Altium File Parsing, AI Design Reviews & PCB Viz Tools

In this episode of OnTrack: The PCB Design Podcast, host Zach Peterson welcomes Eli Hughes, principal at Wave Number LLC, to discuss his innovative open-source tools for PCB design automation and AI integration. Hughes shares his journey from a childhood fascination with video games and music to a career in electronics and embedded systems, highlighting how early exposure to hardware and software sparked his lifelong passion for PCBs. He introduces his suite of tools—collectively known as 'Altium Cruncher' and 'Monkeys'—which automate file parsing, generate lightweight 3D and schematic visualizers, and extract semantic data from Altium designs in JSON format. These tools enable AI-driven design reviews, automated power tree generation, and rapid firmware development by transforming complex PCB data into machine-readable formats. Hughes envisions a future where AI can access a company's entire design history as a searchable knowledge base, enabling true design reuse and eliminating the need for manual research. He also advocates for a new standard where semiconductor manufacturers provide full 3D package data to automatically generate footprints and IPC-compliant models, reducing reliance on manual library creation. The conversation underscores a growing shift in PCB design: from manual, repetitive tasks to intelligent, automated workflows powered by open-source tools and AI. Hughes emphasizes that the real value isn't in the schematic or footprint libraries themselves, but in the knowledge embedded within designs—what he calls the 'library of knowledge.' His tools, like the 3D Viz and schematic visualizer, allow engineers to quickly inspect complex boards and schematics without needing full ECAD software, making them ideal for board bring-up and firmware development. He also discusses the potential of integrating these tools into enterprise PDM/PLM systems, creating localized AI knowledge stores that can analyze historical designs, user feedback, and documentation. The episode closes with a forward-looking vision where AI doesn't replace designers but empowers them to focus on the creative, high-value aspects of hardware development—like building the next guitar amp or innovative system—while automating the tedious, time-consuming parts.