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title: "Platform Engineering: Finding the Harmonics in the Noise" date: "2025-02-27" "2026-02-10" description: How platform engineering turns noise into clarity and chaos into scalable systems
Platform Engineering: Finding the Harmonics in the Noise
Building an efficient engineering platform is a lot like discovering harmonics in noise—those underlying patterns that make order possible. In mathematics, the Fourier Transform is a favorite example of mine: it takes what seems like a messy, complex signal and reveals its building blocks. Suddenly, clarity emerges from the chaos.
Platform engineering serves a similar role in software. By creating the right abstractions and refining underlying systems, we surface the signal that allows teams to innovate faster and reduce friction. This focus on what truly drives impact transforms engineering from reactive problem-solving into a foundation for scalable creativity and efficiency.
What the Noise Looks Like
Before effective platform engineering, organizations experience characteristic patterns: developers asking the same deployment questions repeatedly, each team solving authentication differently, incidents revealing that nobody quite knows how the pieces fit together. This isn't incompetence—it's the natural state when systems grow faster than the abstractions that could make them coherent.
The signal is there, buried in the noise. Teams are deploying successfully. Security is being handled. Observability does exist. But each implementation is slightly different, and knowledge is tribal. Cognitive load accumulates until even simple changes require heroic effort.
Finding the Harmonics
The Fourier Transform works because complex signals can be decomposed into simpler, fundamental frequencies. Platform engineering works the same way: you identify the repeated patterns—the "fundamental frequencies" of your engineering organization—and build abstractions that make them first-class.
This might mean:
- Recognizing that five teams independently built deployment pipelines, then creating a standardized workflow that captures what they learned
- Noticing that incident response always follows the same arc of confusion, then building observability that surfaces the critical path immediately
- Observing that onboarding takes weeks because knowledge is scattered, then creating golden path documentation that reveals the essential structure
The distinction between signal and noise matters. Not every pattern deserves a platform. Some variation is healthy—teams should experiment. But when you see the same fundamental challenge solved six different ways, you've found a harmonic worth amplifying.
The Tuning Process
Platform engineering is never done—it's an ongoing practice of tuning and refining what works. This is where the neuroscience background serves me well: systems that support human cognition need constant calibration.
What worked for 30 engineers may create friction at 100. The abstractions that seemed elegant initially might obscure important details as complexity grows. Good platform engineering requires the humility to recognize when yesterday's solution has become today's noise, and the discipline to refactor accordingly.
I've seen this pattern repeatedly: a platform team builds something brilliant, but it doesn't get adopted because it requires developers to change their mental models too drastically. The harmonics are right, but the interface creates dissonance. Effective platforms meet engineers where they are, then gradually reveal deeper structure.
The Exchange of Signals
The most rewarding part of exploring platform engineering is the exchange—sharing lessons from my own journey while learning from others who have wrestled with the same challenges. Each perspective uncovers another frequency in the signal, helping us see the universal patterns behind resilient and adaptable platforms.
One engineering leader recently described their observability platform as "teaching the system to explain itself." Another talked about their CI/CD pipeline as "removing decision points that don't matter so we can focus on the ones that do." These aren't just technical achievements—they're insights about how to reduce cognitive load and create space for higher-order thinking.
Creating Conditions for Emergence
At its best, platform engineering reveals the harmonics that help teams move with clarity and impact. But the deeper insight is this: you can't predict every pattern that will emerge once you remove friction. When deployment goes from hours to minutes, teams don't just deploy more—they experiment differently. When observability makes the system legible, debugging becomes hypothesis-driven rather than archeological.
The more I explore this space, the more I'm convinced that platform engineering isn't just about technology—it's about creating the conditions for emergence. The platforms I've built that had the most impact weren't the ones with the most capabilities. They were the ones that removed just enough friction that teams discovered new possibilities we never anticipated.
That's the ultimate harmonic: when your platform becomes the foundation for innovation you couldn't have designed yourself.