🔍 TL;DR
We don’t always get to build systems from scratch. Most of the time, we work inside legacy automation systems—inheriting decisions, fixing what’s fragile, and learning what really holds them up.
This post shares five lessons shaped by years inside other people’s systems—and how they influence the way we build today.
Five lessons learned from years inside legacy automation systems, and how they shape the way we build today.
As control system integrators, we’re usually not the first ones in the room.
By the time we’re brought in, the system already has a history. In most cases, we’re working within legacy automation systems; decisions have been made, hardware is in place, and priorities are set. We work within that reality: legacy infrastructure, tight timelines, shifting objectives. Often, we don’t have the final say. We make recommendations, but we don’t always get to decide what gets implemented.
That’s what we’re brought in to do, to support the system as it stands, and the people who rely on it.
But it does make you think.
When you spend enough time inside other people’s systems—figuring out how to make things work and navigate limitations—you start to notice patterns. You see which choices last over time, which ones quietly cause friction, and where a different decision might have made things easier later on. Not because someone made a mistake, but because experience gives a clearer view in hindsight.
We don’t always get to influence the direction of a system. But when we do, we bring with us the lessons shaped by years of working in environments where those decisions had already been made.
This post isn’t a how-to or a critique. It’s a reflection—five lessons that have shaped the way we work and how we think about doing better next time.
1. Standardization solves more problems than it creates
It’s easy to let flexibility take over, naming a few tags differently, adjusting a screen here, or making one exception in a PLC routine. It works in the moment, until years later, when no one remembers why that one loop behaves just a little differently.
We’ve seen how much time gets lost to inconsistency. Not because anyone made a bad decision, but because no one had the time, documentation, or structure to keep things aligned.
Standardization isn’t about rigidity; it’s about resilience. It keeps systems maintainable as teams change. It helps new engineers ramp up faster. And it means the next person won’t have to dig through layers of guesswork to find answers.
We advocate for naming conventions, reusable templates, and clean logic. Not just because they’re “best practices,” but because we’ve lived through what happens without them.
2. Design with the Next Person in Mind
Most automation systems outlast the people who built them. We’ve walked into plants where no one on the current team wrote any of the code that’s still running production. No one remembers why certain choices were made. And when something breaks, figuring it out becomes detective work.
It’s not anyone’s fault; teams change, and people move on. However, when systems aren’t designed with future users in mind, every handoff becomes more difficult, and every fix takes longer.
We’ve learned that clarity fosters trust. Well-organized code, easy-to-find documentation, and an intuitive structure not only support the system but also help those who rely on it.
Even a few additional notes in a comment block or a consistent tag structure can make the difference between confusion and confidence.
3. It’s the last-minute changes that get you
We’ve been on startups where commissioning and debugging occur simultaneously. Where something changed last-minute and didn’t behave as expected, and where the system isn’t quite ready, but the schedule won’t budge.
We understand why it happens. Simulation and testing get cut when timelines are tight. However, we’ve also seen how early testing can change everything.
Even basic virtual commissioning allows you to catch logic issues before hardware is involved. It gives operators a head start and creates space for refinement, not recovery.
We push for it whenever possible. Not to drag out the project, but to shorten the part everyone dreads. Because when a system goes live, it shouldn’t be the first time it’s been asked to work.
4. Fix What You Can Before It Breaks
We’ve worked on systems that were held together through effort, not certainty. That’s often the case with legacy automation systems; they appear stable on the surface, but are vulnerable underneath.
Controllers past their support window. Operating systems are approaching obsolescence. Network hardware is one reboot away from trouble. No one is ignoring the risk—it’s just that in most facilities, other priorities take precedence.
There’s always something louder. Something more immediate. As long as the system continues to run, it’s challenging to make the case for upgrading.
But we’ve learned to pay attention to the subtle signs:
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- Backups are inconsistent
- Hardware sourcing becomes a scavenger hunt
- People start saying, “let’s not touch that unless we have to.”
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Those are the cues that a system is slipping into reactive mode, even if nothing has failed yet.
We’ve learned that being proactive doesn’t have to mean an overhaul. It can involve documenting aging components, creating a phased roadmap, and aligning technical risk with business reality, before failure chooses for you.
Since most people aren’t waiting for things to break, they’re simply doing their best with a long list of priorities. Our role is to make space for what may not always seem urgent but is just as important.
5. Trust isn’t built with features, it’s built over time
We’ve seen systems that functioned technically, but people stopped trusting them.
Maybe a tank level didn’t match the field readout. Maybe alarms went off for no reason—again. Perhaps a tag was marked as “uncertain” during a critical moment.
When that happens, people start relying on workarounds. They ignore alarms, manually double-check everything, and treat the automation as a suggestion rather than a system.
We’ve learned that trust is built when the system behaves the way it should, every time. It’s built on accuracy, reliability, and consistency. And once it’s broken, it takes a long time to earn back.
So now, we pay close attention to the details that shape trust. Not just whether logic works, but whether people believe in it enough to use it.
Because a trusted system is one that gets used, and a used system is one that delivers value.
We Didn’t Learn These Lessons in a Classroom
Everything we just shared came from years spent inside other people’s systems.
We didn’t always set the constraints or make the calls, but we were there, figuring out how to make things work under pressure. Over time, specific patterns became apparent. Not just in how systems were built, but in how they aged. How they held up. Where they built trust—and where they quietly eroded it.
These aren’t hard rules. They’re habits we’ve developed. Priorities we bring to every project, whether we’re starting fresh or building on years of accumulated history.
Ready to Reset?
We don’t claim to have all the answers. But we’ve seen what works—and what causes slow, expensive problems down the road.
If your system feels like it’s been shaped by layers of decisions over time, you’re not alone.
Let’s talk about how to bring clarity, consistency, and confidence to what comes next.
📩 Reach out to our team or download our free Automation Lifecycle Planning Workbook to start mapping out the future of your system—one decision at a time.
