The Difference Between a Hobbyist and a Hirable Embedded Systems Engineer

If you spend enough time around makerspaces, hackathons, or online embedded communities (including my own courses), you’ll see a lot of impressive projects: custom keyboards, home automation systems, robot cars, sensor networks, and beautiful PCBs. That being said, when it comes time to hire for an embedded engineering role, companies still struggle to find candidates who are truly ready.

This isn’t a knock on hobbyists. In fact, hobbyists are the lifeblood of the embedded world. Most of us started there, and there are plenty of areas where I’m still only at the hobby level! Curiosity and hands-on experimentation are how people enter this field, and they’re still one of the best ways to learn.

But there’s a real, meaningful gap between being good at building projects for yourself and being someone a company can trust to ship code into a product that thousands, or even millions, of people will depend on. I want to talk about that gap: not to discourage anyone, but to make it visible.

One of the biggest differences is the definition of success. A hobbyist’s primary goal is usually simple: make it work. The vast majority of my own projects fall into this category! I often just need something to work on camera so I can teach a concept.

Reliable, Robust Products

In a professional environment, though, “it works” is just the starting point (e.g. a prototype). A hirable embedded engineer has to think in terms of reliability. What happens if the device loses power in the middle of writing to flash? What happens if a sensor occasionally returns garbage values? What happens when the system has been running for six months straight? What happens when the network drops for an hour, or a user presses buttons in a strange order?

In a hobby project, if something crashes, you reboot it. If it locks up, you power cycle. If it behaves strangely, you might shrug, learn what you can, and move on to the next idea. In a robust product, those same failures become support tickets, returns, lost revenue, and sometimes safety risks. Hirable engineers assume things will go wrong and design for that reality from the beginning.

The natural follow-up question is: how do you actually get better at building reliable systems? Unfortunately, there isn’t a single course or book that magically teaches robustness. It’s more like a muscle you build over time by seeing what breaks and learning to anticipate those failures earlier and earlier in the design process.

One of the best ways to start is simply to let your projects run longer. Instead of celebrating when something works once, try one (or more) of the following:

• Let it run for a week
• Power cycle it randomly
• Unplug sensors
• Inject bad inputs
• Fill up buffers and look for overflows
• Simulate poor network conditions

A lot of reliability problems don’t show up in the first five minutes. Rather, they show up after hours of operation, when memory fragments, counters overflow, or edge cases quietly accumulate. Just exposing your projects to time and stress will teach you more than another tutorial ever will.

It also helps to shift how you think about failure. In hobby projects, failure feels like a setback. In professional engineering, failure is information. If a system crashes, the question becomes: can I detect that it happened? Can I recover safely? Can I prevent it next time? You start thinking about watchdog timers, safe defaults, retries, sanity checks, and logging not as “extra work,” but as part of the design.

Learning Beyond Tutorials

Online tutorials and videos are incredible resources for getting started, as they can teach you how to wire up hardware, structure a simple project, and start using an SDK. They provide a clear path toward a satisfying outcome.

But tutorials are controlled environments, as everything is pre-selected with curated steps and libraries. Real projects rarely look like that, as you often need to start working outside the bounds of such tutorials where library versions don’t match, APIs have changed, timing issues start to show up, and memory runs out.

A hobbyist might say, “I followed the steps and it doesn’t work,” whereas a hireable engineer says, “Let me figure out why.” That shift is subtle but important. It means getting comfortable reading logs, stepping through code, inspecting registers, measuring signals, and narrowing a problem down until the root cause becomes visible. Companies don’t hire people who can only follow instructions. They hire people who can solve problems when there are no instructions.

As a personal aside, I’m well aware of my position as an online course and tutorial creator. I try to make learning as accessible as possible and to provide insight into the code where I can. But it’s still on you, the learner, to dig deeper and understand what makes a system tick.

Code Formality

The way code is written also tends to evolve. When you’re building something for yourself, speed is often the most important factor, as you just need it to work and you can troubleshoot the project yourself when issues arise. Hardcoding, copy-pasting chunks of code, assuming AI output is correct, and a little bit of spaghetti code is often “good enough.”

In a professional setting, though, someone else will have to read your code. You’ll likely work on a team, and you’ll need to be OK with a senior engineer reviewing your work (feedback can be painful, but it’s one of the fastest ways to grow). Writing well-documented, readable code is also the mark of a professional developer, as they know others (or their future self!) will need to understand their programs.

Many professional shops now rely on test-driven development, even for embedded code. In my experience, this often means writing more code for test harnesses and test cases than actual production code! 

Communication

Another difference that often gets overlooked is communication. A lot of hobby projects are solo efforts, which means you get to make all the decisions, including how to structure the code and when the project is done.

Professional engineering is rarely like that. You’re working with hardware engineers, firmware teammates, backend developers, product managers, and QA teams. This means in addition to writing efficient, robust, and readable code, you need to be good at explaining tradeoffs to stakeholders, documenting decisions, asking good questions, and providing realistic expectations to managers. Engineers who communicate clearly make everyone around them more effective, and that’s something companies value just as much as technical skill. Don’t neglect the “soft skills.” They matter more than most people expect.

Leveling Up

You don’t need to stop being a hobbyist. In fact, the curiosity and creativity that come from hobby work are huge strengths. Many great engineers never lose that mindset. But you can start shifting how you approach your projects. Instead of just making something work, try making it resilient. For example: add basic error handling, let it run overnight, see what breaks, then dig in and understand why it failed.

Another way to grow in this area is to study mature codebases (if you’re able to get your hands on in-house production code or good open source projects). Look at how production SDKs and RTOS examples handle errors. Notice how often they check return values, retry operations, or fail gracefully. You’ll start to see patterns emerge. Professional firmware is full of small defensive decisions that you might not think to add on your own at first. Here are some embedded codebases I recommend digging into:

• Zephyr RTOS
• FreeRTOS
• lwIP
• Linux kernel drivers

Even just reading through how these projects handle errors and edge cases can teach you a lot about what production-quality firmware looks like.

There are certainly resources that help accelerate this learning. Books and material on embedded systems design, real-time systems, and defensive programming can provide a vocabulary for problems you’ve already started to notice. Topics like state machines, memory management, fault tolerance, and concurrency come up again and again in real products. But most of that material really sticks only after you’ve seen a system behave badly in the real world. The theory gives you names for the problems; experience teaches you when they matter.

Here are some books I recommend checking out if you really want to move beyond the hobbyist level and dig deeper into embedded systems, programming, and system architectures:

• Making Embedded Systems by Elecia White
• Programming Embedded Systems In C and C++ by Michael Barr
• Embedded C Coding Standard by Michael Barr
• Test-Driven Development for Embedded C by James Grenning
• Embedded Systems with ARM Cortex-M Microcontrollers in Assembly Language and C by Yifeng Zhu (great for digging into Cortex-M internals)
• Embedded Systems Architecture by Daniele Lacamera
• Mastering Embedded Linux Programming by Chris Simmonds (for embedded Linux)

Look for opportunities to work on a team, such as by contributing to a larger open source project. You’ll be forced to interact with other people and have senior developers review your code. You can also look for projects that interact with real users. When someone else depends on your system, your priorities change. A rare crash is not something that can be brushed off with a quick reset. It becomes a problem that needs to be understood and fixed. That pressure forces you to think more carefully about edge cases, testing, and long-term behavior.

In the end, becoming someone who builds reliable products isn’t just about memorizing best practices. Rather, it becomes about developing instincts. You start to anticipate where things might fail. You start to ask “what if?” earlier in the design, and over time, those small decisions add up to systems that don’t just work once, but keep working long after the demo is over.

That’s really the difference between a hobbyist and a hirable engineer: not intelligence or talent, but the habits you build over time.