AI Learning Pace … Podcast Keeping up wit AI Learning Pace.wav - Google Drive
Anyone Else Feeling Overwhelmed at the Pace of Learning AI from Where We Came From?
Imagine a marathon that turned into a sprint. Halfway through, someone cranked up the treadmill, raised the incline, and started throwing hurdles in your path. That’s what it feels like for many of us trying to keep up with the relentless pace of AI. And it didn’t start here—this journey began back in the days of mainframes, when change was steady, manageable, and mostly predictable.
In those early days, IT pros lived by quarterly updates. Every few months, we’d gather for system APARs, well-structured releases, and a set cadence for learning. We had time to breathe, time to master each new update and apply it without the relentless urgency that technology would bring later. But then, everything shifted. In the ’90s, the Internet came barreling in, bringing with it TCP/IP and an avalanche of protocols: HTTP, FTP, SMTP, DNS, DHCP—the alphabet soup of connectivity. We were suddenly tasked with learning an entirely new language just to stay relevant.
But the change didn’t stop there. Distributed computing arrived, with its own flavor of complexity: OS diversity, NT Domains, Active Directory, and the explosion of different operating systems, each one demanding attention and expertise. We transitioned from centralized mainframes to a dispersed network of user-driven devices, and along the way, had to master new security models, networking standards, and user-centric infrastructures. And just when we thought we had finally adapted, the Cloud Revolution hit. Now, AWS, Azure, and Google Cloud brought instant scalability and decentralization, upending the need for physical data centers. The quarterly updates we once knew became monthly, and our learning cycle sped up accordingly. Agility replaced stability as we adjusted to the new demands of the cloud.
The AI Revolution: From Daily Updates to Hourly Change
Enter the AI era. Just as we thought the pace couldn’t get any faster, AI threw us into overdrive. This isn’t just a new technology; it’s a redefinition of how technology evolves, with advances that hit not monthly or even daily, but sometimes hourly. Every day, we’re greeted with new models, tools, frameworks, and breakthroughs, each one with the potential to reshape our work, our workflows, and our world.
For those of us who came up in IT, the contrast is staggering. We went from predictable quarterly updates on mainframes to protocols that required monthly learning during the Internet age, to the daily updates of distributed computing and cloud. Now, we’re in an AI landscape that changes faster than our screens can refresh. It’s not just exhausting; it’s disorienting. And while we wrestle with AI’s rapid advancements, most of the world—the 90% who don’t live and breathe IT—remain blissfully unaware. They see AI as a mysterious force in the background, a magic trick rather than the result of countless hours of research, learning, and adaptation.
The Reality of Keeping Up: Playlists, All-Nighters, and Endless Learning
For those of us in the trenches, keeping up with AI is more than just part of the job—it’s become a way of life. We’re curating YouTube playlists, running them through the night as if we can absorb the latest advancements in our sleep. By morning, we’re casting videos to screens in every room, or syncing Bluetooth headphones to make the most of every waking moment. The idea of “coming home from work” is a fading memory; work and learning have merged, blurring the lines between life and labor. Even simple routines, like taking the dogs for a walk, feel like a luxury we can’t always afford when there’s yet another AI breakthrough we need to catch up on.
We’re pushing ourselves in ways that no previous generation of IT professionals had to. This isn’t the orderly, structured learning of the mainframe era; it’s a relentless tide of change that we’re forced to navigate, often without a lifeline. And we’re not alone—this pressure is creeping into every role. Janitors will soon work alongside AI-driven robots, teachers will integrate AI into their lessons, and executives will have to learn how to manage AI-enabled systems. There’s no escape from this wave; it’s transforming every job, every role, and every industry, leaving no one untouched.
The Global Challenge of AI Integration
Here’s where it gets even more daunting: AI isn’t just about personal learning. It’s about transforming entire organizations, industries, and legacy IT systems on a global scale. Every business process, every organizational structure, every role will need to adapt. For AI to reach its full potential, it has to be woven into the fabric of how we operate, think, and make decisions. Integrating AI isn’t a simple update; it’s a full-scale overhaul. And those of us who’ve been on this journey since mainframes are now the pioneers, tasked with building the bridges between old systems and new intelligence.
The Human Cost: Empathy in the Age of AI
AI itself may not understand what this relentless pace feels like—the exhaustion, the burnout, the sheer human cost of trying to keep up. But as humans, we feel it. We have physical and mental limits, and yet, we keep pushing, driven by the fear of falling behind. Sometimes we’re so worn out, we barely make it to bed, but we keep that playlist running, hoping some of it will stick. There’s an emotional toll here that we don’t talk about enough: the cost of perpetual learning, the sacrifices we make to stay ahead, and the weight of a responsibility that only grows heavier with time.
This isn’t just a race; it’s a transformation that demands more than just technical skills. It demands empathy, resilience, and an understanding of our own human limits. We need to recognize that, while we’re sprinting toward a future where technology reshapes every aspect of our lives, we are, ultimately, human. We’re not machines, and we can’t be expected to keep up as if we were. This journey requires support, a shared understanding of the challenges, and a commitment to finding balance—if we’re to survive, let alone thrive.
A Future Where No One is Exempt
As we face this massive shift, the future is clear: no one will be untouched. From janitors to CEOs, everyone will have to learn how to coexist with, operate alongside, or even manage AI. The comforting idea of “just doing your job” and leaving work at the door is fading fast. In this AI-driven future, we’re all students in an endless classroom, constantly learning, adapting, and evolving. And while AI might make some things easier, it’s also making the boundaries between work and life, between learning and living, more fluid and challenging than ever before.
So, here we are, trading sleep and spare moments for YouTube playlists, AI news, and 24/7 feeds, hoping we’re keeping up enough to hold our ground. And as the early adopters, as the ones forging the path, we’re left wondering: is anyone else feeling this too? Or are we all just clinging to the treadmill, hoping that someday, somehow, it will all make sense?
If this resonates with you, if you’ve found yourself lost in the endless loop of learning and adapting, remember—you’re not alone. We’re all navigating this new frontier together, clinging to the past, adapting to the present, and uncertain about what’s next. And maybe, just maybe, if we keep moving forward, we’ll find that balance between technology and humanity we’re all hoping for.