Chris Corder
| Azure Senior Technical Advisor | Published Author & Speaker. Building AI-Powered Diagnostics for Cloud Systems | Azure • Networking • Performance
January 2026
A few months ago, I wrote about how the most miserable task in your job might actually be your best AI automation opportunity.
For me, that task was network packet analysis—hours lost in Wireshark, chasing the same patterns, solving the same problems, over and over again.
What I didn’t expect was where that experiment would lead.
Last week, the system I built to escape packet analysis purgatory was officially submitted as a patent.
Not because I set out to invent something groundbreaking.
But because I was tired of doing the same painful task manually.
And that’s the part I want to talk about.
The Surprising Thing About Real Innovation
Here’s a misconception I see all the time:
Innovation starts with a bold vision, a blank whiteboard, and a “next-big-thing” idea.
In reality?
Most real innovation starts with quiet frustration.
Not excitement.
Not inspiration.
Annoyance.
The kind that shows up every time a ticket hits your queue and you think,
“Not this again.”
That’s not weakness. That’s signal.
What Changed After I Automated the Task
Once the AI-driven system was working, once I could drop in a network trace and get a clear, human-readable verdict in minutes, something unexpected happened.
People started asking questions like:
- “Wait… how did it know that?”
- “Could this work for other traces?”
- “Is this something others could use?”
- “Have you documented this approach?”
That’s when it clicked:
I hadn’t just automated a task.
I had formalized expert judgment.
The system wasn’t guessing.
It was encoding years of troubleshooting intuition into a repeatable process.
That’s the line where automation quietly turns into invention.
Why This Became Patent-Worthy (Without the Legal Jargon)
At its core, the system does something deceptively simple:
- It ingests raw, low-level diagnostic data
- Applies deterministic analysis to extract signal
- Uses AI to reason over patterns the way an experienced engineer would
- Produces a clear verdict instead of raw noise
That combination, deterministic analysis + AI reasoning + human-style explanation, is the key.
It’s not just faster.
It’s transferable expertise.
And that’s why it crossed from “helpful tool” into “protectable innovation.”
The Part Most People Miss About AI Automation
Here’s the takeaway I wish more people understood:
You don’t patent ideas.
You patent systems that remove friction at scale.
The reason soul-crushing tasks are such good candidates is because:
- They already have clear success criteria
- They already follow known decision paths
- They already rely on expert pattern recognition
- They already consume massive amounts of time
You’re not inventing from scratch.
You’re distilling.
And distillation is where clarity—and novelty—emerges.
A New Way to Think About Your “Annoying” Work
If you take nothing else from this, take this mental shift:
- That task you dread?
- The one nobody volunteers for?
- The one you’ve done so many times you could do it half-asleep?
That’s not grunt work.
That’s undocumented intellectual property.
It’s experience that hasn’t been formalized yet.
AI just happens to be the best tool we’ve ever had for turning that experience into something durable, repeatable, and, sometimes, patentable.
You Don’t Need to Aim for a Patent
Let me be clear:
You don’t need to file patents to get value from this approach.
The real win comes much earlier:
- Reclaiming hours of your week
- Eliminating mental drain
- Freeing yourself to focus on judgment, not grind
- Becoming the person who fixes the problem, not the one buried in it
The patent is just a byproduct.
The real success was never having to relive packet analysis Groundhog Day again.
Start Where You’re Annoyed
If you’re waiting for permission, inspiration, or a “perfect idea,” don’t.
Start with irritation.
Start with the task you complain about.
Start with the thing you secretly hope gets reassigned.
Describe it.
Break it down.
Hand it to AI.
See what happens.
Worst case? You learn something.
Best case? You change how your job feels, and maybe build something bigger than you expected.
Sometimes the road to innovation doesn’t start with a breakthrough.
It starts with saying:
“I’m done doing this the hard way.”
And then actually doing something about it.
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