My relationship with AI started back in 1993, when I landed my first internship at Texas Instruments in the Speech Recognition Division. I literally trained a language model to interpret speech waveforms...back when most people were just discovering email and connecting to the internet via dial-up. We were working with the early forms of the internet, and manually mapping sounds to words and laying the groundwork for the large language models of today.
That early spark led me to the University of Texas at Dallas, where I pursued coursework in Artificial Intelligence and Computer Engineering in the mid-90s. Long before AI was mainstream, I studied its history, philosophy, and foundations of understanding: how it learns, how it mimics language, and what it reveals about how we think.
Fast forward to today, and that early grounding allows me to bring a rare blend of technical fluency + human insight to leadership development, group facilitation, and culture design. I use contemporary technologies to help teams rethink how they collaborate, including human-to-human and human-to-AI teams. Especially when working with neurodiverse talent, I see AI as the productivity tool that expands access, fosters inclusion, and will accelerates innovation.
Whether I’m designing curriculum for coaching execs or building a custom onboarding experience leveraging technology, I draw on this long arc, from early TIMIT corpus with manual training to modern-day transformers and LLMs, to help people navigate change and thrive in the age of intelligent agents.
(draft of a script for a story about the same time period)
I was the youngest intern at Texas Instruments. I had just started working with early neural networks… training a language model to recognize speech waveforms. Picture a lab full of humming UNIX workstations, CRT monitors glowing with green text, and engineers who’d been pushing the boundaries of machine understanding long before we dreamed of scaling the perceptual models we all have access to today.
One afternoon, I sat down at my terminal with my submarine sandwich, ready to dive into more manual data labeling…mapping audio waves to words one frame at a time. I typed a few commands, hit return… and then something strange happened.
My screen began to melt.
I don’t mean crash. I mean melt. The pixels at the top of the monitor started to drip downward… like digital wax from a candle. Text warped and slid. Windows collapsed into puddles at the bottom of the screen. It looked like the computer was having a heat stroke in slow motion.
I froze. I was new to the Unix environment…. did I break something? Was this some obscure memory overflow? Had I accidentally brought down the entire speech lab?
I called my supervisor over, an average dude with that look of quiet mischief I’d learn to spot later in life. He peered at the screen, nodded solemnly, and said, “Hmm… yeah, that’s not good. What did you do?”
Then he cracked a grin, and told me to type in the word decay.
The whole room burst out laughing.
Turns out, the team had installed a prank script…. some elegantly crafted display hack that one of them put together during their college days that simulated a real-time pixel meltdown by flickering the pixels. A classic “welcome to the team” hazing ritual. Someone tossed me a donut and said, “You passed.”
And honestly? That moment stuck with me…not just because it was funny (which it was), but because it captured something essential about coder culture that I still carry with me: it’s irreverent, clever, experimental, and deeply human. Even in a lab building the foundations of machine intelligence, we weren’t afraid to laugh, play, or break the fourth wall.
That spirit of curiosity, humor, and collaborative invention is still alive in everything I do today. Whether I’m raising amazing children, facilitating leadership development, or exploring what human+AI collaboration can actually feel like.
I remember that moment: the day the pixels melted, and the machines reminded me that tech doesn’t have to be sterile to be smart.