The Engineer Helping Shape GM’s Software-Defined Future
When General Motors began its decisive shift toward software-defined vehicle (SDV) engineering, the transformation did not start with a dramatic announcement or a single breakthrough technology. It began quietly, through engineers who understood that the future of mobility would be written in code, models, data, and systems thinking long before it appeared on the road. Laura Barlow was one of those engineers.
She was not waiting for the industry to catch up. While the automotive world was still balancing traditional hardware-first development, Barlow was already laying the technical groundwork that would later become essential to GM’s SDV strategy. Her career reflects not just personal growth, but the evolution of GM itself—moving steadily from component-centric engineering toward an integrated, software-led vehicle architecture.
From electrification to autonomy, from physical testing to virtual validation, Barlow’s path mirrors the company’s broader journey: start with precision, scale deliberately, and build the future before it becomes obvious.
Early Foundations in Electrification
Barlow’s career at GM began in electrification, a space that demanded a deep understanding of how complex systems behave under real-world conditions. Working on the Chevrolet Volt program, she focused on diagnostics—an area often underestimated but critical to vehicle reliability and performance.
Diagnostics required her to think holistically. It wasn’t enough to understand individual components; she needed to know how subsystems interacted, how faults propagated, and how software and hardware responded under stress. The Volt program, as one of GM’s early electrification flagships, exposed her to the intricacies of battery systems, power electronics, control logic, and the challenges of integrating emerging technologies into production vehicles.
This early experience shaped her engineering mindset. It trained her to anticipate failure modes, trace root causes, and design systems that could communicate their own health clearly and accurately. Those instincts would later become invaluable as GM expanded into autonomy and software-defined platforms.
Building Technical Depth Through HiL and Algorithm Engineering
After electrification, Barlow moved into Hardware-in-the-Loop (HiL) testing and algorithm engineering. This transition marked a shift from observing system behavior to actively shaping it.
HiL environments allowed her to test control software against simulated hardware, exposing issues that would otherwise appear much later in development. It was here that Barlow deepened her understanding of control theory, real-time systems, and verification workflows. She learned how algorithms behaved not just in ideal conditions, but when confronted with timing constraints, sensor noise, and edge cases.
This phase strengthened her ability to bridge theory and practice. Algorithms were no longer abstract logic; they were living components within tightly coupled systems. The experience sharpened her attention to detail and reinforced the importance of early validation—an idea that would later define her approach to SDV development.
Entering Autonomy at the Canadian Technical Centre
Barlow’s next move placed her at the center of GM’s growing autonomy efforts. At the Canadian Technical Centre, she joined as a Controls Specialist just as advanced driver assistance systems and autonomous vehicle development were accelerating.
At the time, the team was small and the scope was expansive. With only one other engineer, Barlow was tasked with mapping system behavior, identifying issues early in the development cycle, and building processes that could scale alongside the technology.
There was no established playbook. The work demanded both technical rigor and creative problem-solving. Barlow helped define how systems interacted, how data flowed across domains, and how early-stage issues could be surfaced before they became costly failures.
This was foundational work—quiet, meticulous, and often invisible outside engineering circles. Yet it was essential. The frameworks and insights developed during this period would later be adopted and expanded across GM’s vehicle programs.
Scaling Capability as Ambitions Grew
As GM’s autonomy ambitions expanded, so did the engineering organization supporting them. What began as a two-person effort grew into six specialized groups focused on diagnostics, mapping, lateral controls, and autonomous vehicle infrastructure.
For Barlow, this period was defined by scale. Scaling wasn’t just about adding people; it required refining workflows, standardizing tools, and ensuring that new engineers could contribute effectively without slowing momentum.
The pace was intense, but energizing. Each iteration brought clearer processes, more robust toolchains, and stronger collaboration across teams. Barlow saw firsthand how thoughtful system design could enable faster development without sacrificing quality.
This phase reinforced a core belief: sustainable innovation depends on infrastructure. Without scalable systems and clear engineering practices, even the most advanced technology struggles to reach its potential.
Advancing Virtual Development and Thermal Modeling
That belief guided Barlow into her next chapter—advanced controls and virtual development. As vehicles became more software-driven, GM increasingly relied on model-based design, model-in-the-loop (MiL) verification, and simulation to shift problem discovery earlier in the lifecycle.
The objective was straightforward in theory: identify failures before hardware was built. In practice, achieving this required precision, alignment across teams, and a cultural shift in how engineering success was measured.
Barlow played a key role in evolving GM’s thermal simulation capabilities. She helped enable software to be tested on virtual Electronic Control Units (ECUs) embedded within detailed thermal vehicle models. This allowed engineers to validate control strategies, thermal performance, and failure responses long before physical components were available.
The impact was significant. Virtual development reduced iteration time, improved predictability, and made debugging more systematic. It also encouraged a mindset closer to modern software development—continuous testing, rapid feedback, and early integration.
This work represented more than a technical milestone. It signaled GM’s transition toward development cycles that resembled continuous delivery rather than traditional automotive timelines.
Engineering in a Software-Defined World
Today, Barlow works within GM’s Data Engineering organization, where her focus has expanded to embedded systems that transform vehicle data into actionable insight. Whether tuning algorithms, shaping thermal strategies, or refining validation pipelines, her work centers on building systems that scale and empower engineers.
Software-defined vehicles, in her view, are not just about new features or architectures. They represent a fundamental shift in how vehicles are conceived, developed, and maintained. Diagnostics, modeling, virtual testing, CI/CD pipelines, and cross-domain collaboration are no longer optional—they form the backbone of modern automotive engineering.
Barlow has helped build many of these foundations. The systems she contributed to now enable faster development cycles, clearer visibility into vehicle behavior, and more resilient architectures capable of evolving long after vehicles leave the factory.
Looking Ahead: Converging Virtual and Embedded Systems
As automation deepens and simulation grows more sophisticated, Barlow sees virtual and embedded systems converging even further. The boundary between software and hardware is dissolving, replaced by tightly integrated platforms where data, models, and code evolve together.
In this future, engineers won’t choose between virtual or physical development—they’ll operate across both seamlessly. Issues will be identified earlier, updates will be deployed faster, and vehicles will continuously improve through software.
For Barlow, this is the culmination of years of foundational work. From early diagnostics on the Volt to virtual thermal vehicles and SDV data systems, each chapter has contributed to a larger vision.
Software and hardware are no longer separate lanes. They are part of one coordinated engine—one that is redefining how GM builds vehicles for the next generation.
Source Link:https://news.gm.com/
