I’m a planner. A systems thinker. My mind works in terms of process. In the age of AI overwhelm, this is both a strength and a new challenge. While a task may send my thoughts in a lot of different directions, those journeys are finite. They are bound by my own personal life experience. Relying on my experiences has always given me a sense of peace and progress. Yet it also creates a false boundary, an unawareness of the new knowledge that might be out there. It’s these blind spots that make partnering with a tool like an AI so exciting. As I mentioned in AI in Context, the tools reflect what we bring to them. But lately, this structured way of working feels overwhelmed by the sheer volume of information coming at me.
Everywhere I look, I see articles and prompts for new “AI challenges.” You can use AI to plan a trip, write a blog post, or even run a business. While I want to leverage these tools to be more efficient and make time for what I truly want to do, I’m finding that the promise of completion is becoming more and more elusive.
The ideas come from everywhere: a blog post about how to find the lowest flight option for a weekend getaway, a course on how to use every new AI, or even a YouTube video that suggests a tool I’ve never heard of. My husband’s Instagram feed is now filled with prompts for the most fulfilling meal on a menu that meets a specific calorie count, or what questions to ask to get a better insurance rate. What once felt manageable, because the scope was limited by my own knowledge, now feels like an endless stream of possibilities.
From Rivers to Deltas
In the past, completing one task might have generated the next. It was a natural flow, like following a river downstream. But now, the tools themselves generate an endless stream of possibilities. My sophisticated Notion databases, once a source of order, can now be flooded with more ideas than I could ever possibly pursue. When I’m getting tired, I find myself just copying and pasting the whole thing into a “follow-up” list. I’m doing this instead of parsing out what I really want to pursue. My digital junk floating in the river is slowly drowning me. What used to be a clear, linear path has become a branching delta of open loops. Each one is a fascinating distraction from the one before it.
Last Tuesday, I sat down to write a simple blog post. Thirty minutes later, I had three different AI-generated outlines, two alternative post concepts, a list of twelve potential stakeholders I’d never considered, and a rabbit hole of research questions. These could fuel months of exploration. The original post? Still unwritten.
To manage this onslaught, I’ve learned a new practice: a Curiosity Container. When a thought comes up, I can simply tell my AI partner to “put that in the Curiosity Container.” This offloads the idea so I don’t have to carry the weight of it down the river with me. I use this in both Gemini and ChatGPT, and I’m sure other AI engines have a mechanism for this as well. The important thing is that the idea is saved. It no longer occupies my mental RAM. With a mechanism like this, I can finish the task at hand and revisit the idea later. I’ve found that this technique pairs beautifully with what I described in Plain Language AI Prompts: The Human Side of Talking to AI — bringing intention and clarity to every prompt and conversation.
The Mindset Shift
This delta-versus-river shift requires fundamentally different navigation skills. In a river, you follow the current. In a delta, you must constantly choose which channel to explore. Just like in economics, this requires a fundamental shift in mindset. The opportunity cost of choosing one path is abandoning dozens of others. Some people thrive in this environment, the natural explorers and divergent thinkers. But for those of us wired for completion and closure, it can feel overwhelming. The challenge isn’t the technology; it’s the awareness it creates.
AI can take my anecdotes and derive multiple story arcs and a new topic I want to explore. And when it uses that anecdote to introduce a new tool? That’s my kryptonite. I’m a lost cause in terms of making progress on anything else.
The Friction Generation: How AI Overwhelm Changes Our Habits
I feel the pull to be part of all of it. But in trying to keep up, I feel a different kind of pressure: a sense that I am falling behind. The real distinction isn’t age; it’s whether your foundational habits were formed in a “completion-oriented” or “exploration-oriented” environment. This distinction is magnified in an era of AI overwhelm.
The challenge isn’t our ability to learn, but rather when and how we were introduced to these tools. For many people, this is a relatable struggle. Music offers a perfect analogy. I was listening to John Mayer on his channel the other day, and he was talking about how you used to be so in touch with the current hits. But then, life happens. You step away, you have kids, and for so many years you’re listening to Barney that you lose track of what’s popular. Later, you come back and don’t recognize any of it. Technology is the same. It’s even more stark because the tools we use today are built on the precursors that came before them. If you never learned the foundations, it takes you just a bit longer to pick up what’s current.
New tools are not inherent to how we operate. They take time to adopt and integrate. Moreover, we are also used to a fallback, a manual system for when technology fails. Many who grew up with this technology may not have those manual systems. This was clear to me when a landscaper was delayed because the city’s permitting system went down and they had no way to function manually.
The Recalibration Challenge
Those of us trained in the era of finite resources, limited research materials, bounded project scopes, and clear endpoints must now recalibrate our entire relationship with how we operate. It’s like learning a language. If you’re introduced to it at a young age, it becomes natural. You can hear when something sounds wrong without memorizing the rules. But if you learn a language later in life, you have to formally learn the rules first, which is a very different way of learning. Tech is the same. We have to learn the rules before we can speak the language fluently.
Redefining Progress in an Infinite Game
I don’t think I’m alone in this feeling. We’re all shifting from a tangible goal of “completion” to something more nebulous to satisfy that need for a sense of achievement.
So, what does progress look like when the goal isn’t finishing? What happens when every answer generates ten new questions? What happens when “enough” is no longer dictated by resource constraints but by our capacity to stop?
I am still learning to reconcile these new metrics with the old. While I’ve learned to tell my AI partner to “stop explaining” to preserve a rich, human communication style, I have a voice in my head that questions the outcome. “That’s great that you learned something,” it says, “but did you deliver what the person needed to move forward?” I still feel challenged by the need to produce a tangible deliverable for a client. Yet with these tools, I think it’s fair to expect to get there faster.
I am learning to incorporate new perspectives into my own thinking. For instance, instead of counting completed tasks, I track insights gained, connections made, or capabilities developed. Did this exploration teach me something valuable about my field, my clients, or myself? That’s progress, even if the project remains “unfinished.” The old metric was binary: done or not done. The new metric is multidimensional. What value was created? Were relationships strengthened? Are future possibilities unlocked? Sometimes an “incomplete” project that generates three new collaborations is more successful than a finished report that sits unread. Rather than trying to pursue every AI-generated possibility, I’ve started asking: Which explorations align with my deeper goals? Which feel energizing rather than depleting? Which build on my existing strengths while expanding my capabilities?
This reflection connects closely to what I explored in Creative Destruction, Curated Creation — how adaptation and evolution drive value when the landscape changes faster than we can plan for it.
The Hidden Costs of Infinite Possibility
There are costs to constant possibility generation that we’re only beginning to understand. The anxiety over endless FOMO is real. It’s fueled by the knowledge that I could be exploring, optimizing, or generating something at any given moment. My attention, which was already prone to wandering, feels even more scattered. The simple pleasure of focusing deeply on one thing has all but disappeared. The cognitive load of perpetual decision-making is exhausting, as is the fear of asking a question wrong and triggering an avalanche of even more possibilities.
But I’ve also realized this isn’t simply a negative. This infinite possibility is actually forcing me to hone in on what I really enjoy and leave the other things by the wayside. Because I’m an introspective thinker, this process is making me analyze my own workflows to figure out what gets accomplished and what I keep going back to. I can see where I’m gravitating. I love building Notion frameworks, designing garden beds, and planning travel. I’m now actively looking for ways to automate, relegate, or employ an AI to do the things that I enjoy less than the things that I love to do. The hidden cost has become a catalyst for self-awareness.
A Framework for Moving Forward
So where does this leave us? How do we harness these powerful tools without being overwhelmed by them?
This collection of articles will explore these questions through the lens of my practical experience. I’ll be sharing my journey as a planner and systems thinker to find a new way to work with AI, not by fighting my nature, but by evolving it. This is a source of frustration, because while I recognize that technology informs behavior (think of the progression of the cell phone), there are days when it feels exceptionally exhausting to adapt my style to a tool. Since a foundational part of “augmented intelligence” is intelligence itself, there’s a natural expectation for the AI to get smarter about how it works with me, rather than forcing me to adjust to it.
The topics that follow will delve deeper into the strategies I’m using, as well as some practical advice for staying on track:
- Boundary Setting: The Art of Strategic Ignorance, a framework for choosing what not to explore, and why saying no to AI suggestions might be the most important skill we can develop.
- Integration Practices: Making AI Serve Your Systems, concrete strategies for incorporating generative tools without letting them hijack your existing workflows and productivity approaches.
- The Satisfaction Problem: Rediscovering Completion in an Open-Loop World, how to create closure and celebrate progress when the work is never truly “done.”
Practical Habits for Navigation
This requires a new set of habits to keep ourselves on track. For example, set aside a specific, time-limited block in your week for pure exploration. Use your “Parking Lot” list to guide what you’ll investigate during that time. If your mind works like mine and you need a checkbox on a to-do list, then reframe your to-dos. Did I learn something? Gain a new perspective? Advance this in some way? These are measurable forms of progress. Finally, if you thought doom-scrolling on social media was a time killer, wait until you start using AI. You can go down a rabbit hole for hours. Set an alarm, take a break, and reset so that you can return to your work with fresh eyes.
The river has become a delta. We can’t change the geography. But we can learn to navigate it with intention, wisdom, and real satisfaction. I read a meme the other day that joked about how great it is that we have amazing AI tools that create art, music, and write books. Really? I wasn’t asking for more time to clean the kitchen! The humor, and the truth, of that statement is that AI seems to be taking over the creative tasks we enjoy, leaving us with more time for the things we don’t. We need to find a way to change our thinking, our effort, and our processes to swap that around and turn AI overwhelm into AI advantage.
If this reflection resonates with you, the next piece in this series, Defining Wins with AI, explores how to measure progress when the finish line keeps moving.