I find what's not working, fix it at the root, and build the team the business can bet on.
"I had the pleasure of both hiring and managing Tyler at Trudell Medical International. He is a unique character with wide skills that would contribute greatly in any company. I was massively impressed by his ability to juggle a multitude of projects and responsibilities in a growing software development team.
I would not hesitate to hire Tyler again — and rely heavily on him for Project Management, Documentation, Quality Engineering and several other areas. Truly a strong generalist who takes responsibility for tasks — and delivers."
Rehab devices moved the limb on fixed trajectories. We built one controlled by the patient's own muscles.
Designed real-time embedded control systems that read EMG signals directly from the patient's arm to drive a wearable mechatronic elbow brace. The device detected muscle intent and assisted the motion the patient was initiating.
Deep brain stimulation was too risky. Medication wasn't enough. We proved a third path existed.
Designed and built a wearable functional electrical stimulation system that adaptively suppressed tremor. Validated the hypothesis and changed what was considered possible.
Every wearable research project was rebuilding the same embedded control infrastructure from scratch.
Built WearMECS, a production-grade open-source embedded control framework. Enables experimentation and evolution of wearable control systems.
Every hardware vendor integration was manual, slow, and bottlenecked on our team.
Built a Python-based automated validation platform that made partner certification fully self-serve. Removed the team as a dependency entirely. 20+ vendors integrated without a queue.
The team was moving fast, things were breaking, and we had no way to see the full picture.
Built a data pipeline that pulled defect metrics from Jira and test results from GitHub Actions, processed them through AWS, and surfaced everything in a QuickSight dashboard. Quality health became visible across the entire organization for the first time.
Manual testing was the bottleneck. Quality was owned by a team, not by the engineers shipping the code.
Built multiple layers of automated testing on top of both existing and custom frameworks. Embedded quality into every pod. The team shipped with significantly more confidence in every release.
I spent years engineering wearable robotics for clinical environments. I watched patients struggle to move their own limbs and understood that every decision has an impact. It can help them or it can hurt them further. That environment doesn't let you stay abstract. It forces you to care deeply about the person at the end of your work, and to listen before you build. I've carried that into every team, initiative, and project I've led since. First as the habit I hold with the engineers I manage, and then as the standard I teach them to hold with their customers.
My job is to understand what is in the way of great work and remove it. For my engineers, that means clearing blockers and building the conditions for focus. For leadership, it means translating engineering reality honestly and advocating for the right investments. For customers, it means holding my team accountable to the reliability they deserve.
My credibility as a leader comes from being genuinely useful to the engineers I lead. If you are stuck on a problem, I can sit down and work through it with you. If you need a real opinion on an approach, I have one. If you want to grow into something more, I can show you the path and coach you along it. I lead from the trust that comes from being useful when it counts.
I align with stakeholders to understand what success looks like, then translate that into a roadmap the team executes against. I gather input from the people closest to the problem, make the call, and name the reasoning clearly. I hold my engineers to own their work, not just execute tasks, but take responsibility for outcomes.
These articles are how I think out loud about the problems engineering teams actually face.
Feature flags feel like a safety net. They aren't. When multiple flags are live at once, the number of code paths to test grows exponentially, and teams skip the regression testing they know they should run.
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AI is generating code faster than engineers can understand it. That gap between velocity and comprehension is not a productivity win. It is an understanding crisis, and someone on your team is already feeling it.
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Most leaders only think about quality when the absence of it is about to cost them a deal. By then, the debt is already compounding. Here is what a quality model actually looks like before the crisis arrives.
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