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For most of the last two decades, software was the center of gravity in technology. But the pendulum is beginning to swing the other way.
Capital flowed toward SaaS. Startups prioritized asset-light business models. “Move fast and break things” became synonymous with code. Hardware, meanwhile, was seen as slower, riskier, and harder to scale.
Physical products required factories, supply chains, inventory, logistics, certification, and long development cycles. Software ate the world because software could iterate infinitely faster.
Hardware teams now operate with the speed, agility, and iteration cycles traditionally associated with software companies. Investors and governments are paying attention. And enterprises are rethinking the strategic importance of building and controlling physical systems.
The AI boom embodies this shift. AI may feel like a software story on the surface, but underneath it’s fundamentally a hardware story, driving massive investment into semiconductors, infrastructure, robotics, and next-generation physical systems.
Why is hardware getting so much attention?
Part of the renewed interest in hardware comes from a simple reality: physical products are still much harder to replicate than software.
Software is being upended by LLMs. Code generation, prototyping, and full application development can now happen at speed not seen before. Entire classes of software products can be recreated or imitated quickly, meaning that the barriers to entry in software are falling faster than ever.
But hardware is different. Producing a physical product still requires deep operational coordination across engineering, manufacturing, sourcing, testing, compliance, and logistics.
Even with AI accelerating design workflows, physical systems remain constrained by atoms, not just bits. You cannot prompt a supply chain into existence overnight, nor can you instantly replicate manufacturing expertise, supplier relationships, or production infrastructure.
This is one reason investors are becoming increasingly interested in hardware-enabled businesses. Deloitte optimistically forecasts a $400 billion investment in AI chips alone by 2027.
Why hardware is the new software
Hardware companies are adopting software-style operating models that truly do make them resemble each other. Traditionally, the hardware development lifecycle followed rigid, sequential processes.
Teams spent years designing products before release. Changes late in the cycle were expensive, feedback loops were slow, and manufacturing handoffs often happened only after engineering was effectively “done.”
But today, mechanical, electrical, firmware, manufacturing, and supply chain teams increasingly work concurrently rather than sequentially. This mirrors how modern software organizations evolved years ago through agile development and DevOps.
How hardware became software-esque
Vehicles, industrial systems, medical devices, robotics platforms, and consumer electronics are increasingly defined by their ability to receive updates after deployment.
Firmware, embedded systems, and microcode updates now play a central role in product evolution. Microsoft explored how low-level system infrastructure supports software-like adaptability and dynamic reconfiguration.
The distinction between “shipping hardware” and “shipping software” is becoming blurry because products are no longer static once deployed. Hardware teams now collect operational data continuously and feed it directly back into development cycles. Physical products are starting to behave like continuously evolving software platforms.
What does this mean for hardware engineers?
Hardware engineers now need to think about firmware constraints earlier in the design cycle. Electrical teams are collaborating more closely with supply chain and manufacturing partners long before a design is finalized.
Embedded software teams increasingly influence hardware architecture decisions because products are expected to evolve long after shipment through updates and connected services.
That means iteration cycles are getting tighter. Prototype feedback loops that once took months are now compressed into weeks or even days. Engineers are expected to validate designs faster, respond to changing requirements more quickly, and coordinate constantly across distributed teams.
Hardware development is becoming less about handing work downstream and more about continuous synchronization across the entire product lifecycle.
The growing overlap between hardware and software is also reshaping engineering careers themselves. Today, a hardware engineer is increasingly part systems engineer, part operations coordinator, and part software collaborator.
This is why it’s such a good time to be a hardware engineer right now.
How PLM provides software-like hardware
The faster teams move, the more important operational synchronization becomes, especially as hardware and software organizations converge and begin to operate as interconnected parts of the same development process.
Without a shared system of record, coordination typically breaks down quickly leading to errors and missed deadlines.
Traditional PLM systems were often designed for slower, sequential development models. But agile hardware development requires real-time collaboration across distributed teams.
That’s exactly why Duro was rebuilt around the reality that hardware development no longer follows old workflows. Teams need systems that allow all stakeholders to move together in real time and for their product data to stay connected, accessible, and synchronized across the organization.
Duro is for the new generation of hardware teams that operate like software companies. They move faster. They iterate continuously. They deploy updates. They run parallel workflows. They rely on data-driven feedback loops. And they require operational systems capable of supporting that speed.
If this sounds like your team, we’d love to hear from you.