From MFC to Mobile AI: Engineering the Future with 18 Years of Experience

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Engineering Principles Don’t Expire

I began my career writing Visual C++ in MFC and ATL COM, debugging complex media pipelines, and optimizing for memory and performance with DirectShow and FFMPEG SDK.

Back then, building software meant solving for constraints—CPU, memory, real-time responsiveness. And while the platforms have changed, those core skills still shape how I work today.

Now, when I build intelligent mobile apps using CoreML or TensorFlow Lite, I rely on the same foundations: architecting for efficiency, minimizing latency, and anticipating edge cases.

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Mobile Development: From Xamarin to SwiftUI and Beyond

I’ve developed cross-platform and native apps using:

• Xamarin & C#.NET

• Objective-C, Swift, SwiftUI

• Android & Kotlin

• Adobe Reader Mobile SDK (RMSDK)

• Apple Watch integration

But the turning point in my journey was embedding AI-driven features. From motion-driven coaching using Apple Watch sensors to conversational UI integrations—this is where UX became adaptive, predictive, and personal.

In one case, we observed a 30% increase in user retention by using on-device ML to tailor the experience to user behavior.

That’s when it clicked: AI is not a feature. It’s a UX multiplier.

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AI Is the New Runtime

AI today isn’t just another API. It’s a new paradigm—one that changes how we build and think about products.

Instead of writing every rule, we train models. Instead of rigid UX, we enable personalization. Instead of guessing what users want, we infer from context.

I’ve been working with:

• CoreML & CreateML (on-device intelligence for iOS)

• TensorFlow Lite (real-time ML for Android)

• Firebase ML Kit (OCR, language detection)

• OpenAI APIs (conversation, summarization, reasoning)

These tools extend what’s possible—but only if you bring a strong engineering mindset to handle performance, testing, and UX implications.

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What Hasn’t Changed (And Won’t)

Even with all the abstraction layers and new libraries, these truths remain:

• Performance still matters. Especially in mobile AI.

• UX comes first. Intelligence should empower, not overwhelm.

• Testing is everything. From COM to CoreML, edge cases never disappear.

AI is powerful, but it doesn’t replace the discipline and systems thinking we’ve honed over the years—it rewards it.

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Why I’m Writing

This is more than a tech transition for me—it’s a professional shift.

I’ve started writing seriously to share what I’ve learned and to support myself through content that helps other developers grow. I believe engineers with deep experience—from systems and media to mobile and UI—have a crucial role in shaping the AI era.

So if you're on a similar journey—shifting from traditional engineering into intelligent, mobile-first systems—I want to connect.

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🙌 Let’s Stay Connected

If this post resonated with you, follow me and reach out. I’ll be sharing more technical insights, product stories, and real-world lessons from the AI-mobile frontier.

• 🔗 Follow me on DEV

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• 🔗 Follow me on Medium

Let’s build the next generation of intelligent mobile experiences—together.