Tyler Lee

Senior hardware engineers are consistently the hardest roles to fill in the industry. It’s not just a numbers problem. These roles require people who’ve seen programs go right and wrong and can design for real-world constraints. A lot of engineers have depth in one area, but fewer have full lifecycle experience from design through test, manufacturing, and deployment. That experience is earned through experience, not taught, and it takes time. As companies moves faster and teams get leaner, the demand for that level of judgment keeps going up. And there simply aren’t enough people who’ve been through it before.

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The software engineering abilities of LLMs are accelerating at a phenomenal pace. Anthropic have recently released Opus 4.6. As a demonstration of the capabilities of Opus 4.6 Anthropic have today published an article and video on a Claude Code Agent Team building a GNU C compiler from scratch that can target multiple architectures (x86-64, ARM, RISC-V) with the end result passing the GCC Torture Test Suite. This did cost $20,000 in token API calls running 2000 concurrent Claude Code sessions. As the author of the article concludes, nobody expected to LLMs to be capable of doing anything close to this in 2026 and, quote, "we’re entering a new world which will require new strategies to navigate safely". I agree https://lnkd.in/erBmxD6m

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One thing that I can say after years of being a GN&C engineer is that we don’t talk enough about research culture that GN&C work should operate in. Guidance, Navigation, and Control is extremely critical to every spacecraft yet our design and development workflows often feel frozen and old Rather than enabling rapid iteration, scalable testing, or continuous refinement, most GN&C environments are locked into a familiar grind: - Wrestling with legacy tools - Manually stitching together configs, data flows, and simulations - Building fragile test environments that require significant overhead to support new models or large scenario sets - Navigating fragmented requirements with poor traceability What’s missing I think is a system that empowers research and rapid experimentation a culture where an engineer can try bold ideas without spending a week setting up the infrastructure first. Today, experimenting with new control models or estimation architectures often takes disproportionate effort just to set up and validate. We talk about robustness but not agility. We document assumptions but rarely challenge them at scale. Compare that with how modern software teams operate: modular, iterative, reproducible, and continuously learning. GN&C needs that same spirit not just to maintain safety, but to accelerate progress. GN&C deserves to be a creative, fast-moving R&D field not a slow-moving chain of manual workflows and static configs. Curious to hear from others: What’s the biggest barrier to GN&C innovation you’ve encountered? #GNandC #AerospaceEngineering #SpaceTech #SystemsEngineering #FlightSoftware #AutonomousSystems #Simulation #EngineeringCulture #Innovation #ModelBasedDesign #SpaceR&D #nasa

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Quantum is now. Not theoretical. Not someday. It’s hardware. System integration. Precision engineering operating at the edge of physics. At IonQ, we’re building full quantum systems — machines that have to perform, scale, and ship. If you’ve built high-performance hardware, advanced controls, photonics, cryogenics, or other precision systems — or led complex deep-tech product, program, or integration efforts — you know the level of discipline this takes. If you’re already building in this space — or ready to — and want to operate where quantum becomes real infrastructure, reach out.

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If you think you need a job at SpaceX to start building space hardware, you’re wrong.    If you're serious about engineering for the space industry, these free tools can help you along the way.    PCB Design & Schematic:   KiCad- professional-grade, open-source, widely respected in aerospace. EasyEDA-  simple, fast, and ideal for prototyping. Simulation:  LTspice- perfect for analog, power systems, and signal conditioning.  Falstad- great for learning, control logic, and concept iteration.   There are more free tools out there but is there any tool that you would add to the list that helped you?  Lets help others looking to get into the industry and drop the tools in the comments below. 

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I’ve been getting back into hands-on mission design learning recently, revisiting astrodynamics, orbit determination, and the kind of tooling that actually scales beyond textbook problems. That’s when I stumbled upon Nyx Space and their open astrodynamics stack. At first glance, what stood out was the engineering discipline: • Computationally efficient libraries • Clean APIs • Designed for modern workflows, not legacy pipelines • Rust at the core, with sensible bindings for practical use As someone who has dealt with Monte Carlo runs, batch analysis, and concurrency pain points, the performance and thread-safety focus immediately made sense. This feels like software built for today’s constellation-scale thinking, not just single-mission analysis. Then I looked closer at the licensing. Nyx Space uses a strong copyleft model (AGPL-style), and that changed how I viewed the whole ecosystem. This isn’t just an open-source checkbox. Copyleft actively shapes behavior: • If you improve the core, those improvements flow back • Hosted or internal use doesn’t quietly bypass sharing • Fork-and-lock strategies become harder to justify • Collaboration becomes the default, not an afterthought In a field like space mission design, where correctness, edge cases, and domain knowledge accumulate slowly and painfully, this creates an interesting dynamic. Instead of fragmented internal tools and proprietary silos, the system nudges engineers toward shared foundations and upstream contribution. It’s a very different incentive structure compared to permissive licenses, and arguably closer to how we already collaborate informally across missions, papers, and reference models. Curious to hear from others: Have you worked with copyleft licensing before? How do you see its implications for aerospace and space software adoption? Could this kind of licensing model enable a more genuinely collaborative industry framework, or does it introduce friction for commercial programs? Would love to hear perspectives, especially from folks building or operating mission software today.

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