How to Keep Up With AI: Eight simple habits that will keep you in the game
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AI is evolving faster than any technology in history, and many people feel overwhelmed by the pressure to keep up. In this episode of CoolTimeLife, we look at why AI fatigue is so common — and why you don’t need to master every new tool to stay relevant. You’ll learn eight simple habits that will keep you in the game to create a sustainable path forward.
This is the transcript to the podcast. You can also listen to it on Apple Podcasts, Spotify, Amazon, Audible, iHeart , and YouTube.
Every day, AI seems to reinvent itself, and somehow all of it becomes your problem. It feels like the world handed you a brand-new job: learn everything about AI immediately. It seems impossible to keep up as AI seeps further and further into your job. But here's the twist. This is actually a good news story today. Not because AI is simple, it isn't, but because keeping up with it is far easier than you think.
Welcome to CoolTimeLife. I’m Steve Prentice. I’m glad you’re here. Each of our CoolTimeLife episodes focuses on a topic dealing with people, productivity, technology, and work-life, and each offers ideas and facts you need to know about to thrive in today’s busy world. An index of our podcasts and videos is available at cooltimelife.com.
Despite the breathless exaltations of YouTube experts and AI coaches, the majority of regular people feel overwhelmed because AI evolves daily, but we don't. We all have too many other things to do to take stock of all these changes. Yes, this is called AI fatigue. Every day, there's a new model, a new tool, a new headline disguised as a solution. This is the first time in history where capability jumps happen weekly rather than generationally.
But you know what? That feeling of falling behind is often worse than the reality of it. In all honesty, we do not need to keep up with everything. No one can, not even the experts.
The Reality: Yes, AI Moves at Breakneck Speed
This technology, AI, has changed the world in a way that is similar to the development of writing or the creation of the printing press or the arrival of electricity or the arrival of the internal combustion engine and, of course, the internet itself. All of these tools weren't just things unto themselves. They were things that allowed for the creation of other things, incubators of innovation. Other people came along and thought, "Hmm, how can I use this for another different purpose?" And they did.
So today, we are in a true genie-out-of-the-bottle moment. Software-based tasks that used to take years now take months or weeks, while those that took months or weeks now take minutes, and there is no going back. Yes, each of these new models builds on the last, so the AI development curve does indeed feel exponential.
Typically, some people are quick off the mark, learning new skills that kind of emerged overnight, like vibe coding, prompt engineering, building custom AI agents, and building multimodal workflows. And then there are the influencer superstars on YouTube and LinkedIn pitching their courses and delivering tips and tricks for creating AI agents as if they have been doing it for a decade. And I certainly admire them, but for all their wisdom and energy, it still makes the rest of us feel kind of even worse. But there seems to be so much more to know about, and it seems we must learn it all right now.
So is that really true? I don't think so.
Companies move at the speed of culture, not code
Organizational change in companies, in organizations of any sort, their cycles are measured in years rather than weeks. Most workplaces still struggle with quite a few cultural and legal realities that mean it will be months at least before some of these new AI technologies become the norm. Much of this has to do with maintaining stability. Organizations, whether they are in the public sector or the private sector, must keep doing what they are currently doing. They have production cycles, budgets, and established processes. They have suppliers with contracts, customers with expectations, boards of directors and other overseers who insist that their ship stay on as smooth a course as possible to have the strength to weather any bad times to come, including the geopolitical instabilities that we are currently experiencing. New technology has captured the attention of company leaders, of course, and in many organizations the first steps towards establishing an AI policy are being taken, but its very nature as a technology with new processes and risks that evolve by the day make this difficult and time-consuming.
In addition, most organizations work with a Microsoft system of some sort using Teams and Windows products interconnected with servers, cloud, and legacy systems. Many also use other outside products like Adobe or Dropbox, but by and large they stick with the tried and true, and this is important when we look at how AI and other innovations seek to change technology quickly.
So before we get into my eight techniques, I'm hoping that this little historical summary helps take a little bit of the pressure off this need to keep up with AI. One of the main reasons that most organizations are Microsoft-based at all and do not use Apple products is because Microsoft in its early years worked with IBM, providing the operating system for the IBM PC. That's what made Bill Gates a millionaire by the age of twenty-six and a billionaire just five years later. Before personal computers arrived, businesses relied on mainframes that were supplied by IBM. It was the mainstay of the business throughout the mid decades of the past century, and therefore when it came time to choose partners with a newfangled computer company, Gates shrewdly chose to license his software to IBM, and companies chose to stay under the IBM umbrella. For the very same reasons that I am describing for today's companies and today's situations. Change brings risk. Careful leadership and management demand careful footing. Microsoft was associated with IBM, and that made the change feel safer.
Sticking with this IBM-Microsoft culture led companies to maintain many outdated processes as well, seeing them as central to their culture. Email, as I have said many times, is just an electronic version of postal mail, just faster. The process of communicating over the last fifty years did not innovate, it just sped up.
Only now, with the arrival of channel-based apps like Microsoft Teams Chat and Slack, are there hints of innovation in the world of internal communication, but they too have simply inserted themselves like a round peg in a square hole. No one has really innovated the way we communicate and collaborate in any way that has taken root in a workplace.
The same goes for our use of PowerPoint and of meetings and of calendars. They are all just electronic variations of long-used tools. Truly innovative techniques for meeting and presenting seldom gain the traction needed. No company wants to set itself back due to challenges in learning or accommodating new technology until the market makes it the norm.
Somewhat outdated procedures will remain the norm. Sure, everybody is now growing used to Copilot and other AI tools, but many organizations are still struggling with the basics, the legalities of it all, and these are legitimate fears. Compliance, data in transit, data that may be subject to freedom of information requests, the confidentiality of data belonging to clients, customers, patients, or students, cybersecurity concerns, and overall control of a very wild card technology. Companies and their leaders do not like risk or risky behavior, and so for all of AI's promises, it remains a wild card.
So AI as a technology evolves daily, but your company won't. That's not a failure. That's reality, and it's pretty smart. You will still have to manage meetings in boardrooms. People will still send email. They will still use Microsoft Excel for crunching numbers, Microsoft Word for words, and PowerPoint for presentations. Yes, we do need to understand what it is doing, we do need to understand what it is capable of, and we do need to keep pace with our clients' and customers' expectations. But that doesn't mean we have to put ourselves under enormous pressure to do so.
Here are 8 Strategies for Keeping Up
So here are eight strategies for keeping up with AI. The formula is kind of like this: AI is changing fast. Organizations change slowly. Your opportunity sits in the middle.
Adopt a “little and often” mindset
First, adopt a little and often mindset. Spend maybe ten minutes a day experimenting with one AI tool or watching a couple of YouTube videos about it. Just small, consistent exposure beats occasional deep dives. Just take in as much as you want, as much as you can, so that when the day comes that your department decides to start using a certain AI tool, you might not yet have mastered that tool, but you will know about its context and where the organization hopes to eventually go with it.
Learn workflows rather than tools
Number two, learn workflows rather than tools. The AI tools will continue to evolve and change. We need to focus on existing workflows, how people meet, how we present, how we write, how we communicate. These workflows will allow you to swap in any new tool as and when it arrives.
Build an AI muscle memory
Number three, build an AI muscle memory. Yes, it's a good idea to learn how to use an AI tool. Try it out. Practice asking it better questions. Learn how to write prompts. If you do not know how to write a prompt or a specific or sophisticated prompt, then tell your AI tool what you want and it will create it for you. That's the coolest thing. You don't need to know how to do all these things. All you need to know is it is out there, and all you have to do is ask for it.
You can treat AI like a collaborator, not a vending machine. It's designed to solve problems based on easy-to-ask questions. You do not have to go into an index or a complex sequence of questions framed in a rigidly engineered way that requires you to know in advance what search terms to use. Just ask when you need it.
As part of this muscle memory concept, you can learn how to iterate, learn things in steps, and then refine upon your research using your conversation history with your AI tool. Even though AI is not human, it has been designed to approach things in this human way, or more precisely, it allows you to approach things in a more human way.
Don’t chase every trend
Number four, don't chase every trend. You don't need to learn vibe coding, for example, unless it's relevant to your work. If you don't know what vibe coding is, it simply means writing code to fit the vibe of the moment, the thing you need now. The great thing about vibe coding is that you don't need to know how to code. You don't need to go to school to learn it. You just simply tell your AI tool, "This is what I want the code to do," and it will take care of the rest. If coding is not part of your job right now, you don't need to learn how to vibe code. But if one day you think to yourself, "I wanna create a better way to do a particular thing on a computer," the odds are good you will be able to create an app that can do just that without having had any prior coding experience or education.
The challenge, of course, will be to get that approved as an allowed tool within your organization's system.
That's what the process is all about.
So I'm not saying don't learn about AI, but what I am saying is don't feel under pressure to learn it all right now because by the time your organization gets around to using a specific AI tool, things will all be much further down the road. The stuff you learn today will likely be out of date by then.
So definitely learn the principles behind AI. Understand that AI responds to patterns, structure, and clarity, but remember that it knows nothing. If you wanna know exactly how AI works, I have an episode on that too. Just look for the episode How Does AI Actually Work?
Focus on your domain
Number five, focus on your domain. AI can be a great tool, but it rewards people who know their field deeply. So its best results will come from combining your expertise with AI's capabilities. As a simple example, you can use AI to break writer's block or procrastination. If you're struggling with how to put a presentation together or how to draft an email, AI can get the ball rolling by suggesting some bullet points to frame your message, but it shouldn't write it for you. It's your expertise that will make the message effective. It can simply help you get started. And the other reason why you wouldn't want it to write for you is that people are already becoming adept at spotting documents that read like AI. And if they see that in your writing, your value in their eyes may decrease, not increase.
So have AI set up the structure for you to write, for you to leverage your expertise, your deep knowledge. And maybe at the end, let AI make some suggestions about points you may have missed or a better way of framing the narrative. It's good at that too, but you are good at what you are good at.
Create a personal AI stack
Number six, create a personal AI stack. This means creating a simple set of tools that you can rely on that are AI-based. Maybe a writing assistant. Hey, even Grammarly is an AI writing assistant, basically. So maybe a writing assistant, a research assistant, an automation tool, and a creative tool. And they can all exist inside one brand like Copilot, or maybe you prefer to use separate apps for separate things, the way you might already do with tools like Slack, Dropbox, and Zoom.
So look at the tools that are out there, see what they can do for you, and get familiar with a small collection or stack of tools.
Personalize your relationship
Number seven is to personalize your AI relationship. This is one of the must-dos, I have to admit, to build a relationship with your AI tool in terms of saving all of your past conversations. Remember that AI knows nothing about anything, but it is really good at reading fast and then predicting what next to say. Your collection of past conversations with your AI tool become an asset. Each time you work with this tool, it will reread your past conversations and projects, relearning who you are, and then applying this knowledge to customize its communication with you.
This is where the value comes from. This is where the deep relationship can really be leveraged. Most AI tools now offer this, and it's worth looking for. And if for some reason the LLM that you do use does not retain past conversations, then make sure to save them as a document and upload that document the next time you talk to it. This is truly one of the key parts of having a great agent at your side. An agent should be something that knows what you need even before you do, and it can only do this once it has reread your past interactions with it and has refamiliarized yourself with your deep knowledge.
So these seven techniques out of eight are enough for you to stay ahead of ninety percent of other people and to stay ahead of where your organization is at any time.
Stay curious, but don’t seek perfection
My last one, number eight, is to stay curious, but don't seek perfection. Curiosity is sustainable and can be enjoyable. Seeking perfectionism is exhausting, especially in a field where the products advance and change every day. As I said before, I see endless ads on LinkedIn and other socials advertising twenty-eight-day courses to help you master AI, but I personally do not hold much stock in these simply because studying anything for twenty-eight days straight will not give you twenty-eight days worth of knowledge. It will simply leak out of your memory due to a concept called the Ebbinghaus Law. We can't retain that much. And even if you could be available for twenty-eight days straight, the world is gonna be a different place twenty-eight days from now. This is kind of like learning how to fly a plane while you're already inside a flying plane.
The better route, in my opinion, is just to stay curious. Read the headlines on a daily newsletter like superhuman.ai or therundown.ai. Get a sense of the things that are going on, knowing that if you need to know more today or a week from now or twenty-eight days from now, you can always search and learn as and when you need it.
The Bottom Line: How to Keep Up With AI
You don't keep up with AI by sprinting. You keep up by building a mindset that can absorb change without fear. Remember, fear is a protection reflex that actually shuts down the learning centers of the mind. I wrote a whole book about this if you're interested. AI should not be seen as some big giant kit that arrives on your doorstep one morning and that you now have to figure out how to assemble like some sort of IKEA furniture.
AI, as I have said, evolves daily, and so do you. It is better to look around at your surroundings and ask a question. Don't ask, "How do I make AI work?" But instead ask, "Where do I have a situation that could be improved, and how could AI help me with this?" If you struggle to decide what to have for dinner, it is much easier to ask, "Is there an AI tool that can look in my fridge and make a recipe out of what I have?" than it is to take a course called Cooking with Copilot.
Look for workplace issues and seek to solve each one at a time, rather than diving into a completely new agentic collaboration suite. Whatever it is you need, even a simple checklist to prepare for a meeting, there's already a prompt for that.
Humans evolve slowly. Every innovation needs its time to settle into the work environment, and some never do. We have had access to video memos for years, such as Loom, as well as all kinds of virtual meeting spaces like Virbela and Toucan that just never caught on. For some reason, people still prefer to use email. Why? Because it works for most people. It connects on some level with how we actually like to relate to people, maybe not through video, maybe not through three-dimensional virtual environments, but through messaging. And that's why, despite its many liabilities and weaknesses, it is still here, while other better technologies have since come and gone.
As innovation races around us, the best place for you to stand is confidently in the middle. Take notes. Learn one new thing daily, but also take your time.
Until next time, stay safe, stay confident and thanks for listening.
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Keywords:
how to deal with AI overwhelm and AI fatigue
why organizations adopt AI slowly
eight simple habits that keep you in the game
how to build AI muscle memory
how to stay ahead at work without chasing every trend
why focusing on workflows beats learning every tool
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