1000 days, one mindset: A mid-career engineer's reinvention

What happens when the skills you’ve spent your career mastering suddenly become outdated?

For Frank La Vigne, that question wasn’t theoretical. It was a reality he faced mid-career. After years building apps for Windows Phone, he found himself laid off and staring down a harsh truth:

“I was a Windows Phone developer. And then, suddenly, those skills were no longer in demand,” Frank explains. “I realized I didn’t have mainstream employable skills anymore.”

It’s a moment many technologists quietly fear—especially those who’ve been in the industry a while. Tech evolves fast. Sometimes entire stacks or platforms disappear. Suddenly, what made you valuable yesterday feels irrelevant today.

But instead of staying stuck, Frank made a bold choice nearly ten years ago: he decided to learn his way into a new future.

Tech industry layoff turned tech career reinvention

Frank’s journey of reinvention didn’t begin in a classroom. It began in a conference room. While working at Microsoft in 2016, he attended an internal research summit. The topic? The future of AI.

“They were talking about AI becoming part of every product,” Frank recalls. “That sounded wild at the time. But it blew my mind. I thought, this. . .this is what I want to do.”

It was a powerful spark. But inspiration isn’t enough. Frank still had to bridge the gap between his current skill set and the direction tech was heading.

With no formal background in data science and no interest in going back to school for a PhD, he started exploring online learning platforms and professional certification programs. He studied data modeling, machine learning, Python, and statistical thinking, laying the groundwork for his next move.

And it worked. Within eight months of dedicated self-study, he landed a role leading the data science practice for a Microsoft partner.

“I just immersed myself. I made retooling my job. Every day, I studied like it was my full-time role.”

This wasn’t a clean slate. It was a pivot. A bold, self-driven recalibration that allowed him to stay in the tech world he loved, without starting over.

1000 days of learning—and counting

Fast forward a few years: Frank was working as a data and AI architect at Microsoft, building and advising on solutions. But even then, he knew staying sharp required more than experience. It required continuous growth.

That’s when he rediscovered Pluralsight.

“I needed to strengthen my data engineering skills, optimizing pipelines, tuning SQL servers, stuff I hadn’t done much of. Pluralsight gave me that edge,” he says. “It was like a supermarket of learning. Whatever I needed, it was there.”

He began learning between meetings, over coffee, and on weekends. Some days were deep dives. Others were a few minutes of review. But what made it stick wasn’t a specific course. It was the streak.

“Today is day 1,000 of consecutive learning,” Frank shared. “Not every day do I feel curious. But I don’t want to break the streak. So I log in. I learn. And every day, I grow.”

That consistency has become his secret weapon—not just for building knowledge, but for staying resilient.

Flexibility in tech knowledge is the new superpower

One of Frank’s proudest achievements isn’t a job title or a certification. It’s the ability to stay adaptable in a fast-changing field.

“I went from being all Microsoft, all the time, to presenting at AWS re:Invent on a MacBook,” he laughs. “That kind of shift takes mental flexibility.”

He’s now a Technical Marketing Manager at Red Hat, where he creates content around emerging AI tools, translates complex topics for broader audiences, and regularly draws on skills he didn’t have five years ago, like Linux administration and OpenShift deployment.

When asked how he keeps up, Frank says it comes down to curiosity and range.

“If you’re in AI and not thinking about cybersecurity, that’s a problem. If you’re a dev who never thinks about infrastructure, that’s a gap. Everything overlaps now. The best people in tech aren’t siloed. . .they’re flexible.”

Tech learning without learning gatekeeping

Frank’s journey also highlights a shift in how people can break into AI.

When he first attended that AI conference in 2016, he felt out of place.

“Everyone I met had a PhD in math,” he says. “One guy told me, ‘Just go back to school and get a PhD. You’ll be fine.’ As if that was as easy as running to the store.”

That moment could have stopped Frank, but, instead, it fueled him. He launched a podcast called Data Driven to learn publicly, share insights, and connect with others navigating nontraditional paths into AI.

“I wanted to show that you don’t need to be a mathematician. You just need to be motivated. AI needs more than coders. It needs explainers, strategists, and communicators. There’s room for everyone.”

He’s since interviewed dozens of experts on the show, including one of his inspirations, educator and data scientist Lillian Pierson. Her path from civil engineering to data science helped Frank see his own journey was valid, too.

What Frank’s journey means in a volatile tech job market

Frank’s story is more than just impressive, it’s also motivational and practical. He didn’t reinvent his career with a master plan or a silver bullet. He did it with curiosity, commitment, and a learning streak that never quit.

For technologists facing layoffs, skills gaps, or shifting job markets, Frank’s experience offers insights anyone can follow:

• Start with the end in mind. Decide whether you want to build, sell, teach, or explain AI, then work backwards to find where to start.

• Pick one skill and go deep. Don’t try to learn everything at once. Focus, and let momentum build.

• Use the tools. Platforms like Pluralsight make it easy to learn in short bursts and build a habit.

• Track progress. Gamification, streaks, and badges can make the hard days easier.

• Embrace range. Knowing a little about adjacent areas, such as cloud, security, or Linux, will make you more adaptable.

“You don’t have to be the best coder. But you do have to be a lifelong learner. That’s what keeps you relevant.”

Start your own learning streak

Frank didn’t plan to hit 1,000 days of learning. He just kept showing up—one course, one concept, one day at a time. That steady habit didn’t just change his resume, it changed his mindset.

Don’t get overwhelmed by your end goals; start with something small and determine to be consistent with it. Here are three good next steps:

• Choose one course in an area you’re curious about: AI, data, cloud, or security

• Set a 7-day streak goal to build a learning habit

• Track your progress so you can plan small celebrations at milestones

Just by focusing on one day, one course, one celebration at a time, you’ll start your own reinvention. 

Change your mindset, upgrade your tech skills and reinvent your career.