Why Simplicity Trumps Complexity in Engineering

The Power of Engineering Thinking Engineering isn’t just about machines or code it’s about problem-solving. Every bridge we cross, every app we use, every drop of clean water we drink all exist because an engineer decided to solve a real-world problem. What makes engineers different isn’t just technical skill, but the mindset: Breaking big problems into small, solvable steps Testing, failing, and improving Building things that make life better Whether you’re designing circuits or systems, remember you’re not just building things, you’re building possibilities. #Engineering #Innovation #STEM #ProblemSolving #Technology

Design isn’t optional. It’s the tradeoff you’ll pay for with bugs later. Skipping design now feels faster - but it costs hours of debugging later. In embedded & systems engineering, 9 out of 10 real issues come from unclear flow, not bad code. A quick state-machine sketch or a tiny sequence diagram can avoid massive rework down the line. When I started doing this seriously, my debugging time dropped significantly. I realized building without design is like sailing without a map. What’s one design habit you swear by before writing code? Share it — it might help someone save 10× the time later. #EmbeddedEngineering #SoftwareDesign #EngineeringMindset #TechLeadership

“It’s easier to change in software” — true, but as Christopher Mallinson points out, that mindset often backfires. The “10X rule of quality” reminds us: the longer you wait to fix an issue, the harder (and costlier) it gets. Bringing mechanical, electrical, firmware, and software teams together early isn’t a luxury, it’s smart engineering. #EngineeringLeadership #Collaboration #ProductDevelopment #AgileThinking #Innovation

The "Blueprint" - From "Idea" to "Specification" What’s better than a 100-page spec document? A spec you can actually run.  Every chip starts as an "Idea." But to become a product, that idea must be evaluated (market fit, technical feasibility) and turned into a solid "Specification." This spec defines features, power, performance, and cost (PPA). This is where Model-Based System Engineering (MBSE) shines. Instead of static documents, we build executable models that become the "single source of truth," allowing us to validate our assumptions.  A "runnable" spec ensures all teams (HW, SW, and validation) are building to the same, validated plan before the expensive design work starts. Have you ever been caught by a vague or outdated spec? How could an "executable" model have helped?

The best engineers don’t build faster — they think clearer. Speed means nothing if you’re running in the wrong direction. And yet, most engineering teams still confuse velocity with progress. Every failed project I’ve seen had one thing in common: teams moving fast without understanding the same problem. Go horse style. People weren’t unqualified — they were misaligned. And alignment isn’t created by working harder; it’s created by thinking clearer. Clarity is not slowness. It’s precision in motion. The best engineers I’ve ever met are not the ones who rush to build — they’re the ones who pause to make sure everyone is seeing the same system before anyone touches it. They design alignment before they design hardware. They synchronize meaning before they synchronize signals. That’s what separates builders from system thinkers. The first create parts. The second create predictability. 🧠 Engineering isn’t just about speed. It’s about directed speed — and clarity is what gives direction to every technical decision. As highlighted by Lukosevicius (2017) in “Characterization of complexity in engineering projects”, the more complex a system becomes, the greater the cost of semantic misalignment. When understanding diverges, complexity amplifies — and no amount of effort compensates for lost clarity. The future doesn’t need faster engineers. It needs clearer ones. #SystemsEngineering #MBSE #ComplexSystems #EngineeringLeadership #ClarityBeforeAction #SynthesisFramework

“A year ago I wrote about how I didn’t want to be the person chasing after the tractor — and since then, AI has become the engine driving my consulting work. From firmware generation to automated test documentation, the tools have matured, but the real value still comes from knowing how to guide them. My focus this year has been building context-driven engineering systems that let small teams do big things. If your product team could use that kind of horsepower, let’s connect.”

Prompt Engineering ≠ Guesswork Prompt engineering isn’t magic. It’s iterative input design to reshape probability distributions. Small changes in wording—or even whitespace—can radically alter a model’s output.

⏱️ How long does it really take to bring an embedded system from concept to production? It’s a question every product leader asks — and the answer surprises most. In our latest blog, Fidus explains what realistic development timelines look like when partnering with an embedded systems design services company — and how structured processes, transparent communication, and multidisciplinary collaboration accelerate success without cutting corners. ⚙️ Learn what drives timelines. 🧭 See how experienced design partners compress them. ✅ Build confidence in every stage of development. 👉 Read the full article: https://lnkd.in/eAg6P-BX #EmbeddedSystems #DesignServices #HardwareDesign #ProductDevelopment #EngineeringDesign #FPGA #EmbeddedSoftware #FidusSystems

Overengineering is just the other side of underpreparation. Some companies fall behind because they never invested in the tech they needed. Others fall behind despite investing because they chase complexity, not clarity. One ignores tech until it’s too late. The other builds systems no one asked for. Yet, neither wins. So, who are the team that do win? They’re the ones that obsess over the problem, not the stack. And, the ones that know when to pick structure over scale, and simplicity over pride.

What Prompt Engineering in 2025 Actually Looks Like (When You’re Trying to Build for Real) I've been reading a lot about how prompt engineering has evolved — not in the "let's hype it up" way, but in the actually-building-things way. A few things have stood out to me about where we are in 2025 👇 Prompt engineering is turning into product behavior design. You're not just writing clever instructions anymore — you're architecting how your system thinks, responds, and scales. The structure, schema, and even sampling parameters decide how your system behaves: accuracy, reasoning, latency, all of it. Think of it like API design. You're defining contracts, handling edge cases, optimizing for different use cases. The prompt is your interface layer. "Works once" isn't enough. You have to test prompts across edge cases, personas, messy user data. That's when you see where it breaks. Cherry-picked demos hide the gaps. Real evaluation reveals: How it handles ambiguous inputs Whether it maintains consistency across variations Where it confidently hallucinates Performance degradation un https://lnkd.in/g_KHq_cS