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If SpaceX can iterate Starship faster than most teams iterate a simple PCB, what does that say about our definition of 'hardware complexity'?

I’ve been browsing engineering jobs in the mechanical R&D and manufacturing in various industries. Once thing has stood out: a lot of companies want the typical Solidworks + extensive GD&T experience, but buried in these job descriptions was also mention of experience with coding languages preferred. The first time that I saw it, I figured it was a copy-paste error, but the more it pops up the more I realize that this is a fundamental shift in the industry. Hardware engineers that can code are no longer unicorns, but becoming the norm.

This pattern is hard to ignore. When I talked to professors at local engineering schools, they told me they're scrambling to add programming courses to mechanical engineering curricula because their graduates kept getting turned away from interviews for lacking software skills. Startup founders I know can't build hardware products anymore without significant firmware components, data collection systems, or IoT connectivity. Even traditional manufacturing companies want engineers who can automate their design workflows and build custom analysis tools.

It hit me that we're living through a fundamental shift in what it means to be a hardware engineer. The coolest innovations today - whether it's Tesla's self-updating cars, SpaceX's reusable rockets, or medical devices that learn from patient data - all exist at the intersection of atoms and bits. Pure hardware knowledge isn't enough anymore, but neither is pure software expertise. The future belongs to engineers who can speak both languages fluently.

This isn't just about adding a programming language to your resume. It's about understanding how software is reshaping the entire hardware development process, from initial design through manufacturing and into the field. Over the next four weeks, we're going to explore this convergence from a hardware engineer's perspective - not how to become a software developer, but how to remain a great hardware engineer in a world where the two domains are inseparably linked.

There’s a fundamental shift happening in the hardware development world. Long standing design principals utilizing CAD PDM for version control is being overtaken by software development style methodologies that are revolutionizing version control, continuous integration, automated testing, and iterative deployment. This shift, will completely change how we design, build, and improve hardware.

Traditional hardware development has operated on what many call the "gold master" mentality. Teams spend months or years perfecting a design before manufacturing, treating each iteration as a major milestone. Any changes after production require expensive tooling modifications, lengthy approval processes, and significant financial risk. This approach made sense when manufacturing was inflexible and software updates were impossible after shipping.

But that world is disappearing fast.

Today's hardware is increasingly software-defined. Tesla vehicles receive over-the-air updates that unlock new features, improve performance, and fix issues without requiring a trip to the service center. John Deere tractors can be remotely updated with new capabilities, turning agricultural equipment into platforms for continuous improvement. Even traditionally mechanical products like 3D printers now operate more like software platforms than static machines.

This convergence creates an opportunity to apply proven software development practices to hardware projects. Version control systems that track every change to code can now manage CAD files, PCB designs, and assembly instructions. Continuous integration pipelines that automatically test software can run design rule checks, simulations, and compliance validations. Agile methodologies that enable rapid iteration in software can guide hardware development cycles.

Making code-first hardware development work requires the right technical infrastructure. CAD version control systems like Onshape operate natively in the cloud, allowing real-time collaboration and automatic version tracking. Traditional tools like Autodesk Vault and PTC Windchill provide enterprise-grade version control for existing CAD workflows.

Automated testing becomes crucial when hardware designs change frequently. Continuous integration pipelines can automatically run design rule checks on PCB layouts, validate mechanical assemblies for interference, and ensure designs meet manufacturing constraints. Some teams even automatically generate test parts on 3D printers when CAD files change, enabling rapid physical validation of design iterations.

Documentation-as-code practices ensure that specifications, assembly instructions, and compliance records stay synchronized with design changes. Engineering teams write specifications in Markdown, store them alongside CAD files, and automatically generate reports and documentation from version-controlled sources.

Modern hardware development increasingly resembles software deployment pipelines. When an engineer commits a design change, automated systems spring into action. Design rule checkers validate PCB layouts against manufacturing constraints. Simulation engines test mechanical assemblies under load conditions. Cost analysis tools estimate manufacturing impact. Compliance checkers ensure regulatory requirements are met.

This automation catches problems early, when they're cheap to fix. Rather than discovering interference issues during prototype assembly, automated clash detection identifies conflicts immediately after design changes. Instead of finding manufacturability problems during production, design rule checkers flag issues before fabrication begins.

The result is faster iteration cycles with higher confidence. Teams can make changes more frequently because automated validation reduces the risk of introducing problems. Engineering time shifts from manual checking and validation toward higher-value design work.

Several companies are already demonstrating the power of code-first hardware development. OpenROV developed their underwater drones entirely using open-source CAD tools with Git version control. Every design change, from hull modifications to electronics updates, gets tracked and managed like software commits. The result is a development process where multiple engineers can collaborate simultaneously, changes can be rolled back instantly, and the entire design history remains accessible.

Prusa Research has taken this approach even further with their 3D printer product line. Their entire hardware ecosystem is managed like software releases, with version numbers, release notes, and staged rollouts. When they discover an improvement to a component, they can push updates to users who can then print the upgraded parts themselves. This creates a feedback loop where hardware improvements can be deployed almost as quickly as software patches.

SpaceX represents perhaps the most aggressive application of iterative hardware development. Their Starship program operates on rapid prototype cycles, building and testing vehicles at a pace that would be unthinkable in traditional aerospace. Each iteration incorporates lessons from previous tests, with design changes happening between flights. This approach has allowed them to advance rocket technology faster than companies spending decades on single designs.

The technical aspects of code-first hardware development are often the easy part. The harder challenge is cultural transformation. Hardware teams must abandon the gold master mentality that treats each design iteration as a major event. Instead, they need to embrace continuous improvement, viewing designs as living documents that evolve over time.

This shift requires new definitions of quality and success. Rather than measuring success by how few changes are needed after the initial design, teams need to optimize for how quickly they can incorporate improvements. Quality metrics shift from defect prevention to rapid defect detection and correction.

Risk tolerance must also evolve. Traditional hardware development minimizes risk by extensive upfront planning and validation. Code-first approaches accept higher iteration risk in exchange for faster learning cycles and reduced overall project risk. Teams become comfortable with imperfect initial designs, knowing they can improve rapidly based on real-world feedback.

Different industries are adopting these practices at varying speeds. Consumer electronics companies, already comfortable with rapid product cycles, are leading the transition. Automotive manufacturers are following, driven by the shift toward software-defined vehicles. Aerospace and medical device companies, constrained by regulatory requirements, are moving more cautiously but still finding ways to incorporate iterative development within compliance frameworks.

Company size also affects adoption patterns. Startups and smaller companies can pivot quickly to new methodologies, while large enterprises must navigate existing processes, toolchains, and organizational structures. However, the competitive advantages are significant enough that even conservative industries are beginning to experiment with software-inspired hardware development.

Adopting code-first hardware development isn't without challenges. Legacy CAD tools weren't designed for version control, creating technical obstacles for teams trying to implement proper change tracking. File formats can be incompatible with standard version control systems, requiring specialized tools or workarounds.

Manufacturing partners may not be prepared for frequent design changes. Traditional suppliers expect stable designs with infrequent updates. Teams implementing rapid iteration must either find more flexible manufacturing partners or develop hybrid approaches that balance iteration speed with manufacturing constraints.

Regulatory environments can also create friction. Industries with strict compliance requirements may struggle to implement rapid iteration while maintaining audit trails and approval processes. However, better documentation and automated validation can actually improve compliance by creating more thorough and consistent records.

Code-first hardware development represents the future of engineering. As products become more software-defined and manufacturing becomes more flexible, the advantages of iterative development compound. Teams that master these approaches will deliver better products faster than competitors stuck in traditional development cycles.

The transformation goes beyond efficiency gains. Code-first methodologies enable entirely new product categories and business models. Hardware platforms designed for continuous improvement can evolve after shipping, creating ongoing relationships with customers rather than one-time transactions. Products can improve throughout their lifecycle, delivering increasing value over time.

For engineers, this shift creates opportunities to work more like software developers while solving physical problems. Version control eliminates the fear of breaking working designs. Automated testing provides confidence to make changes. Continuous integration catches problems before they become expensive. The result is a more productive, less stressful development environment that encourages experimentation and innovation.

The hardware industry is ready for this transformation. The tools exist, the examples are proven, and the competitive advantages are clear. The question isn't whether code-first hardware development will become standard practice. The question is how quickly engineering teams can adapt their processes, tools, and culture to take advantage of this opportunity.

Engineering is about solving, innovating, and connecting ideas to make a difference. Progress is a collective effort and your curiosity is what drives it forward. Thank you for exploring the dynamic world of engineering with all of us at Pipeline Design & Engineering and The Wave.

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“Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while.” - Steve Jobs

In collaboration and creativity,
Brad Hirayama
Blueprinting tomorrow, today