questions consistently emerge that separate companies making transformational progress from those stuck in pilot purgatory.   How do we move from AI experiments to enterprise-scale impact?   Most organizations have yet to see organization-wide, bottom-line impact from AI use. This is the strategic challenge keeping C-suite leaders awake at night.   The problem isn’t the technology. It’s the application of the technology. Too many enterprises are trying to treat AI like a magic wand they can bolt onto existing systems. But garbage in, garbage out. If your underlying data is fragmented and inconsistent, AI won’t solve your problems; in fact they’ll get worse.   At its core, anything automated is powered by…