When a Popular Method Feels Like the Answer

A few years back, everyone was folding their socks into little rectangles. That was the Marie Kondo method, sparking joy everywhere. People were thanking their old t-shirts as they were putting them on the let-this-go pile. Her method became popular. It got shared, repackaged, and turned into some pretty cool businesses.

When I first heard about it, I thought, okay, I’ll try this. I’ll spark some joy. Then I went to my closet and realized this wasn’t going to work for me. I live minimally. It started after move one, and five moves later it’s still the same thing. I could see why it worked for people who consume a lot of stuff, but I wasn’t drowning in things. I didn’t need the method to work.

And that could have been the end of it. Not me, not my problem, move on. But there was still that little nag in my head of there’s something to this. I’m just not quite sure what.

So when the next thing showed up, I was ready for it.

This time it wasn’t sparking joy. It was Andrej Karpathy talking about building a wiki — a different kind of second brain you could actually navigate. Catalog everything. Link it together. Make it searchable months later.

That little nagging feeling from Marie Kondo came back immediately.

Maybe this was the thing I had been missing.

I didn’t have a physical clutter problem. I had a digital one. Or at least that’s what I thought.

For years I had accumulated conversations, notes, decisions, ideas, half-finished projects, articles, and experiments across more places than I cared to admit. Finding something wasn’t usually the problem. Finding my way back to why I made a decision six months earlier was.

A wiki sounded like exactly the thing I had been missing.

Finally someone had put words around a frustration I’d been carrying for years. It wasn’t just that my information lived in fifteen different places. It was that I never quite trusted I’d be able to find my way back to the thinking that got me there.

The pull felt real because it didn’t feel like another productivity system. It felt like an explanation for why I kept losing my way back to my own work.

So I opened ChatGPT and started building.

I thought I was about to build a better knowledge system.

The Moment I Realized I Was Building Someone Else’s System

At first, the conversation felt productive.

That was part of the problem.

ChatGPT was fast, competent, and full of structure. Every answer seemed to make perfect sense. Move this here. Rename that. Create an inbox. Separate active memory from the wiki. Decision records go here. Conversations go there.

I knew I had conversations everywhere—ChatGPT, Claude, Gemini, Notes—and somehow every version of the system still left me wondering where I was supposed to go when I needed to remember why I’d made a decision.

Nothing it suggested sounded ridiculous. Most of it sounded useful. And because it sounded useful, I kept going.

By the third conversation, we weren’t solving the problem anymore. We were reorganizing the solution we’d already reorganized once.

That was the part I had to pay attention to.

The answer wasn’t obviously wrong. It was aimed at a version of me that worked differently than I do.

But then a few steps in, something was wrong. Something wasn’t sitting right. I couldn’t quite name it yet. It was just that feeling that the thing we were building wasn’t going to work the way I needed it to.

I eventually went back and looked at those conversations. What struck me wasn’t that ChatGPT was wrong. It was how many times I told it I was still confused while we both kept building anyway.

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The Trap Isn’t AI. It’s Assuming the Misfit Is You.

Looking back at those conversations, I realized something uncomfortable. AI wasn’t wrong.

It wasn’t making things up. It wasn’t giving me nonsense. It wasn’t sending me in some obviously ridiculous direction I could dismiss and move on from.

That almost would have been easier. The harder part was that the answers sounded reasonable.

Your AI keeps guiding confidently somewhere that sounds useful. Your gut is quietly saying, this doesn’t quite fit. And you keep going anyway.

Because somewhere along the way, you decided the problem was probably you.

You’re thinking, this is a me problem. You haven’t found the right system yet. You haven’t explained it clearly enough. Everyone else seems to have it all figured out. When the AI guides you somewhere that feels a little off, you don’t stop. You push through because pushing back means trusting your own gut over the thing that sounds more certain than you feel.

And that feels riskier than maybe just being wrong.

That’s the trap.

Not bad information. Not a bad tool. Not even bad advice.

The quiet decision that the misfit is your fault.

And here’s where you let AI keep driving you to a destination that you already know is not really the place you want to be.

I almost did it during those three conversations with ChatGPT.

I had the feeling, and yet I kept building anyway, telling myself the confusion meant I wasn’t getting it.

I can see it now in the conversation itself. I wasn’t saying, this is working. I was saying some version of, I am no more clear now than before.

That’s the part I keep coming back to.

I wasn’t ignoring the feeling because I didn’t know it was there. I was ignoring it because the system sounded so reasonable.

And that might be the sneakiest part of working with AI.

It doesn’t have to be wrong to pull you away from yourself.

Sometimes it just has to sound more confident than you feel.

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What Changed When AI Started Asking Instead of Guiding

Eventually I hit a point where I couldn’t keep pretending the confusion was mine.

I finally typed:

“Stop acting like you know what is best and start getting clarification.”

It wasn’t written because I was angry with ChatGPT. It was written because I realized we were solving a problem I hadn’t actually agreed to solve.

That single sentence changed the conversation.

ChatGPT started asking instead of guiding:

• Where do the decision records need to live?

• What breaks if they move?

• What are you trying to find your way back to?

Those questions changed everything because they forced me to explain my thinking instead of evaluating its thinking.

At first I thought the breakthrough was better context. Looking back, I don’t think it was. The breakthrough was that ChatGPT stopped assuming it understood the problem and started verifying that it did.

Better context assumes AI already understands the problem and simply needs more information. Clarification questions test whether AI understands the problem at all.

I thought I was asking it to help me build a wiki. It turned out I needed help figuring out whether a wiki was even the right answer.

Those are completely different conversations.

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The Misfit Wasn’t the Problem. It Was the Data.

Looking back, that misfit turned out to be the most useful part of the entire experience.

I kept treating it like evidence that I hadn’t found the right system yet, when it was actually telling me I was solving the wrong problem. The wiki was never the answer I was missing. It was the catalyst that surfaced the question I should have been asking all along.

The questions started changing.

Instead of asking: “Where do I store this?”

I started asking: “If I need to remember why I made this decision six months from now, where would I naturally go looking for it?”

That was a completely different problem.

The question wasn’t where my information belonged. The question was how I found my way back to my own thinking. No popular method could answer that for me because it wasn’t really a knowledge management question.

It was a personal navigation question.

That’s what Marie Kondo started years earlier without me realizing it. Her method wasn’t wrong. Karpathy’s wasn’t wrong either. Neither one solved my problem because neither one was actually my problem to solve.

What they did do was expose the question underneath it.

That’s what I take away from this now.

When a new method shows up and everyone seems convinced it’s the answer, I don’t ask whether it’s good. I ask whether it’s solving the problem I actually have.

Those are two very different questions.

The misfit isn’t a verdict on you. It’s information.

When something feels off a few steps in, that feeling is data, not a sign you’re behind. The trick is catching it early, before you’ve built the whole thing, and saying it out loud instead of pushing through.

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How I Now Test Whether a Popular AI Method Fits Me

This experience changed something about the way I work with AI.

I don’t ask it to help me build the method anymore.

I ask it to help me decide whether the method deserves to be built in the first place.

When something catches my attention—a video, an article, a framework, a thread—I paste it into ChatGPT before I start reorganizing my world around it.

I want to try this, but I’m not sure it will work for me. Review the reference and find the gaps or inconsistencies with how I work. Ask me if you’re not sure or need to be more clear.

That last sentence is the part that matters most.

Ask me if you’re not sure.

It’s such a small change that it’s easy to overlook, but it completely changes the relationship. Instead of assuming it understands how I think, AI has permission—even the responsibility—to stop and verify it before it starts building a solution.

That one sentence also changes my responsibility.

Instead of evaluating the answer after it’s built, I’m asking AI to challenge its assumptions before we build anything together. If it can’t tell where the method and the way I actually work stop lining up, it has to ask instead of guessing.

That’s a very different conversation than simply asking it to make me a better system.

It’s a small shift, but it puts me back in the driver’s seat before I’ve invested three conversations building something that was never really mine to begin with.

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Before You Build Someone Else’s System

Looking back now, I don’t think Marie Kondo was ever wrong. Her method simply wasn’t built for me. Karpathy wasn’t wrong either. The wiki wasn’t a bad idea. It just wasn’t answering the question I actually needed to answer.

That’s the pattern I keep overlooking.

I treated each one like a test I was failing, when the real question was never whether the method was good. It was whether it fit the way I actually think and work.

I thought the lesson was going to be the system I eventually built.

It wasn’t.

The lesson was the moment I finally stopped building long enough to question whether I was building the right thing in the first place.

Now, whenever I feel that rush of “This is it. This is the missing piece,” I treat it as a signal to slow down instead of speed up.

Not because the method is probably wrong. Because I haven’t yet answered the more important question.

Is this actually solving the problem I have?

Because the question was never whether it works. It was whether it works for you, and you’re allowed to ask that question before committing yourself to someone else’s way of thinking.

That’s still one of my favorite ways to use AI—not to tell me what to do, but to help me figure out whether I’m solving the right problem before I spend weeks building the wrong solution. Sometimes the simplest questions are still the best ones.

“Is this actually for me?”

“Will this help me accomplish what I’m trying to do?”

“What assumptions am I making that I haven’t questioned yet?”

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If something feels off, don’t assume you’re the problem.
That’s exactly why I created the Something Feels Off waypoint—to help you slow down, sort through the friction, and figure out whether you need a different tool, a different method, or simply a different question.

I know that feeling. Not because of AI. Because of a book.

I’m a reader. It’s how I disconnect. No screen, no noise, just me and the page while ideas swirl in the back of my head. Most of what I read is fiction and biographies, because for me it’s about the story. And I have a rule: if a book doesn’t grab me, if it’s slow or it’s just not for me, I put it down and move on. No guilt. Life’s too short for a book that isn’t landing.

Then Lean In came out.

It wasn’t just a bestseller. It was a movement. Everyone was reading it, talking about it, building whole conversations around it. So I told myself, okay, I have to read this and see what all the fuss is about.

I had a hard time getting through it. Normally that’s my cue to stop. But this time I made myself finish, cover to cover, because of all the noise around it. Everyone seemed to be getting something out of it. What was I missing? Maybe if I just read the whole thing, I’d see what they saw.

I finished it. And the only thing I came away with was this: I don’t think this applies to me.

Which should have been fine. Except it didn’t feel fine. It turned into the question that actually stung. Why doesn’t this apply to me? What’s wrong with me that I can’t connect with the thing everybody else loves?

A Ladder With Every Rung Already Labeled

For a long time I didn’t have words for what bugged me about that book. I just knew it wasn’t for me, and I felt a little bad about that.

Then AI showed up, and the same feeling came back.

Look around at the AI conversation right now. Before most of us have figured out where it even fits in our work, there’s already a ladder built, every rung labeled. AI expert. Prompt engineer. AI strategist. Thought leader. The lists of top voices to follow. The “women in AI,” the “women in tech.”

I want to be careful here, because this part matters to me. Women in tech have been overlooked for a long, long time. The visibility is earned. The recognition is good. I’m not knocking anyone who’s climbing, and I’m not knocking the women who are finally getting seen. That’s not the problem.

The problem is what the ladder quietly says to everyone standing near it. That to matter, you have to climb. That if you’re not building the app, growing the audience, becoming the voice, then you’re behind. Or worse, that you’re holding yourself back out of fear.

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There’s Another Way to Lean In

Years later I finally understood what was bothering me about the message and the movement.

Lean In had one idea of success, and it was a narrow one. Climb. Get to the table. Get to the boardroom. And if you weren’t reaching for that, the book had an explanation ready: you simply hadn’t found your nerve yet.

But some of us weren’t afraid. We’d already looked at that version of success and decided it wasn’t the one we wanted. We’d chosen our own terms. Family, or a different pace, or work that fit the life instead of the other way around. The book couldn’t see that choice. It only saw a woman who hadn’t climbed yet. It invented a problem I didn’t have, and then handed me the guilt for not having it.

That’s the same move I feel in the AI conversation now.

There’s one shape of success on offer. Build the thing. Get loud. Become the authority. And if that’s not what you’re after, the explanation is already written for you: you must be scared of something, or behind, or playing it too safe.

I don’t buy it. And I don’t think you have to either.

Because there’s another way to lean in. You don’t have to lean in by going faster. You can lean in by going deeper.

When I say deeper, I don’t mean deeper into some specific app or model, learning every setting and every update. I mean deeper into the thing you’re actually trying to do. Pushing it to the edge of what you need it to do for you, and then stopping there. That’s enough.

And deeper is allowed to look small. It can be solving the single most time-consuming, annoying problem you have — the one that affects nobody but you, that nobody will ever clap for. It can be something you build to help you right now that’s useless in six months. That still counts. That’s still leaning in.

You took a chance on something small and unglamorous while everyone else chased big and shiny. Nobody hands out labels for that. Doesn’t make it matter less.

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What Lasts When Everything Keeps Moving

Here’s what I keep coming back to. Nobody has this figured out. The technology shifts every week, and outside the handful of people actually building it (it being the AI models), we’re all working with incomplete information. Me included.

That used to make me anxious. Now it does the opposite. If nobody has solid ground, then I don’t need to either. I just need to keep deciding what matters to me as things move.

I’ve lived through enough technology changes to trust that. In my twenties it went from analog to dial-up to modems. In my thirties, wifi and working online. Heading into my forties, online business became a reality for a lot of us. Every shift opened a door onto a dimly lit hallway. Nothing you could plan for, just feeling your way while you waited for more light to lead you.

Now there’s so much light you can’t figure out how to navigate. I’ve never felt anything move this fast. It’s exciting and it’s a little scary, both at the same time.

And what carried me through every one of those changes wasn’t being first to know, or having the most to say about it. It was being able to ask a decent question and decide what actually mattered to me.

That’s the skill that lasts. Not memorizing this month’s tools. Knowing how to decide.

So I have a few questions I ask myself now, almost without thinking, every time something new shows up:

Does this affect me?

Is it going to make my life better, or just different?

Does it touch my relationships, or the goals I’ve actually set?

That’s it. It sounds like me-me-me, and honestly, it is. I’m putting myself first. Not to get ahead of anyone, not to push some agenda. Just to know, for my own sake. Curiosity is allowed to be only curiosity.

And those questions don’t just sort AI tools. They sort anything. A medical decision. A legal one. Money. Anywhere the noise is loud and the stakes are yours, the work is the same. Figure out what’s actually for you, and let the rest go by.

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The Smallest Thing I Built

Where the idea came from.

My AI conversations kept going in circles. Sometimes it was because I’d picked up someone else’s prompt, and what it handed back didn’t match the way my brain actually processes information. Other times I gave it conflicting information, or sent it off on a tangent. But the bottom line is I was getting frustrated, because it didn’t seem like AI was the smartest book on the shelf.

How I applied it.

Back in late May, I wrote myself a short collaboration profile. A plain description of how I think and work:

• I figure things out by talking them through.

• I need one question or decision at a time.

• A wall of text or a big framework too early loses me.

• I’d rather react to something small than start from a blank page.

Here’s the actual ask I gave the AI to build it:

I want to create a short context doc for the way that I think, process, and work, because what’s happening is that with a lot of my asks, the waters are getting muddied. Thinking is different than processing, and a lot of the time the AIs get confused by that. I’m imagining something short and sweet that I can paste in or put in instructions, because a lot of my conversations are going sideways. When you and the other AIs formulate answers, it’s for John Q. Public, not someone who struggles a little bit like I do. Maybe we go through ten questions or so and then come up with a summary.

Now, whenever I’m working on something, whichever AI I’m in, I hand it that context first.

So that I’m not perpetually scrolling to find the advice or information I need. So that I get presented with options and time to think about them, instead of trying to decipher everything at once. Basically, I needed the AI to understand how I process information, so the output is specific to me.

The result.

And now it does the one thing I ask of it. The conversations stop circling. The AI meets me the way I process information instead of the way someone else does. It isn’t clever and it isn’t impressive. Nobody would look at it and jump up and down and go, why didn’t I think of this? I just use it every day. Instead of reiterating all of this in every conversation or every thinking session, I give it the parameters, and it knows how to have the discussion with me.

The tie forward.

And this is what I mean by building something small, just for you. If you’re sitting there feeling behind, wanting to build something big enough to count, this is the size of thing I mean. A plain document that makes one part of my day work the way I do. That’s a build. That’s what leaning in is to me.

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Back to the Book

So back to Lean In.

For years I carried that feeling from the finished book around as a small, quiet failure. Everyone else got something out of it, and I didn’t, and I let that mean something was off with me.

It wasn’t. The book had one idea of success, and it wasn’t mine. That’s all. The thing wasn’t wrong with me. The yardstick just wasn’t mine to measure against.

I think a lot of us are about to do the same thing with AI. Pick up the version of success that’s getting all the noise, hold our own quiet work up against it, and decide we’re behind. When the truth might be that we’re measuring with someone else’s ruler again.

This is the part I don’t want to lose. While everyone’s looking up at the loudest voices, the people actually changing things in our lives are often the quiet ones. The person who solved one real problem and mentioned how. The one who said here’s what I tried, and here’s what I found out, with nothing to sell you. We’ve been trained for a few years now to point our attention at the experts and the thought leaders. I wonder how many of the people making the biggest difference we’re walking right past.

You don’t have to become an AI anything. You don’t have to keep up, or get loud, or build something big enough to earn a label.

You just have to find the thing that’s actually yours, go a little deeper there, and share it if you feel like it. Not to get ahead of anyone. Just because it was yours, and it worked.

That’s leaning in too. It always was.

So here’s the one thing I’d leave you with, if you want it. That’s all I did when I wrote that little profile to help AI understand how I take in information and ask for what I need. It’s the kind of problem most people don’t even think to solve, and it’s quietly made the biggest difference in how I actually use AI.

So don’t go learn another tool. Pick the single most annoying, time-eating problem you have this week, the one nobody else would even notice, and see if AI can help you make one small dent in it. That’s the experiment. Not to have something to show for it. Just to find out.

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But sometimes the harder part isn’t picking the problem. It’s the nagging sense that you’re measuring against the wrong thing and can’t quite name what’s off. I built a short walk for exactly that. A few minutes, your own words, and you leave with a next move, not more noise.

Something feels off →

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The expertise is already yours. You just needed a framework to trust it again.

It’s not that I wanted to pick up her habits or her quirks. At the time I definitely didn’t want to raise five boys and three dogs. Okay, maybe the dogs. And the smoking and being put together 24/7 didn’t fit with the tomboy me.

But her confidence was something. And the way she handled the side-eye and the criticism — that was inspiring. I learned a lot from her.

Most likely it was due to the filters I had unknowingly developed. You know that gut reaction that tells you when something is off or not quite the right fit.

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You already know how to do this

Even all these years later, we still do this. Every day, with people and ideas and advice, we’re sorting what fits from what doesn’t.

But somewhere along the way it got harder to hear. The internet filled up with people who sound certain. The feeds, the newsletters, the courses, the YouTubers — everyone with a framework, everyone with a recommendation, everyone two steps ahead of where you are.

And it started to feel like a tool problem. Or an AI problem. Or a problem with not knowing enough yet.

It’s none of those. It’s a filtering problem.

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Why it’s so hard right now

Part of what makes this moment tricky is that almost no one is actually an expert yet.

AI is new enough that real expertise is rare. But you wouldn’t know it from the feeds. Everyone has positioned themselves as the person who figured it out. And when everyone sounds like an authority, the usual signals you’d use to sort them — credentials, confidence, follower counts — stop telling you much.

Then there’s the advice that’s just old. Techniques that made sense a year ago and don’t anymore. “Start every prompt by telling it to act as your role.” “Begin with the perfect prompt.” Some of it was never necessary, and as the tools evolve, more of it falls away. But it keeps getting repeated, because it once worked, and repetition sounds like authority too.

And the hardest one: plenty of brilliant people are sharing genuinely good work that still has nothing to do with your business. They’re not wrong. They’re just not building what you’re building.

That’s the part that catches you. Not the bad advice — you can spot that. It’s the good advice meant for someone else.

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Valuable is not the same as useful

So how do you sort the good advice meant for someone else from the good advice meant for you?

Not by deciding who’s worth following. By noticing the difference between valuable and useful.

Someone can be valuable. They expand how you think. They show you something you hadn’t considered. is this for me — much of what she shares isn’t built for my business, but the way she works changes how I see a situation.

Take her Open Door project, where a group each builds a piece of one collective space. Or the way she distills insights from others using AI and art. None of it is my use case. All of it shifts how I think about what’s possible.

That’s valuable. Valuable isn’t the same as useful.

Useful is when someone’s work consistently helps you make a better decision. This is also why the template habit can quietly work against you — borrowed structure that fit someone else’s process, not yours. Mia at is useful to me because she shares the thinking and the process, not just the finished build. I can take how she works through something and adapt it to my own business.

The value is in the method, not the output.

And then there’s the source you keep, even knowing most of it isn’t for you. Stu Jordan has been my AI go-to for years. He pushes the limits, further than I have any reason to go, because I’m not building what he’s building. I didn’t stop following him. I built a filter for him, a sense of what to actually act on and what to admire from a distance.

That filter is the whole thing. Not picking the right people. Knowing what to do with the ones you’ve got.

A few questions that do the work

Once you start filtering on purpose, a few questions do most of the work.

The first one I ask before building anything: why am I building this? Is it because it’s cool and I want to play with it? Because it actually moves something forward? Or because I want to learn the technique? All three are fine answers. The trouble is when you don’t know which one you’re in — that’s how “cool” quietly costs you a week.

The second is about who’s doing the recommending. When someone tells you a tool is the latest and greatest, it’s worth asking what’s in it for them. A lot of the time there’s an affiliate commission attached, or they’re building an offer around it. That doesn’t make them dishonest. It means the recommendation has a second job, and you should know that before you adopt it.

And the third is the one that stings a little. If you’re saving something for someday — a tool, a thread, a technique — but you’re not doing anything with it, is the save even worth it? By the time you come back, it may be outdated. The pile isn’t progress. It just feels like it. (I’ve written before about how saving outpaces doing — the gap between learning and acting.)

None of this means stop following people who are nothing like you. I do it constantly. It means take what they’re doing and bend it to your situation — your model, your clients, your use case. The signal that you’ve crossed a line: when their work makes you doubt yourself, or change course for no reason you can name. That’s not learning anymore. That’s drift.

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The prompt graveyard

I have a folder full of prompts I’ll probably never use. It’s the new version of the swipe file graveyard — collecting that feels like progress and isn’t.

I collected them the way everyone did. Prompt engineering was the thing, and we all became collectors — saving, screenshotting, copying every clever prompt we came across, sure that somewhere in the pile was the magic one that would unlock it all. I have prompts in there I never once tried. Others I saved are for a version of these tools that doesn’t really exist anymore. Old asks for an old moment.

That folder is what no filter looks like.

Not a character flaw — just what happens when you let everything in because it might be useful someday, and never run it through the gut check of is this mine.

So that’s the decision, and it’s a quieter one than it sounds. Keep following Alyssa, Mia, Stu, and the people who make you think. Keep learning from people who build nothing like you. But put it through the filter on the way in, not into a folder for later. Decide what’s yours and act on it now. Then put the rest aside — not because it isn’t good, but because good was never the question.

If you want to see your own filter at work, go look at the prompts you’ve saved:

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Back to the neighbor

I think about that neighbor sometimes. She never asked anyone’s permission to be exactly who she was, and she never tried to be anyone else either.

You have a version of her too. Someone you watched, somewhere, and knew without deciding it: that part is mine, that part isn’t. You didn’t study them. You didn’t save them to a folder. You just took what fit, and moved on from the rest.

That instinct is still in there. It’s the same one you’re trying to use on every expert, every tool, every thread you’ve saved for someday. You’re not missing a skill. You’re trying to remember one you’ve had since you were a kid, watching someone three houses down be entirely themselves.

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Thinking Through Something?

If you’re sitting with a decision, workflow, tool stack, or AI process that technically works but doesn’t feel quite right, I offer limited advisory sessions for solo business owners trying to sort through the noise without adding more complexity.

Think It Through Together →

So I watched my friends get handed theirs. No caveats. They turned sixteen, took the permit test, practiced, got the license. That was the whole path.

Mine had an extra step bolted onto the front. And I was peeved. Genuinely angry about it. Why was the bar set higher for me than for everyone I knew? It took me longer. I was the passenger while my friends were the drivers. I got there eventually. Had the job, got the license. But for a good while I was sure the rule was unfair, and I second-guessed it the whole time. Is this even worth it?

Then I turned twenty-six. I remember the moment. Holy crap, I’m in the next phase, first twenty-five behind me. And I looked back to take stock of what I was grateful for.

The rule was on the list.

The extra step wasn’t a disadvantage. It was the thing that built my relationship with money, with responsibility, with earning what I had.

The harder path hadn’t gotten me to the same place by a slower route. It built something the easy path didn’t build.

I’ve been thinking about that rule a lot lately, because I’m standing in the same spot again. Except this time, nobody set the bar for me. I set it for myself.

This isn’t the first time I’ve caught myself following frameworks built for someone else instead of trusting the path that actually fits.

Three tools, one job

I sat down a short bit ago to settle a question I’d been carrying: I’m paying for three different AIs that can create images (one only creates the images). Do I actually need all three?

So I ran a test. I pulled up a featured image I needed to make, fed each tool a few examples of my own work and my style guide, and wrote a prompt for the scene I wanted. Then I gave the same setup to Nano Banana, to ChatGPT, and to Midjourney. Three tools, same job, head to head.

Midjourney landed it (it being my style). Every time.

The other two missed. Every time. I adjusted the prompt. I changed the references. I tried the tips and tricks everyone swears by, the exact phrasing, the magic words, the structure that’s supposed to produce the perfect image. Nothing got me the look I was after.

And here’s the part I want to be honest about. I didn’t walk away thinking those tools work differently. I walked away thinking what am I doing wrong.

The doubt that wasn’t really about me

That question sent me looking. Not at the tools. At myself.

I took it to Gemini. I took it to ChatGPT. I even took it to Claude. I described what I was doing and asked, more or less, what’s off here? What am I missing? I was sure there was a setting I’d skipped, a technique I hadn’t learned, some obvious thing everyone else knew that I didn’t.

This wasn’t new, by the way. I’ve been with Midjourney since it lived on Discord. And Discord and my brain did not get along. Not the image-making, the finding. Every image I made disappeared into a chat thread, and I’d lose it. I almost left over that. Then they moved to a browser, and that was the change that kept me. So I’d already been through one round of is it me, or is it the tool and stayed.

Then there’s the prompting itself. Midjourney V7 and V8 are, functionally, two different engines. The way I asked V7 for an image is not the way V8 wants to be asked. I had to relearn it. And the relearning cut against everything I’d been taught about prompting, because Midjourney doesn’t want instructions. It wants you to set a scene. You don’t tell it to do X, Y, Z. You give it creative input and let it interpret.

That’s a hard hump to get over when every other tool has trained you to be precise and literal.

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The expertise is already yours. You just needed a framework to trust it again.

It was never me

Here’s what the rabbit hole finally turned up.

It’s not me. Midjourney isn’t a worse version of ChatGPT or Nano Banana. It’s a different kind of tool. It works in layers. It’s built for artistic interpretation, not instruction-following. So no matter how perfectly I copied the prompting that worked for everyone else, I was never going to get the same result. I was using a different kind of engine to do a different kind of thing.

The doubt was the wrong question. “What am I doing wrong” assumes there’s a right way I’d failed to find. There wasn’t. There was just a tool that asks for something different than the popular ones do, and a result, on the other side of that difference, that I couldn’t get anywhere else.

The bar I set for myself

This is where the license rule came back to me.

At sixteen, the higher bar was handed to me. My parents set it; I just had to clear it. What I’m doing with Midjourney is the same shape, an extra step everyone around me skips, except now I’m the one holding the bar. Nobody’s making me take the harder path. I’m choosing it.

And I could have not chosen it. I could have settled. I could have taken the popular tool, accepted images that were fine, and told myself the difference didn’t matter. That would have been easier. It would have cost me less time and less relearning.

But I’d be making everyone else’s process. I’d be taking something that works for me, something people recognize, something they see and know is mine, and trading it for a result I don’t actually want, just because the path to it is smoother.

The license rule taught me what that trade costs. The easy version gets you the license. It doesn’t build the thing the harder version builds. My images are distinctive because I stayed on the harder path long enough for them to become mine. That’s not stubbornness. That’s the higher bar doing exactly what a higher bar does.

You don’t have to pick just one tool

Staying with Midjourney does not mean I’ve sworn off the other tools. That’s the part I don’t want misread.

Look at any of my articles. The featured image is Midjourney. But the infographics, the step-by-step visuals, those aren’t, because right now Midjourney can’t handle heavy text the way ChatGPT and Nano Banana can. I use Perplexity and Tally for research. I use Claude to think and draft. I use Midjourney for one kind of image and Chat for another. It’s the same instinct behind coming back to the tool that actually worked after testing the alternatives.

Holding a higher bar doesn’t mean forcing one tool to do everything. It means knowing which result you’re protecting, and being honest about where another tool genuinely does the job better.

The bar isn’t loyalty to a tool. It’s loyalty to the result.

Before you switch

Every time a new tool drops, the comparison articles start, and the question underneath them is always the same: should you switch? It’s easy to let that question turn into doubt about every choice you’ve already made.

So here’s a better one to sit with.

What does your current tool produce that you’d genuinely miss if you switched, and is that thing the result you actually want, or just the result you’re used to?

If the honest answer is nothing, I’d be fine, then switch. The new tool might be the better fit, and there’s no higher bar worth holding for its own sake.

But if there’s something real there, a result that’s yours, that you’d lose, that you worked to build, then the doubt isn’t telling you anything true. It’s just noise from watching everyone else take the smoother path. You already cleared the harder one. That was the point.

If this tension feels familiar, you may want to keep exploring from here.

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Built for Someone Else: Building workflows that fit your actual business and energy instead of someone else's blueprint.

Thinking Through Something?

If you're sitting with a decision, workflow, tool stack, or AI process that technically works but doesn't feel quite right, I offer limited advisory sessions for solo business owners trying to sort through the noise without adding more complexity.

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Chances are you’ve already tried at least one tool that promised to make your life easier — and quietly abandoned it three weeks later. You’re not alone. Over half of small business owners are experimenting with AI but never committing. And 82% of the smallest businesses say AI simply “isn’t applicable” to them.

That’s not a technology problem. That’s a translation problem. And that’s what this is about.

I went to Vo-Tech in high school mostly because I wanted a hands-on learning experience. Cooking was where everything clicked — not just the process of making food, but the chemistry behind it. The measuring. The way combining the right ingredients in the right order creates something that didn’t exist five minutes ago. Sometimes it was really tasty. Sometimes it bombed epically. Either way, I understood what happened and why.

The plan was culinary institute after graduation. James Beard. The full professional kitchen. I wasn’t just dreaming — I was training.

Then came the blind taste test. Mandatory for admission, no way around it — and they couldn’t guarantee there’d be no seafood in it. With my allergy, that took me completely out of the game. Not a maybe. Not a workaround. Just like that, the award-winning culinary path was off the table.

But that path closing didn’t mean it was the end of my love for cooking.

This was the recalibration moment. A moment of — okay, this door is shut, so where do I go now? The Culinary Institute was the plan. James Beard and the awards were the destination. And neither of those was happening now.

It stings when you’ve been working toward something specific.

But what I knew I wasn’t going to do was decide that cooking was broken for me — or that I’d wasted my time training for something that didn’t pan out. Those skills were still there. The love of it was still there. I just had to figure out what cooking actually looked like without a classically trained chef in a restaurant at the end of the road.

Long story short, I never stopped cooking.

The classically trained path closed, but cooking stayed open. I still cook for friends, family, my husband, different events. Sometimes small meals, sometimes big ones. Sometimes I just open the fridge, look at what’s in there, and make something cohesive out of it.

And nobody has ever looked at a meal I made and said, “Whoa, I can’t believe you never went to culinary school.”

Because the goal was never about the restaurant or the awards. When I create a meal, it allows me to be part of the experience. That was always the point.

So I just had to figure out which version of cooking actually fit into my life.

AI automation works the same way.

Right now, every piece of content out there is pointing you toward the restaurant — full automation, removing yourself from the process. It’s all about building agents and sub-agents, AI-scheduled tasks, letting AI run while you sleep. Let AI do the work so you can scale, grow, and be everywhere at once.

But that’s not what you actually need for your business. Because as a creative and as a solo entrepreneur, you need to be part of the process — not completely removed from it or paralyzed by it.

This is the part that’s real, and one of the things nobody is talking about.

There are different levels of AI involvement, and the level that fits your business should come from your actual needs, your processes, and honestly, how much of yourself you want to keep in the work. Not from whatever framework someone built to showcase their expertise or sell you a tool.

Some people will want to run the restaurant with a full staff. Others just want to cook a cohesive dinner with what they have in their refrigerator. Those are different goals, and neither one is wrong.

So let’s break it down into the simplest terms first.

The Pantry — What’s Already on Your Shelf

Step one of AI automation for solo business owners: know what you have before you buy anything else.

In the AI world, this is your stack. The tools you’re already paying for or using for free — ChatGPT, Claude, Gemini, Perplexity, Canva, whatever’s already open in your browser on any given day. The subscriptions you signed up for with good intentions. The free tiers you’re dabbling in.

This is what the industry calls your AI tooling or your model layer — the raw ingredients sitting on the shelf. And just like a real pantry, most people have more in there than they realize. The problem isn’t that the pantry is empty. It’s that nobody’s taken inventory.

Before you can cook anything, you need to know what you have. That’s it. That’s the whole pantry step.

The question at this level: What AI tools am I actually using right now — and what am I paying for that I haven’t touched in three weeks?

The Recipes — The Things You Already Do Well

Where AI assistance (not full automation) fits into your existing business processes.

Recipes are your repeatable processes. The tasks you do regularly, in roughly the same order, that produce a reliable result. Writing a newsletter. Responding to client inquiries. Putting together a proposal. Onboarding a new client. These are your recipes.

Here’s the thing about recipes you’ve been making for years: some of them are so ingrained that you move through them on autopilot. You don’t notice what’s in them anymore — which means you also can’t see what could be improved or where AI could genuinely help. You’ve always done it that way. It works. End of story.

But other recipes are ripe for a shortcut. And this is where AI assistance — not automation, assistance — actually fits. Think of it like buying a rotisserie chicken from the grocery store instead of roasting your own. The meal still gets made. You’re still cooking. You just didn’t spend two hours on the part that didn’t need two hours.

In practice, this looks like using AI to draft a first pass, generate an outline, summarize a long document, or repurpose something you already created. You’re still in the kitchen. You’re still making the meal. You’re just not doing every single step from scratch.

The industry calls this: AI-assisted workflows, co-pilot tools, or prompt-based automation. It sounds complicated. It’s just a smarter grocery run.

The Meal Plan — Coordinating Across the Week

This is what most AI agent advice is actually talking about — and where solo owners need to decide how far to go.

A meal plan is sequencing. It’s not one dish — it’s how the dishes connect across a stretch of time. Monday’s roast chicken becomes Tuesday’s soup. The prep you do on Sunday makes Wednesday easier. Things flow into each other with intention.

In your business, this is where scheduling and coordination come in. What runs when, in what order, triggered by what. Some meal plans are simple — a sticky note on the fridge that says what you’re cooking each day of the week. Others are full meal delivery services: planned, packaged, and dropped at your doorstep on a schedule.

This is the level most AI agent content is talking about — automated workflows, scheduled tasks, multi-step sequences that run with minimal input from you. Tools like Zapier, Make, n8n, or CoWork live here. So do the AI agents and sub-agents everyone is building in public right now.

And here’s where the all-or-nothing trap springs: most of the content skips straight to “build the full meal delivery service” without asking whether you actually need it.

“A sticky note on the fridge is a meal plan too. It doesn’t need to be a subscription box.”

The question at this level: Which sequences in my business actually benefit from running on their own — and which ones need me in the loop?

The Leftovers — What Actually Survived

The most important step in any AI workflow: testing what works, ditching what doesn’t, and letting your results guide the next decision.

This is the most underrated part of the whole framework, and the one nobody talks about.

After every meal, you find out what actually worked. What got eaten. What got pushed to the side of the plate. What you’d make again and what you’d quietly retire. That feedback doesn’t stay in the kitchen — it goes back into the pantry, informs the next recipe, shapes the next meal plan. This is how the whole thing gets better over time.

In your business, this is your testing and iteration layer. It applies whether the process is automated or manual, yours or borrowed. What did the automation actually save you? What did it break? What did you think would be easier that turned out to be more complicated? What small thing ran quietly in the background and genuinely freed up your week?

The industry calls this: Retrospectives, feedback loops, iteration cycles. Which — fair. But leftovers is more honest. Some things survive the week and get better. Some things go in the trash. Both are useful information.

I’m in the middle of this right now. And I can tell you exactly where I drew the line — and why.

My Content Lab pipeline — the process I use to research and write every article — sits firmly in the Recipes layer. The creativity is the work. My experiences, my take, the hands-on-ness of it. That’s not something I can hand off to AI, or to anyone else, and still have it be the same thing. The moment I remove myself from that process, I’ve handed off the thing that makes it worth reading.

“If I outsource the recipe, I’m just serving someone else’s food.”

Same goes for my chief of staff dashboard. That lives at the Meal Plan level — it’s how I sequence and coordinate my week. But if I hand that completely over to a process, it becomes about productivity. And managing my energy, not my task list, is the whole point. I’m not willing to trade that.

But here’s where the Leftovers come in. My CoWork automations — subscription tracker, daily news recap — those run on a schedule and do their thing without me. I kicked them off, I tested them, and I know what they do. They free up bandwidth without removing me from anything that matters. They survived. I’d repeat them. That’s how I know they belong in the kitchen.

That’s my line. Not a framework someone handed me — mine. Built from figuring out what I actually needed to stay in the work, and what I was fine letting go.

So here’s the question I want you to sit with.

What’s actually in your pantry right now?

Not what you think you should have. Not what someone else’s stack looks like. What do you actually have on the shelf — the tools you’re using, the processes you’ve already built, the tasks you do on repeat every single week?

And from that — is there one dish worth making? One recipe that could use a shortcut, one part of your meal plan that could run on its own without you losing anything that matters?

You don’t have to build the restaurant. You just have to know what you’re cooking and why.

If you’re feeling stuck between “I should be doing more with AI” and “I don’t even know where to start,” that’s exactly the conversation DigiNav is built for.

If you’re a paid subscriber, the next section is for you.

I put together a practical framework for actually running a project once you know what’s in your kitchen — without losing the thread, without starting over every session, and without burning the kitchen down. It’s the how behind everything we just talked about. You’ll find it below.

Read more

This year’s winter jaunt was laid-back St. Augustine, Florida. Getting there and back meant two days in the car — the perfect stretch for catching up on work, reading, and whatever sparks come from hours of uninterrupted road time.

After my turn to drive, I decided to get an article or two into the pipeline. Except the work couldn’t be tackled on my iPad. Pulling out the laptop isn’t usually a big deal, but the computer bag was wedged in the back of the car and getting to it required some gymnastics I wasn’t in the mood for.

That’s where the rubber hit the road on my fancy Cursor content creation process.

The rubber being Cursor. The road being this: every conversation felt like starting from scratch. I was re-explaining myself every time. The context that makes working with Claude feel like working with someone who actually knows me — the memories, the context docs, the way I’ve built up how I operate over dozens of sessions — none of that was there. So while the AI agent was doing its job — technically — I was starting from scratch. Again.

That’s when it hit me: your AI workflow is only as good as what your AI actually knows about you.

Moving from Cursor back to ClaudeAI

The decision to move the full content pipeline out of Cursor had already been made — that part was clear. But mid-migration, something stopped me. The experiment docs were being glossed over and they’re the foundation of every article I write. Get that wrong and everything downstream is shakier than it needs to be.

So before anything else, I dealt with that first.

I had nine experiment files sitting in Cursor as markdown docs. I uploaded them all to Claude, and we assessed the existing Notion database together — what to keep, what to cut, what was missing entirely.

Claude fixed the schema.

The old template sections — Prompts, Inputs, Outputs, Artifacts, Notes, Next Iteration — got replaced with the structure that actually matched how I work: What I Built or Changed, How I Tested It, What Happened, Verdict.

Then the MCP applied all the existing records into the updated database. That’s where it got interesting. The first test run overwrote records instead of updating them. We fixed it and retested. Four rounds before it landed cleanly.

Once the existing data was solid, I added the forward workflow: at the end of any build session, ask Claude to document it directly into Notion. I live-tested this in the same conversation — one API call, all properties and body content written correctly in one shot.

The improvement I didn’t see coming: documenting the build directly through the conversation removes more friction than any tool switch ever could.

The breaking points, or not.

Nothing broke in the technical sense. Which is almost the point.

The friction in Cursor wasn’t loud. It didn’t throw errors or fail visibly. It just quietly required more from me than I realized — more re-explanation, more re-context, more process around the edges. The kind of thing you stop noticing because you’ve adapted around it.

What I didn’t expect was how much I relied on the build notes — the Experiment doc — as the actual foundation of each article. It adds the context, the actual conversation threads from AI and sometimes screenshots.

It was a structural piece that wasn’t getting its due. Cursor’s AI agent didn’t have access to the relationship Claude has built or the conversation memory. That’s not a Cursor problem — it’s just a fundamentally different thing.

Because sometimes broken isn’t when things don’t work, it’s when things are overlooked.

And if I’m honest, I’d been chasing a shinier setup instead of trusting the process I’d already built. The tools that had context — Claude, Notion — were right there. I just had a layer in the middle that didn’t.

If I had to do it again.

Trust the process you already built. Notion had been functioning as my persistent memory all along — storing context, tracking experiments, holding the thread between sessions. Claude had been the thinking partner. Those weren’t gaps to fill with a new tool. They were the foundation worth building deeper into.

I’d stacked a layer on top instead of doubling down on what was working. The switch didn’t require a complicated migration plan. It required recognizing that the combination I was working around was already solving the problem I needed solved.

New and shiny has a cost that’s easy to miss: it starts with zero context. And zero context means starting from scratch. Every time.

Decision one in the bag.

Kill Cursor for content creation. The decision wasn’t about features or capability — it was about context. Notion for persistent memory. Claude for thinking partner and automation. That’s the combination that already knew how I worked.

Cursor wasn’t a bad tool. It was the right tool for a moment that’s passed. The smarter move wasn’t finding something newer. It was recognizing what was already working and doubling down on it.

Notion remembers. Claude thinks and connects. That’s the pairing worth building on.

One more thing worth naming: things move fast in the AI space. What feels like a gap today may not be the stumbling block tomorrow. That’s not a reason to wait — it’s a reason to make decisions based on what’s working now, not what you’re hoping a new tool will eventually solve.

This is Part 1 of a short series on rebuilding the content workflow from the ground up. Getting the experiment documentation right — the soul of every article — was the foundation.

Next up: how the Article CEO workflow sits on top of it, and how the full pipeline runs from first spark to published piece.

One Thing You Can Try Today

Take five minutes and run this prompt against your current workflow:

“I use [tool/s] to do [specific job]. Given what I know about [the other tools I use daily], is this still the right fit — or am I working around it without realizing it?”

You’re not looking for a reason to switch anything. You’re just looking with fresh eyes. The answer might be: this still fits perfectly. That’s a useful thing to confirm too.

I’ve always been directionally challenged. Map reading stressed me out. My husband used to tease that I could follow step-by-step instructions and still end up lost.

So when I downloaded Waze for the first time, I knew it would be my game-changer. Plug in the destination, follow the instructions. Simple.

Except when traveling routes I kind of knew.

Because “How do I get there fastest?” isn’t the same question as “What’s the best way for how I want to travel?”

The thing is, following the optimal path always felt wrong. It took away my “what if” moments. What if we turn down this side street? What if we stop at that interesting store? What if we take this side road that cuts traffic because I’ve driven it a hundred times?

The GPS didn’t factor in the shortcuts I already knew. It just gave me the statistically efficient route. And following it felt hollow like something essential got left behind.

I didn’t realize I was about to experience the exact same tension in my work.

Last week, I activated Claude’s newest feature: Skills. Perfect on paper. But for what I actually needed to accomplish? It didn’t land. The prescribed approach felt like I was forcing something that wasn’t built for my specific context.

So I started asking questions, lots of questions.

Not because Skills was wrong. Because I needed to understand the who, what, and why of what it was suggesting.

That curiosity changed everything.

Optimal Features Aren’t Always Optimal

Here’s what most people think when they encounter optimization features: “The system knows what’s best. I should follow it exactly. Deviating means I’m doing it wrong.”

It’s a reasonable assumption. Optimization sounds scientific. Authoritative. Like, there’s one right answer baked into the algorithm.

But here’s what I discovered: optimization assumes the “best route” is universal. It’s not.

The best route depends on what you already know, what you’re willing to explore, and what you’re actually trying to accomplish. When you follow a prescribed path without asking, “Does this fit my actual situation?” you’re not being efficient. You’re operating with blinders.

Which means the smarter move isn’t to follow optimization—it’s to question it.

Here’s what this costs you if you don’t:

• You implement solutions that work on paper but feel misaligned with your actual workflow

• You spend time forcing “best practices” into systems they weren’t designed for

• You lose the strategic shortcuts you’ve already discovered through experience

• You mistake following instructions for progress

The GPS gives me the fastest route based on traffic data. It doesn’t know I’ve driven these roads for years, and there’s a neighborhood shortcut that saves five minutes and avoids an intersection I hate. It’s optimizing for speed. I’m optimizing for how I want to travel.

When I activated Claude’s Skills, the same pattern emerged. The framework was solid. But my project needed a “side road” the Skill hadn’t accounted for—a nuance that shifted everything.

I could have forced it. Most people do.

Instead, I asked the nagging questions. The ones that felt like they might slow me down but kept surfacing anyway.

Those questions didn’t derail the process. They refined it.

Working Fine Is Not Working Fine

When I first started using Claude, I approached it like a GPS. Here’s my destination, show me the optimal path, and I’ll follow it.

That worked fine for simple tasks: basic writing, quick research, and straightforward questions.

But when I started building more complex workflows—specifically, automating my content creation process—I ran into a wall.

I realized I was manually copying and pasting refined stories from Claude into Notion. Each piece: headline, refined story, components. All separated, all requiring me to bounce between apps.

It didn’t take hours. But it took energy. That momentum-killing friction of flipping screens, losing focus, copying from here, pasting there, back and forth.

So I thought: I’ll just build a Skill. That’s the whole point of Skills—automate these repetitive things.

I started building it. And immediately hit confusion.

My process wasn’t linear. I had multiple Notion databases working together. So my first real question was: “How does it know which database to put this in?”

That’s when I realized the Skill was optimizing for a generic workflow. But my workflow had layers. Context that the prescribed solution hadn’t accounted for.

I could have scrapped it. Could have said “This doesn’t work for me” and gone back to manual copy-paste.

Instead, I got curious about the question itself.

I asked Claude: Why are you suggesting this approach? ” What if I have different databases? What if I need the instructions to account for this specific context?

We started recalculating.

The first attempts didn’t work. One day it would function perfectly. Next day, nothing. I kept hitting walls and I kept going down the wrong roads.

Watch me walk through the exact moment I realized the prescribed Skills approach wasn’t built for my workflow, and how asking clarifying questions led me to embed automation directly into my Claude project instructions instead.

But then something shifted.

I stopped asking “How do I make this work?” and started asking “What’s the actual problem I’m trying to solve?”

The actual problem wasn’t “automate this workflow.” It was “eliminate the friction of bouncing between apps while keeping the flexibility of my specific process.”

That’s different.

So instead of building a standalone Skill, I went back to Claude with everything I knew about my actual process. I gave it the full picture: Here’s my database structure. Here’s what I need extracted. Here’s where it goes. Here’s the specific format I want. Here’s the friction point I’m trying to eliminate.

Then I asked Claude directly: “Based on my actual workflow, how should I build this automation into my project instructions? What’s the simplest, most reliable way to structure this so it works every time?”

That question changed everything.

Claude walked me through exactly how to embed the automation. Instead of me guessing at the right syntax or structure, Claude recommended the specific approach that would work for my situation. It showed me where the trigger point should be, how to format the extraction logic, and what the verification step should look like.

The moment I implemented Claude’s recommendation, everything clicked.

Now, when I finish refining a story, I paste the title. Hit enter. The system extracts every component, formats it exactly as I need, saves it to Notion, and gives me a verification link.

No more bouncing between apps. No more copy-paste friction. Just intention meets automation.

Tools That Actually Work

Why Following Prescribed Optimization Was Costing Me

I was spending a few minutes per piece manually transferring content between apps. Seems small. But across my workflow, it meant losing focus repeatedly, context-switching energy drain, and the friction that makes you less likely to refine stories in the first place.

Real consequence: I was avoiding the full process because the back-end felt tedious.

Here’s What Changed: Context-Specific Instructions Over Generic Solutions

Instead of building a universal Skill, I embedded the automation into my specific Claude project, providing detailed context for my actual workflow.

Here’s exactly how to adapt this for your situation:

Step 1: Map Your Actual Process (10 minutes)

Don’t describe what you think your process should be. Document what you actually do:

• What’s the starting trigger? (For me: refined story)

• What happens in between? (Extraction, formatting)

• What’s the endpoint? (Notion database)

• Where do you currently lose energy bouncing between tools?

Write this down. Be specific about friction points.

Step 2: Identify Your Clarifying Question (5 minutes)

There’s usually one detail that shifts everything. For me, it was the multiple databases that were part of the process.

Ask yourself: What’s the one piece of information that would make this system know what to do without me explaining it every time?

That’s your clarifying question. Build it into your process.

Step 3: Give Claude Your Full Context (10 minutes)

Instead of: “Automate this”

Say: “Here’s my current process: [detail]. Here’s the friction point: [specific problem]. Here’s what I need the output to look like: [exact format]. Here’s my clarifying question: [the detail that triggers everything].”

Step 4: Let Claude Recommend How to Build It (5 minutes)

Paste this into Claude:

I need to automate this workflow into my Claude project instructions. Here’s the full context:

[Your process map from Step 1] [Your friction point] [Your desired output] [Your clarifying question] [Your destination system]

Based on my actual workflow, how should I structure this automation in my project instructions? What’s the most reliable way to embed this so it works consistently? Show me the specific approach you’d recommend.

Claude will recommend the exact structure that fits your situation. Not a generic template. The actual approach that works for your specific workflow.

The Result

You stop guessing at how to build automation. You let Claude analyze your specific situation and recommend the approach that actually works for you.

Most people either try to force generic solutions or spend weeks building custom ones. This 30-minute process saves you that friction by letting Claude recommend the right approach upfront.

SECTION 5: CLIENT REALITY CHECK (290 words)

When clients come to me frustrated with Claude or other AI tools, the conversation usually goes like this:

Them: “This feature is supposed to save me time, but I hate it. Everything feels off.”

Me: “That’s not a flaw in the tool. That’s your gut telling you it wasn’t built for your specific situation.”

Them: [Long pause] “So I’m not doing it wrong?”

Me: “No. You need to define the process to your needs and match the tool to it.”

That pause is everything.

Most prescribed solutions optimize for efficiency in general. They don’t account for the specific context that makes your workflow yours.

One client was using a template-based content system that technically worked—it saved time. But she hated using it. Everything felt generic. The output was fast but hollow.

When I asked her, “What would make this feel like your voice instead of the system’s voice?” she realized the template was stripping out the personality. The specific details that made her advice different from everyone else’s.

We didn’t need a better template. We needed instructions that preserved her specificity while automating the busywork.

Here’s the universal principle:

Permission to explore and question isn’t inefficiency. It’s strategic refinement.

When something feels off, it usually means the prescribed path doesn’t match your actual situation. That’s not a weakness. That’s strategic awareness.

The businesses I see winning aren’t the ones that blindly follow the suggestions. They’re the ones who ask: “Does this work for how I actually operate? If not, what needs to change?”

That questioning isn’t slow. It’s what makes automation actually work.

Most people try to force the generic solution first. Then they give up when it doesn’t fit. What works is asking the clarifying questions early—the ones that feel like they might complicate things but actually make everything simpler.

Your caution about following a prescribed path? That’s not overthinking.

That’s exactly the strategic thinking that separates working automation from frustrating solutions.

The Smarter Strategic Approach

The Old Way: Activate a feature or framework, hope it fits your specific situation, force it when it doesn’t.

The Smarter Way: Use Claude to map your actual workflow, identify friction points, and build instructions that account for your specific context.

Here’s exactly how:

Step 1: Audit Your Current Process (10 minutes)

In your Claude project or thread, paste this:

I’m trying to automate [specific task]. Right now, here’s how I do it manually:

1. [Starting point]
2. [Middle steps]
3. [End point]

The part that takes the most energy is: [specific friction point]

What I need the output to look like: [exact format/destination]

Step 2: Ask Claude to Identify Your Clarifying Question (5 minutes)

What’s the single piece of information I could provide that would tell the system how to route/handle this automatically? What’s my “story title” moment—the trigger that makes everything else clear?

Claude will help you surface this. It’s often simpler than you think.

Step 3: Build Your Instructions (10 minutes)

Instead of relying on a pre-built feature, embed this directly into your Claude project instructions:

When the user provides [clarifying question], follow this sequence:

• Extract [these components]

• Format as [specific format]

• Route to [specific location]

• Return [verification link/confirmation]

Step 4: Test With One Real Example (5 minutes)

Don’t build the whole system first. Test it with one actual piece of work.

Use your clarifying question trigger. See if it works. Adjust if needed.

The Result

You stop trying to force generic solutions into specific situations. You build automation that actually matches how you work—not how you think you should work.

Most people waste weeks trying to make prescribed frameworks fit. This 30-minute process removes that friction by starting with your reality, not an idealized version.

Permission To Explore

Permission to explore isn’t inefficiency. It’s strategic curiosity.

It’s knowing when to follow the prescribed path and when to trust that the questions surfacing—the ones that feel like they might slow you down—are actually pointing toward something more refined.

The GPS still gets me where I need to go. But I don’t always follow it exactly. That’s not stubbornness. That’s strategy.

The same applies to AI tools, frameworks, and features. The ones that work aren’t the ones you follow blindly. They’re the ones you questioned enough to make fit your actual situation.

This entire process—from realizing prescribed optimization doesn’t fit, to building context-specific instructions that actually work—is exactly what I’m building into the SHIFT Your Context Workshop. It’s designed to help you create the documents and context that make AI work smarter for you because the gap between needing help and getting the right-sized help is smaller than you think.

That new AI tool won’t transform your business overnight. Here’s why the implementation journey matters more than the destination—and how to actually make your existing tools work.

When the View Isn’t What You Expected

On a trip to the Smoky Mountains, my husband and I decided to visit Grotto Falls—the only waterfall in the Gatlinburg area where you can walk behind the curtain of water.

Sounded magical, right?

We parked, found the trailhead, and I saw the sign: 1.4 miles, moderate trail. Easy enough, I thought. What I failed to register was the part about it being 1.4 miles up a mountain. Straight up.

Let’s just say “moderate” is doing a lot of work on that sign.

We’re at that stage of life where ‘moderate’ trail signs require scrutiny, and this hike wasn’t giving us the full story. But we were already headed up, so up we went—huffing, laughing, and lightly complaining the entire way.

We stopped to chat with folks coming down, each one assuring us, “It’s so worth it when you get to the top.”

So we kept climbing.

And sure enough, Grotto Falls was beautiful. We stood behind the water, cool mist on our faces, and took it all in. But here’s the truth: we’re from Pennsylvania—where many waterfalls are practically in the backyard—and for us, it just didn’t feel that extraordinary.

We weren’t disappointed exactly, just... aware.

The Real Problem: We’re Climbing for the Wrong Destination

Here’s what I realized on that hike: I was climbing for the waterfall.

But the waterfall wasn’t the point.

The climb was the point. The conversation. The stops to catch our breath and laugh at ourselves. The way we figured out our rhythm—when to push, when to pause, when to just acknowledge that this was harder than we expected.

“The software, the systems, the AI—they’re the waterfall. Beautiful, yes, but not the whole experience.”

This is the exact trap I see solopreneurs falling into with technology. We invest in new tools expecting the view from the top to instantly change everything. We buy the course, sign up for the platform, implement the automation... and then wait for the transformation.

But here’s the thing: the tool is the destination, not the transformation.

The transformation happens during the climb—the messy implementation, the learning curve, the trial and error of figuring out what actually works for your business, not someone else’s.

Most people are solving the wrong problem. They think they need better tools when what they actually need is a better relationship with the tools they already have.

What I Learned the Hard Way About Tools and Expectations

On the way down from Grotto Falls, we met a couple from Florida.

With the same hopeful-but-uncertain look we’d had on the way up, they asked, “Is it worth it?”

We said, “Well, it’s pretty.”

They looked thrilled anyway.

That’s when it hit me: value is about context.

For them, a waterfall hidden in the mountains was rare magic. For us, it was familiar beauty. The difference wasn’t the waterfall—it was the expectation we brought to it.

I’ve been doing the same thing with my tech stack for months.

I kept thinking I needed:

• A better system for organizing my business knowledge

• More sophisticated automation

• The latest AI tool everyone’s talking about

• Another platform to “streamline” my process

What I actually needed was to stop climbing toward new waterfalls and start appreciating the one I was already standing behind.

The turning point came when I stopped asking, “What new tool do I need?” and started asking, “What am I not using that I already have?”

Turns out, I already had everything I needed:

• ChatGPT for content processing and refinement

• Google Docs for accessible document storage

• A system I’d designed but never fully committed to

• Workflows I’d mapped but kept abandoning for shinier options

The problem wasn’t my tools. The problem was my relationship with the climb.

.Watch me walk through the specific tools I use daily and how I’ve learned to resist shiny object syndrome while building systems that actually stick.

Here’s what changed once I stopped tool-hopping and started tool-mastering.

The Shift: From New Tools to New Habits

I made one rule: no new tools until I’ve maxed out what I already have.

That meant finally committing to:

• ChatGPT for thinking through ideas and refining content

• Google Docs for building reusable context I can access anywhere

• Notion for tracking what actually matters

Nothing fancy. Nothing new. Just consistent use of what was already sitting in my toolkit.

The Context Library Workshop

The biggest change came from building a library of reusable business documents instead of starting from scratch every time. I’m not talking about templates or some complex system. Just core documents that capture what I do, how I do it, and why - so I stop reinventing my own business knowledge every week.

The magic isn’t in the sophistication. It’s in having context that works for me instead of against me.

What This Actually Looks Like

Instead of hopping between tools looking for the “perfect” system, I built a simple practice:

• Capture ideas when they’re fresh

• Use AI to help refine the messy parts

• Keep everything accessible and reusable

• Refine as I grow

another AI strategist working with creators wrote something in her Substack that hit home: we don’t need “endless lists of random tools” - we need to actually use what we have. She’s seeing the same pattern I am.

Why This Pattern Matters More Than Ever

Here’s the broader truth about technology adoption in small businesses:

Most tools fail not because they’re bad, but because we treat them like destinations instead of practice.

According to research from McKinsey, 70% of digital transformation efforts fail—not due to bad technology, but due to resistance to change and lack of sustained implementation. The tool works. The commitment doesn’t.

This applies to:

• AI integration (buying access isn’t the same as learning to use it)

• Automation platforms (setting them up isn’t the same as optimizing them)

• Content systems (creating the structure isn’t the same as following it)

• Document libraries (building them isn’t the same as actually using them)

The pattern is always the same: we climb toward the waterfall, arrive, take a photo, and then wonder why our business didn’t transform.

Think about it this way. When that Florida couple reached Grotto Falls, they weren’t just seeing water cascade over rocks. They were experiencing the payoff of their own climb—every step, every breath, every choice to keep going despite uncertainty about what they’d find at the top.

That’s the difference between tool ownership and tool mastery.

What You Can Try This Week

Here’s your 15-minute experiment in climbing instead of destination-hopping:

The One-Tool Audit

1. Pick ONE tool you already pay for but underutilize

2. Set a 10-minute timer

3. Open the tool and ask: “What’s one thing I could do right now that would make tomorrow easier?”

4. Do that one thing (not three things, ONE)

5. Write down what you notice about the process

What to pay attention to:

• Where do you get stuck? (That’s where you need practice, not a new tool)

• What feels easier than expected? (That’s what you should double down on)

• What makes you want to quit and try something else? (That’s your shiny object syndrome alarm)

The goal isn’t to master the tool in 15 minutes. The goal is to practice the climb—the uncomfortable, unglamorous work of actually using what you have.

The Climb Is the Transformation

So here’s what actually happened.

I spent months testing every new AI app that showed up in my inbox. Daily announcements. Shiny demos. “Game-changing” features. And sure, it was fun to play around - like hiking to a new waterfall every weekend.

But when I looked at what actually moved my business forward? My tried-and-true tools did the job just fine. Often better.

The problem was never the tools. It was me treating each new one like it would finally be the one that made everything click.

Remember that couple from Florida? They weren’t adventure-shopping for a better waterfall. They were just going to climb the one in front of them.

Your tech stack works the same way.

That’s what I’d forgotten.

The transformation doesn’t come from finding the perfect tool. It comes from committing to the climb with the ones you already have.

What tool are you already paying for that deserves more of your attention than a new one?

The waterfall can wait. The climb is where the real work happens.

Want to see how I’m actually using AI tools without the hype? Check out my YouTube breakdown where I walk through my daily AI workflow—no fluff, just the systems I actually use to build content and manage my business without burning out.

And next week? I’m announcing the Context Library Workshop - the system that finally gave me something to climb toward instead of just more tools to collect. Stay tuned.

Seventeen years ago, I began my career as a virtual assistant.

Back then, that role was the rising trend in online business—a way to meet the needs of entrepreneurs trying to make digital work for them. But as my skills and the market evolved, I leaned into coding, stepping into web development and support long before drag-and-drop websites made things simple.

Eventually, I landed on WordPress and built my agency.

The sweet spot where customization and usability meet.

That willingness to pivot wasn’t about chasing fads. It was about meeting the intersection of my strengths, the tools available, and what my clients needed most. Each shift was less a leap and more a compass point, directing me toward the next chapter.

Recently, I launched the DigiNav Compass™ to help others find that same “next best move.” Tech keeps reshaping how we work and live, but the question isn’t “What’s the newest thing?”

It’s “What actually works for you, and where are you headed?”

Here’s what I’ve learned the hard way: technology shifts aren’t about chasing the newest thing—they’re about context fit.

The Real Problem With “Shiny Object Syndrome”

Here’s what I realized was actually happening when people asked if I’m abandoning WordPress now that AI and vibe coding are emerging.

The question itself reveals the deeper issue.

We’ve been conditioned to think that new automatically means better, and staying put means falling behind. But that’s not how sustainable businesses work.

“The real problem isn’t that people are slow to adopt new technology. It’s that they’re making adoption decisions based on fear instead of fit.”

When people approach tech decisions from anxiety, they end up with these issues:

• Digital Swiss Army knives — tools that do everything but excel at nothing

• Patchwork workflows — half-integrated solutions that create friction

• Decision paralysis — too many options, no clear framework for choosing

• Constant rebuilding — starting over every six months with new tools

Their workflows become a collection of solutions searching for problems instead of tools serving specific needs.

The same pattern shows up everywhere. ChatGPT Projects vs Custom GPTs. WordPress vs AI builders. Email platforms vs all-in-one solutions.

We’re asking “which is better?” instead of “which fits my actual workflow?”

From Trend Follower to Strategic Adopter

I considered abandoning WordPress for a moment when AI coding tools emerged, but WordPress continues to serve me and my clients well.

That pause made me realize something crucial.

I had already developed an unconscious framework for tech decisions. I just hadn’t articulated it yet.

Here’s my actual decision-making process:

I grew up analog. Even with the internet, smartphones, and constant connectivity, there are days I crave the simplicity of a landline.

Nostalgia aside, it’s grounding.

“Just because something new arrives, the old isn’t automatically obsolete. Sometimes it just needs an update, a tweak, or a new role.”

That’s why I created the DigiNav SHIFT System™. It’s about adjusting, not abandoning.

AI is now part of my toolkit — not as a replacement, but as a way to adapt to what’s ahead, because technology will continue to evolve.

The key is choosing what supports your work, your clients, and your lifestyle without losing the roots that still hold value.

What I tried first: Jumping on every new AI tool that promised to revolutionize my workflow. I spent more time learning new interfaces than actually working.

The mindset shift that changed everything: Realizing I needed a filter, not more options. I started asking, “Does this organize my work or automate my work?” instead of “Is this the latest thing?”

My breakthrough moment: Understanding that ChatGPT Projects and Custom GPTs serve completely different purposes. Projects are like digital filing cabinets for ongoing work. Custom GPTs are like specialized tools you build once and reuse.

Specific results: Instead of trying 15 different AI configurations, I now use Projects for client work organization and Custom GPTs for repeatable tasks. My decision time went from weeks to minutes.

Tools That Actually Cut Through the Noise

Here’s the exact framework I use before adopting any new technology:

The Two-Question Test:

1. Does it save time? Not just promise to save time — actually demonstrate time savings in a real scenario

2. Does it fit my workflow? Can I integrate it without rebuilding everything else I do

According to a recent study by McKinsey, 87% of businesses struggle with tool proliferation, which explains why this simple filter matters more than ever.

Here’s the exact decision matrix I use for AI tools:

ChatGPT Projects vs Custom GPTs:
- Exploring questions or keeping research organized? → Projects
- Need repeatable, consistent answers? → Custom GPTs
- Working with clients on ongoing projects? → Projects
- Building tools others will use? → Custom GPTs

Watch me walk through real examples of when to use Projects for organization versus when to build Custom GPTs for automation

For your situation, try this variation:

Before choosing between similar tools, map your actual use case:

• If you’re still exploring and need conversation history → Choose the organizing tool

• If you have a repeatable process that needs consistency → Choose the automation tool

• If you need to collaborate or share context → Choose the tool that handles external access better

The tool categories that actually matter:

• Organizing tools: Projects, Notion databases, file systems — for when you’re still figuring things out

• Automation tools: Custom GPTs, Zapier workflows, templates — for when you know exactly what you need

• Integration tools: APIs, connectors, webhooks — for when you need tools to talk to each other

The breakthrough that changed my client work:

Instead of debating which AI tool is “better,” I started asking clients: “Are you organizing information to make decisions, or are you automating decisions you’ve already made?”

Organizing needs: Use Projects with uploaded context documents and memory settings

Automating needs: Build Custom GPTs with specific instructions and knowledge bases

This clarity eliminated the decision fatigue that comes with having too many similar options.

Why Context Beats Trend-Chasing Every Time

This isn’t just about WordPress versus new coding tools or projects versus custom GPTs.

It’s about sustainable decision-making in a world where the next big thing arrives weekly.

The people building the most resilient businesses aren’t the early adopters or the late adopters. They’re the strategic adopters — people who evaluate tools based on context, not hype.

Consider this supporting example:
Basecamp still uses its own custom-built project management tool, rather than switching to newer alternatives. Not because they’re stuck in the past, but because it serves their specific workflow better than any other available option.

This same approach applies to:

• Hiring decisions — do you need a specialist or generalist?
• Partnership choices — do you need access to their network or their expertise?
• Business model pivots — are you solving a new problem or solving an old problem better?
• Content strategy changes — are you reaching new people or serving existing people better?
• Client onboarding processes — do you need more personal touch or more efficiency?

Every successful business you admire probably uses a mix of cutting-edge and “outdated” tools. They’re focused on what works for their specific situation right now.

What You Can Try Today

One specific, 30-minute experiment:

1. Pick one tool decision you’ve been debating (AI-related or otherwise)

2. Instead of researching features, spend 30 minutes mapping your actual workflow

3. Ask these specific questions:

   • Am I organizing information or automating processes?

   • Do I need conversation history or consistent outputs?

   • Will I use this weekly or just when I remember it exists?

   • Does this replace something I already use, or add a new step?

4. Test with the simplest option first — regular ChatGPT before Custom GPTs, basic tools before all-in-one platforms.

Notice whether your energy goes toward learning the tool or solving your actual problem.

After 30 minutes, apply the two-question test. If it saves time and fits your workflow, schedule time to implement properly.

If it fails either question, move on without guilt.

The Real Shift That Matters

When people ask if I’m abandoning the tools that built my business, I think about that landline analogy.

Sometimes the most strategic move isn’t adopting the newest technology.

It’s being intentional about what you keep, what you adapt, and what you actually need to replace.

The shift from trend-chasing to strategic adoption changed everything for me. Instead of constantly learning new tools, I got better at the ones I already had.

Instead of rebuilding my systems every six months, I refined them.

What’s your current approach to new technology? Are you choosing tools based on what everyone else is doing, or are you choosing tools based on what actually moves your work forward?

Ready to build your strategic foundation? I’m launching a workshop on creating your personal context library — the decision-making foundation that helps you evaluate tools, partnerships, and business direction based on what actually fits your situation. Keep an eye out for the

What seems like many moons ago, I was offered a forced resignation, which I gladly accepted.

Was it on my terms and timeline? No.

Was it a blessing in disguise? You betcha.

For a good six months, I thought about leaving the company, but the salary was amazing and the schedule worked for me. Add to that, I’d built a dream team and hit every productivity mark.

The golden handcuffs were firmly in place.

Why it happened is a story for another day, but after the fact—when I had time to reflect—it was the universe talking to me.

I was overworked. Not as professionally driven. And my family needed me.

All the signs were there, but I was too comfortable (and too scared) to make the move myself.

“Here’s the thing about being pushed into change: it strips away all the comfortable lies we tell ourselves and forces us to see what actually matters.”

When Job Offers Flood In: How to Evaluate Opportunities Without Losing Yourself

In a highly competitive industry, I was one of the few without a no-compete clause. I could go anywhere and demand the world.

And the offers came in when word got out.

I was the needle in the haystack.

Every recruiter call felt like validation. Every offer felt like proof that I was valuable. For someone who’d just been pushed out of their comfort zone, this felt like the universe saying, “See? You’re going to be just fine.”

But then my better half reminded me of two things:

• I was stressed by the schedule and workload

• I would need to share secrets that most no-competes cover

Which was the deciding factor to pass on them all.

Here’s what I realized was actually happening: I wasn’t evaluating opportunities—I was reacting to them.

The real problem wasn’t finding the next job. It was figuring out what kind of work life I actually wanted to build.

Most people think the hard part about career transitions is finding opportunities.

It’s not. It’s knowing which ones to say no to.

The Integrity Test That Changed My Career Path Forever

Not because the workload would be heavy or the schedule wouldn’t fit.

Because integrity was the one thing that allowed me to soar at that company, and I was never going to compromise that.

This wasn’t just about non-compete clauses or trade secrets. This was about recognizing that my competitive advantage wasn’t what I knew—it was how I operated.

My integrity had been my differentiator all along.

What I’ve learned the hard way is that when you’re pushed into a corner, you discover what your actual boundaries are. Not the ones you think you have, but the ones you’ll actually defend when it matters.

I started with one simple experiment:

I wrote down what I would and wouldn’t do, regardless of the money offered.

The “wouldn’t do” list was shorter than I expected, but it was crystal clear. Any opportunity that asked me to cross those lines got an immediate no.

What worked was treating my values like a filter, not a suggestion.

What surprised me was how much easier decisions became once I knew where I wouldn’t bend. Instead of agonizing over every offer, I had a clear framework for evaluation.

“My next move became obvious: I was going to build something of my own, on terms that aligned with those non-negotiables.”

The forced resignation hadn’t just pushed me out of a job—it had pushed me toward clarity about what kind of business I wanted to build.

Decision-Making Framework: Build Your Personal Values Filter

Here’s the framework I developed from that experience, and what I now teach to avoid saying yes to opportunities that drain you:

The This or That Values Matrix: Start with trade-offs that show up often in your work. Create two columns and choose what feels more aligned with your current season:

• Deep engagement vs. Big audience

• Flexibility vs. Structure

• Privacy vs. Visibility

• Fast results vs. Sustainable growth

• High pay vs. Meaningful work

• Autonomy vs. Team collaboration

The Integrity Boundary Check: Before evaluating any opportunity, write down your non-negotiables. Not what you prefer, but what you absolutely won’t compromise on.

For me, it was integrity in how I handled confidential information.

For you, it might be:

• Family time boundaries

• Creative control requirements

• Financial transparency standards

• Work-life balance minimums

The Stress Test Question: Ask yourself: “If I took this path, what would I need to do that would make me lose respect for myself?”

This isn’t about being dramatic—it’s about being honest. The answer will tell you more about fit than any pro/con list.

The 10-Year Vision Filter: This is where I use a ChatGPT Project to build and refine my long-term vision over time. You can continuously add decisions, outcomes, and reflections to see patterns in what actually aligns with your bigger picture.

For one-time decision clarity, I created the Clara Decision Filter custom GPT that cuts through all the short-term pressure and gets to what actually matters. You can access it here: Clara Decision Filter.

According to a recent Harvard Business Review study, 67% of professionals report feeling overwhelmed by career decisions because they lack clear decision-making frameworks. This systematic approach helps cut through that overwhelm.

Build Your Personal Decision Filter in 15 Minutes

Watch me walk through the exact “this or that” matrix process I use to avoid saying yes to opportunities that drain me. You’ll get the ChatGPT prompts and Notion setup to create your own values-based decision system

Copy-Paste ChatGPT Prompt for Decision Questions:

I’m creating a set of tailored questions to help me make better decisions in my business that align with my needs. I started with a this or that matrix that reflects my preferences. Let’s talk about it.

[Paste your matrix choices and reflection notes here]

I prefer pinpointed reflective questions and would like you to factor in your findings, my matrix, and my core values to craft five key questions I can use when I need clarity on a decision.

Why Career Pressure Creates Better Decision-Making

This isn’t just about career transitions—it’s about recognizing that being pushed often reveals our clearest thinking.

We live in a world that celebrates the quick yes and the hustle mentality. However, the most successful builders I know have gotten really good at saying no to good opportunities so they can say yes to great ones.

The pattern is this: External pressure forces internal clarity.

When you’re comfortable, you can afford to be wishy-washy about your values. When you’re pushed, you find out what you actually stand for.

Here’s what I see happening with the entrepreneurs and creators I work with:

• They get stuck not because they lack opportunities

• But because they lack a clear framework for choosing between them

• They’re evaluating everything on individual merits

• Instead of filtering through their actual priorities

This same values-based filtering works for:

• Partnership decisions (like the partnership that drained me in two weeks)

• Client boundary setting

• Business opportunity evaluation

• Investment choices

“The most successful people aren’t the ones who say yes to everything—they’re the ones who know what to say no to.”

15-Minute Exercise: Find Your Decision-Making Framework

Pick one decision you’re currently wrestling with—could be a client opportunity, a partnership offer, or even a personal commitment.

Instead of making a pros and cons list, try this approach:

Step 1: Create your “this or that” matrix with 5-6 trade-offs relevant to this decision.

Step 2: Choose the option that feels more aligned with your current season (not what sounds good, but what feels right).

Step 3: Write down what these choices say about how you want to work.

Step 4: Use the ChatGPT prompt above to generate 5 core decision questions.

Step 5: Apply those questions to your current decision.

The goal isn’t to make the decision right now—it’s to build a system you can use repeatedly.

When Life Forces Clarity: Your Next Move

Looking back on that forced resignation, I realize it wasn’t just about leaving one job and finding another.

It was about being pushed into a moment of truth about what I actually valued and how I wanted to operate in the world.

The opportunities I turned down led to the business I built instead.

The integrity filter I developed in that moment of pressure became the foundation for every major decision I have made since then.

Here’s what I’m curious about: What decisions are you avoiding right now because you haven’t gotten clear on your own non-negotiables?

Sometimes, the best thing that can happen is life pushing you to find out.

Ready to build your own decision filter? The video above walks you through the complete system, and you can get the Clara Decision Filter custom GPT plus more frameworks like this at diginavcompass.news.

We’re building a space for you to experiment with these tools yourself, including creating a set of Context Library docs and a Story Refining system.

Because sometimes the best thinking partner isn’t human—it’s a well-designed system that helps you pause before you say yes to something that might not fit.

As someone who devours books, this felt like failure. Until I started flipping through them and realized something. The ones gathering dust weren't the problem. I was.

That highly recommended marketing book everyone said was "essential"? Outdated advice that had nothing to do with where my business was heading, wrapped in case studies from companies I'd never heard of, teaching strategies that felt like they belonged in 2015. The productivity guide that was supposed to revolutionize my workflow? I'd forced myself through 200 pages of rehashed time management tips I'd heard a dozen times before.

But here's what I noticed. The books I actually finished? I ripped through them in days, filling the margins with notes and walking away with a list of things to try immediately. The struggle-through books left me frustrated and uninspired. Like homework.

Maybe the problem wasn't my attention span.

Perhaps the problem was that I thought I had to finish everything just because I had started it.

Why Business Education Overwhelm Hurts Your Progress

We're drowning in business education. Courses. Podcasts. Books. Newsletters. Masterclasses. The message is everywhere: consume more, learn more, do more.

But here's what nobody talks about. Most of that content isn't meant for you. Not right now, anyway.

There's a notion that the more you consume, the more successful you'll become, as if knowledge accumulates like interest in a savings account and eventually reaches a magical tipping point where everything falls into place.

I've watched people collect courses like baseball cards, yet they still struggle with the same problems they had two years ago.

What if we flipped the script entirely?

I recently came across Pat Flynn's new book Lean Learning, and it made me realize I'd felt the same way about challenging everything we've been told about business education.

What if instead of learning everything about something, we learned just enough to take action? What if we stopped when we had what we needed instead of continuing until we were overwhelmed?

This approach has four simple steps:

1. Choose your next goal

2. Learn only what's essential

3. Take action

4. Reflect and repeat

Notice what's missing? The part where you consume everything available on the topic. The part where you research until you're paralyzed.

How to Focus on Essential Business Knowledge

How many times have you signed up for a course, bought a book, or started a training program only to realize halfway through that it wasn't what you needed?

I used to power through anyway. Because quitting felt like giving up.

But there's a difference between giving up and being strategic.

Sometimes, the most valuable thing you can extract from a 300-page book is one framework from chapter three. Othertimes, a $500 course teaches you exactly what you need in the first module. The rest? Filler.

Here's what I've started doing instead.

I browse for the timeless tips and information I can apply right now, regardless of where I am in my business journey. If a book isn't giving me inspiration or actionable insights within the first few chapters, I extract what's useful and move on.

No guilt. No forcing myself through irrelevant content just because someone else found it valuable.

It’s like drinking a glass of sour milk just because the glass was full.

Yet somehow, when it comes to business education, we torture ourselves through content that isn't serving us. We guilt ourselves into finishing courses that aren't relevant to our current stage. We push through books that feel like slogging through mud because someone on LinkedIn said it was a "must-read."

Why Action-Based Learning Gets Better Results

The traditional learning model goes like this: Study everything, then maybe do something.

Let’s rework that thinking. Learn just enough to take one meaningful action, then learn more based on what happens.

This isn't about being lazy or cutting corners.

It's about recognizing that real learning happens when you're doing, not when you're consuming. When you're getting feedback from real people about real results instead of theoretical knowledge about hypothetical situations.

I think about a client who spent six months researching email marketing platforms before sending a single email. She could tell you the features of every tool, the pros and cons of each pricing tier, and the technical specifications that didn't matter for her 100-person list. But she hadn't actually written an email. Or built a sequence. Or learned what her subscribers wanted to hear about.

What if she'd learned just enough to pick one platform and send one email?

What if she'd figured out what she actually needed by doing, instead of by researching?

She would have discovered that her subscribers were more interested in behind-the-scenes content than industry tips. She would have learned that her best open rates came from Tuesday sends, not the Wednesday schedule all the experts recommended. She would have found her voice by writing, not by studying other people's successful campaigns.

Action teaches you things research never will.

Why This Feels So Hard

People think that once you pick up a book, you need to struggle through and finish it. Same with courses. Same with offers. Anything.

There is a work ethic ingrained in business education that suggests struggle equals value. If it's not hard, it's not worth doing. If you didn't suffer through all 400 pages, you didn't really learn anything.

But here's what I've learned. The books that feel like work usually aren't teaching you anything. The courses that feel like slogging through mud aren't moving you forward. The content that leaves you frustrated and uninspired isn't helping you build anything.

The stuff that's actually useful? You can't put it down. You finish it quickly because it's speaking directly to what you need right now. Because it's solving a problem you actually have instead of a problem someone thinks you should have.

What This Looks Like in Practice

Since adopting this approach, my learning has become more focused and targeted. I pick a specific challenge I'm facing - let's say improving client retention. I don't read three books about customer success and take two courses on relationship building.

I find one resource that addresses my specific situation. I extract what I need. I try it. I see what happens.

If it works, great. If it doesn't, I learned something valuable about what doesn't work for my situation. Either way, I'm moving forward instead of staying stuck in preparation mode.

This doesn't mean I've stopped learning. I probably learn more now than I did when I was trying to consume everything. But I learn something specific, not just to accumulate knowledge.

The Real Rebellion

In a world that profits from keeping you perpetually learning, choosing to learn less is actually radical.

The course creators want you to believe you need their entire system, from foundation to advanced strategies, even if you only need help with one specific challenge.

The productivity gurus want you to think you need to optimize everything, from your morning routine to your email signature, when maybe you just need to stop checking Instagram during work hours.

Business books want you to believe that more information equals more success, that somewhere in those 300 pages lies the secret that will transform everything.

But what if the opposite is true?

What if learning less, but applying more, is actually the path to better results? What if the people who are getting ahead aren't the ones consuming the most content, but rather the ones who know when they have enough to move forward?

This approach isn't just about efficiency.

It's about recognizing that your time and attention are finite resources. Every hour you spend consuming content that isn't directly applicable to your current challenge is an hour you're not spending building something real. Testing something. Learning from actual experience instead of someone else's theory.

Your Turn

So here's what I'm curious about: What's one thing you're over-learning right now?

What course are you halfway through that isn't giving you what you need? What book are you forcing yourself to finish even though it lost you three chapters ago? What area of your business are you researching instead of testing?

Maybe it's time to close the book. Mine what's useful. Move to action.

The rest will be there when you actually need it.

Want to organize your learning around what actually matters? I've created a Learning Central Notion board—a free template that helps you track only the essential knowledge you need for your current goals. It's a small part of the Digital Navigator HQ resources I share with my community. Get your copy here and start learning less, but applying more.

Each was promising to improve my workflow. Write my articles while I slept. Generate social posts that would attract new readers. Transform my scattered thoughts into cohesive content.

The only problem? My best-performing articles come from the messy, unscalable stuff—the random thoughts I try to get out of my head.

Each promised magic. Faster output. Smarter results. All the bells and whistles.

I spent three hours reading reviews, watching demos, and comparing features designed to streamline my entire writing process. My brain buzzed with possibility. My excitement built with every feature I discovered. What if one of these gave me an added edge?

Something in me hesitated. I looked at the kind of work I actually create—messy first drafts, ideas sparked by so many before me, voice memos taken while riding or doing cardio.

None of those things is scalable. Or templated. Or could be done without my input.

I emptied my cart and moved on.

The Lies We Tell Ourselves

You’ve probably heard some version of this advice: “Good business owners stay plugged in”. They listen to popular podcasts, follow industry leaders, and invest in tools that give them a competitive edge.

It sounds so responsible. And smart.

But in practice? It creates chaos under everything. A sense that you’re always behind, no matter how much you consume or try to catch up.

Building unrealistic steps for the conversion funnel. Signing up for the “best” time-saving productivity system. Bookmarking the YouTube influencers who are crushing it.

Before long, your instincts get buried under a pile of other people's methods.

It’s the kind of pressure that doesn’t just drain your energy—it hijacks your instincts. Instead of feeling focused, you feel reactive. Scattered. Scrambling to keep pace with a game no one seems to be winning.

The most dangerous business advice I ever followed was "always be learning." Because constant learning became my excuse to avoid doing the actual work that I already knew how to do.

The Day I Realized I Was Sabotaging Myself

Ten years ago, I joined a beta program for a project management tool that promised to “revolutionize how solo business owners organize their workflows.”

Why? Because someone with 350K followers called it a "game-changer," and well, with that many followers, they must know something.

I spent a weekend setting it up. Created sections for my three main projects. Color-coded my tasks. Built automated workflows that would trigger when I moved items from one status to the next.

It was beautiful. Sophisticated.

There was just one problem: I had two leads in the pipeline and one project underway. I could have tracked them on a spreadsheet.

Instead of spending that time following up with those two leads or finding more projects, I was working on improving someone else's system and product.

That's when it hit me. I wasn't solving my business problem. I was procrastinating on the real work—the conversations, the proposals, the uncomfortable follow-ups that actually grow a business.

I dropped out on Monday.

The Filter Test That Changed Everything

Now I use what I call the "In-the-Weeds Check” for every new tool, system, or strategy that is on my radar.

It’s simple: Would I reach for this on a random Monday when I’m just trying to get work done?

Not when I’m feeling motivated and in the zone. Not when I’m inspired by someone else who’s crushing it. Just a regular old Monday morning when I have a week of deadlines to meet and clients to help.

If the answer is no, out it goes.

The test has saved me from:

• A client onboarding system with 15 steps that would completely overwhelm my clients (who want to pay me and get started)

• A content calendar that plans and schedules six months ahead (my best stuff comes from the results of things I did last week)

• A $99/month membership with a 50-lesson course and as many different templates (who has time to sort through those templates after that course)

What I Do Instead of Chasing The Trends

Here’s what I live by now:

1. Does this simplify or complicate? If I need an in-depth tutorial to understand it, it's probably more complex than my actual problem requires.

2. Will I still use this in three months? Most tools get abandoned when the initial motivation wears off. I look at what I have and how I can make it work better.

3. Does it fit how I naturally work? I'm all for a good system and strategic thinking, but I know the difference between tools that support my planning and tools that become projects themselves.

4. Am I solving a real problem or avoiding real work? Sometimes the tool isn't the issue. Sometimes I just don't want to have the difficult conversation or face the uncomfortable decision.

If something doesn't pass all four questions, it doesn't belong in my business.

The Unexpected Impact

Here's what happened when I stopped trying to keep up with every new strategy and started trusting my instincts:

Business Decisions: I stopped second-guessing my approach based on what others were doing and started leaning into my strengths.

Client Relationships: Without the distraction of constantly tweaking my systems, I could focus on delivering results that mattered.

Personal Wellbeing: I wasn't constantly learning new methods. I was getting better at the methods I'd already chosen, and my energy soared.

The truth? Limiting inputs increased my momentum. When I stopped consuming every piece of business information, I started trusting my judgment again.

Overcoming Resistance to Change

The hardest part? Letting go of the idea that more input equals smarter action.

Conventional wisdom suggests that the more informed you are, the better your decisions will be.

But information overload isn’t clarity. It’s paralysis dressed up as productivity.

Your Filter Practice Starts Here

Look at your bookmarks folder. Your list of subscriptions. The apps on your phone.

How many of these tools would pass the In-the-Weeds Check?

Which ones are you keeping "just in case" but never actually use?

What are you learning about that you're never going to implement?

Your instincts aren't wrong or outdated. They're just being drowned out by everyone else's noise.

The path forward isn't about finding better tools or smarter strategies; it's about finding the right ones. It's about trusting what you already know and protecting that knowing from the constant stream of other people's solutions.

Start there. Let everything else be background noise.

Last week, the fog was real. I kept bouncing between browser tabs, tools, and notes, trying to decide which project to pursue.

It wasn’t that I didn’t have ideas. It was that I had too many.

And that’s when I remembered my Netflix moment—the day I spent 45 minutes trying to pick a show and still ended up rewatching something old.

Sometimes, it’s not the work that’s hard. It’s the choice.

The belief that keeps us circling

We’re told that picking the right idea is the most important step in starting anything. That message is baked into startup culture, online business courses, and even well-meaning advice from friends.

"Don't waste your time." "Pick a niche before you start." "Make sure it's profitable first."

But here's the truth: all that pressure to be strategic, smart, and certain? It doesn't help. It slows you down. It turns possibility into panic.

Because instead of exploring and experimenting, you’re trying to future-proof every decision before you even begin.

The fear of choosing wrong becomes bigger than the excitement of starting.

And when that happens, it’s not clarity you’re after—it’s permission. You don’t need a genius idea. You need a green light to move.

That’s the shift that changes everything.

That Netflix scroll moment

I wasn’t in the mood to think. I just wanted to rest. But even relaxing became complicated.

Netflix was open, the couch was calling, and yet I sat there—scrolling, previewing, hesitating. For 45 minutes.

Because I didn’t want to waste my time. Because I wanted to make the best choice.

That moment hit me in the gut—I caught myself turning a simple yes-or-no into this dramatic high-stakes poker game where the jackpot was millions. That same energy shows up in business, especially when we’re trying to pick our “big idea.”

It’s not laziness. It’s not procrastination. It’s fear masquerading as caution.

We don’t need more time—we need permission to stop perfecting and start.

The Permission-First Framework

Here’s what I’ve seen work—not because it’s clever, but because it’s realistic when your brain is foggy and your heart is unsure:

1. Pick an idea that feels light.
Not light, as in flaky. Light, as in I could easily do this over and over. Think about the idea you’d be willing to explore on a slow day. That’s usually a sign that holds some energy for you.

2. Drop the outcome obsession.
You can’t know what will work until you try it. So shift your focus: Instead of thinking in can’t and won't, think about the lessons you will learn if you fall on your face.

3. Cross off the idea that drains you.
Sometimes, you look at your ideas and feel like you’ve been body-slammed with fatigue. Even if it’s profitable and trendy - you feel the pull of weight dragging you straight down. You know this point is to pull back and save your energy.

4. Decide with a deadline.
Give yourself 24 hours. Not a month. Not a week. A short time period so that you won’t beat the dead horse. A small window forces you to listen to your gut instead of endlessly analyzing every angle.

5. Let curiosity lead.
Ask yourself: which of these ideas am I genuinely interested in right now? Not for life. Not for strategy. Just now. Curiosity is a true north compass—especially when confidence is wobbly.

What if we've been putting blind faith in knowing all the answers?

We praise the quick-thinkers. We give kudos to those who speak without hesitation. We're drawn to the person with the bold vision scribbled on a napkin.

But most people I’ve worked with didn’t get clear until they were already in motion. Doing so taught them what worked and what didn’t, giving them data to trust their own process.

And more often than not, their original idea morphed into something even bigger and better.

The point isn’t to have certainty. The point is to get going.

Try this today:

Write down the three ideas you’re currently circling.

Now cross one off.

Then, choose the one that feels lightest or most interesting.

Give it one week of honest effort. Just one.

At the end of that week, you’ll know more than you do now. And that clarity will be earned, not imagined.

Taking the next step

There’s no shame in being stuck. And there’s no shame in asking for help to get unstuck.

If you want support figuring out your next step, I created Clarity On Call just for that.

It’s a simple way to bring your ideas, get clear on what matters, and walk away in one direction that feels like you.

Taking it one step at a time with you,
Lee

Who am I to question the six-figure dream?

I was stuck in a cycle that every solopreneur begins at — working harder, hustling longer, and constantly comparing myself to others who seemed to hit this benchmark effortlessly. My personal and professional life felt out of sync, and I began to wonder: Is this even what I want?

Redefining Success: Why Enough Is the New Goal

It hit me one evening as I stared at a spreadsheet filled with projections and goals that felt foreign and unattainable. I realized I had never stopped to ask myself what enough looked like for me. My six-figure goal wasn’t based on my lifestyle or values—it was based on someone else’s definition of success. That was the moment I decided to rethink everything.

I started by stripping it down to the basics.

What did I truly need to live a comfortable life? What expenses were non-negotiable, and what could I let go of? Most importantly, what kind of life did I want my business to support? These questions shifted my perspective from chasing more to focusing on what mattered.

The Problem with the Six-Figure Obsession

For years, we’ve been sold the idea that six figures are the hallmark of success. Social media is full of coaches and entrepreneurs bragging about their “multiple six-figure” businesses. But here’s what they don’t tell you:

1. Six figure gross revenue isn’t the same as six figures in your pocket. Taxes, expenses, and overhead chip away at that number until it often looks more like $50K or less.

2. Chasing someone else’s idea of success can leave you burnt out and disconnected from what truly matters to you.

3. An arbitrary goal like “six figures” doesn’t reflect your unique circumstances, whether you’re supporting a family, living in a high-cost area, or striving for more spare time instead of more cash.

Aligning your income goals with your values, lifestyle, and priorities changes everything. Instead of feeling like you’re failing to keep up, you’ll focus on what actually makes you thrive.

The Power of Knowing Enough

Imagine building your business around what you need instead of what sounds impressive. That’s where knowing your “enough number” comes in—the minimum income that allows you to live your desired lifestyle comfortably, with room for growth.

When you know your “enough number,” you stop chasing numbers that don’t matter and start designing a life that does. Here’s why it matters:

1. It Reduces Overwhelm

Without a clear target, it’s easy to feel like you’re always falling short. That constant pressure to “do more” or “earn more” can lead to burnout. But when you have a defined enough number, you know exactly what you’re aiming for—and when you’ve hit it. This clarity quiets the noise and lets you focus on what really matters.

2. It Aligns Your Work with Your Values

Your enough number isn’t just about covering bills—it’s about living a life that reflects what you care about most. Whether it’s spending more time with family, traveling the world, or having space for creativity, knowing your enough number helps you prioritize those things without guilt.

3. It Prevents the Lifestyle Inflation Trap

Knowing your enough number keeps you grounded. Instead of automatically upgrading your car, home, or lifestyle. Some feel that when you earn more, you spend more. Suddenly, what used to feel like plenty isn’t enough anymore. This is lifestyle inflation at its worst.

4. It Helps You Say No with Confidence

When you’re unclear about your financial needs, it’s tempting to say yes to every opportunity, even if it doesn’t align with your goals. But knowing your enough number gives you the confidence to say no to projects, clients, or commitments that don’t fit into your bigger picture.

5. It Builds Long-Term Sustainability

Chasing random income goals often leads to overwork and burnout. But when you define your enough number, you can build a business model that supports sustainable growth. You can focus on consistency rather than quick wins, creating a life and business that thrives long-term.

Chasing Six Figures

Chasing six figures isn’t always the solution to a fulfilling life or business. Knowing your “enough number” is. This number reflects your unique needs, values, and aspirations. It’s not about settling or thinking small—it’s about clarity and alignment.

Think of it like this: Imagine taking a vacation with no destination planned. How do you know when you’ve gotten there?

But when you define “enough,” you’re setting a clear marker for success. It doesn’t mean you can’t aim higher, but it gives you a baseline to work from—one that’s rooted in reality, not expectations of others who are set on all hustle.

Make It Practical

Want to find your “enough number”? Here’s a simple framework to get started:

1. Calculate Your Essentials: List your non-negotiable expenses—housing, food, insurance, debt, and savings goals.

2. Add Your Happiness Factors: Include what brings you happiness, like hobbies, travel, or dining out.

3. Factor in Flexibility: Build a cushion for unexpected expenses or opportunities — the rainy day fund.

4. Define Your Priorities: Ask yourself, “What kind of life do I want my income to support?” Use this to refine your number.

Transform Your Expectations

Here’s what surprised me the most: knowing my enough number didn’t just reduce money making stress—it transformed how I approached my business. I had the confidence to:

• Say no to projects that don’t align with my goals.

• Invest in tools and training that supported my growth.

• Build a schedule that balances both work and play.

Defining your enough number is empowering. It’s not about limiting yourself; it’s about creating a life that’s fulfilling and sustainable—one step at a time.

Tools to Help You Build Clarity

If you’re ready to break free of the six figure trap, here are some tools and strategies to guide you:

• Profit First by Mike Michalowicz: This book and system flips traditional budgeting on its head, prioritizing profit and sustainability.

• A Monthly Budget Tracker: A simple spreadsheet or app like YNAB (You Need a Budget) can help you manage expenses and avoid surprises.

• Values-Based Planning: Ask yourself, “What kind of life do I want?” and reverse-engineer your income goals to support that vision.

Chasing six figures might sound ambitious, but it’s not the solution for everyone—and that’s okay. By defining what enough looks like for you, you can stop running on the hamster wheel and start building a business that feels aligned and sustainable. Because at the end of the day, success isn’t about a number—it’s about creating a life you love.

What’s holding you back from redefining success on your terms? Let’s talk it.

A good bit ago, we (meaning the hubs) had a dream to move to the country on lots of land. I was convinced we could make it work, and that started the hunt for property in a rural community. The kind of place you can sit on the front porch, breathe in the fresh country air, not have to listen to city traffic and watch the sunset over the farm lands. Perfect scenario, right?

Well almost and here’s what happened.

Catching the Dream

We found the “perfect” space — a 100-year-old farmhouse on 22 acres of land. It needed a bit of TLC, but we wanted to put our touch on it anyway. I imagined all the things I could do with this rustic dream in the making.

So, we put in the offer and made plans to move. The excitement of it was overwhelming — giving up the norm for a new, adventurous dream.

Reality Set in Quick

For the first few weeks it was wonderful, exciting possibilities for the honeymoon phase. Every morning I’d wake up, take a walk around the pond and property and bask in the silence.

But the reality set in — the house was huge, the property was even bigger and there was a lot more to do then TLC stuff. The maintenance was unsettling, from the old outdated appliances to the critters that made a home in the attic. And we won’t talk about the heating bills from the old oil furnace. I was starting to regret this part of my dream life.

And the property. At first, it was great to have all this space. But soon I felt the loneliness of the seclusion. Not to mention the upkeep of mowing the lawn and who knew there was upkeep in the wooded areas.

Where Did We Go Wrong?

Here’s the thing that no one told us about moving from the city — it’s a ton of work. It’s not just about maintaining the space, but not having our circle of family and friends to rely on. Every time I looked at the pond I thought it would be so nice, I saw the scum and overgrowth.

And the house was so big, and so old. Sure, it had character, but there were a lot more spaces to keep clean and heated. I missed my single story, 3 bedroom ranch house. This house felt huge and empty — the memories were all gone.

Downsizing At First Chance

Not quite two years after our big move, we wanted out. The rural dream was draining us — more mentally than physically. The upkeep, the space, the loneliness…it became too much. Luckily for us, there was an interest in the property, and we jumped at the chance to sell.

Let me tell you, to say we were thrilled with the decision to sell is an understatement. Suddenly, I had more time to concentrate on growing my business. More energy to get back to hobbies and fun stuff. I didn’t have to worry about the next project, and more importantly, we now were in a neighborhood community. Sure, I didn’t have the quietness anymore, but I had a space that I felt connected to again.

The Lesson: Bigger Isn’t Always Better

Looking back on it now, it was a great idea to give it a go. There’s something about wide-open spaces that many don’t get to enjoy. But for me, bigger isn’t better — it’s more things that can go wrong and cause added stress.

I need small and intimate, Things that allow me to connect with people, places, and things. Much like how I structure my business. Enjoying a handful of clients on projects that bring them purpose and joy. Because I want things that truly improve life — physically and mentally.

Sometimes What We Think We Want

Moving to a rural area wasn’t my ultimate dream, but I thought it’s an adventure, let’s make this work. Occasionally, what we think we want isn’t actually what we need.

There’s no shame in realizing that bigger isn’t always better. We don’t need other people’s dreams or benchmarks. So if you’re tempted to go big because someone told you should — think about the joys staying small will bring by the simpler choices.

If you’re feeling overwhelmed, it might be time to rethink what you really need to be happy.

How about you…have you ever regretted a decision because it was bigger but not better?

I’ve (we’ve all) been there. You start with big ambitions, ready to invest whatever it takes to build a successful business. So, you throw money at courses, new software, or books from “experts” who seem to have it all figured out. But instead of a breakthrough, you end up overwhelmed, staring at a long list of things you should do. And worse—your business hasn’t budged an inch.

It’s enough to make you want to quit. It feels like you’re pouring everything in and getting nothing back.

But here’s the deal—I know you’ve tried. You’ve worked hard. You’ve read the books, taken the courses, and followed all the advice, but somehow, it feels like spinning your wheels. The progress just isn’t showing up, and you start to wonder if maybe you’re not cut out for this whole “entrepreneur” thing after all.

That’s precisely where I used to be.

Why Most People Fail When Trying to Invest in Themselves

Most people are told that to succeed in business, you need to build your skills and invest in yourself—whether that’s paying for a business coach, signing up for the latest online courses, or buying fancy tools to streamline your workflow.

Here’s what most people do when they try to solve the problem:

1. They throw money at it. They think the more they spend, the faster the solution will come. Not only that, but they shell out hundreds thousands, for programs that promise results, only to find themselves with more knowledge but no change.

2. They go into debt. Many people believe that going into debt is a sign of commitment. After all, aren’t we told “If you’re serious, take out that loan or max out my credit card to prove it.” While I did not put myself in debt monetarily, I wasted my fair share of time.

3. They focus on finishing courses or books, but forget the follow-through. Raising hand here, guilty as charged. You get that rush from completing the course or finishing the book, and then… you move on to the next thing without implementing any of it.

So what happens? The same results over and over again.

• You feel broke and stretched too thin, financially and mentally.

• You lose momentum because you’re overwhelmed by all the information and options.

• You start to question whether this whole “building a business” thing is even a thing.

And listen, I get it. It feels like everyone else is moving ahead while you’re stuck in the same place, even though you’re doing all the right things.

How I Broke Out of the Cycle

I know all of this because I was exactly like that.

I had a budget for professional development and I used to believe that if I just invested enough money or finished enough books, my business would take off. But I’d still find myself in the same place—overworked, overwhelmed, and underperforming. With courses unfinished and books on my to-read list.

At some point, I hit a wall. I realized something had to change because, I love building businesses and helping people… but how could I keep doing this if I wasn’t walking the walk? How could I suggest learning if nothing was moving the needle forward?

That’s when I asked myself the most important question:

What if the investment isn’t just about money? What if it’s about the commitment of my time, energy, and effort in the right ways?

Change is good, right?

I stopped throwing money at the problem or mindlessly checking boxes off my “learning list”. Every investment I made—whether in time, money, or energy—had to be smart, sustainable, and action-driven.

The Secret to Smart Investing in Yourself

Most advice about investing in personal development misses the mark. It focuses too much on the money part and not enough on the action part.

It’s not about how much you spend. It’s about how committed you are taking one small step forward.

So here’s my best advice for putting skin in the game the smart way:

1. Invest only what you can afford. Don’t go into debt trying to buy your way to the top. You don’t need to spend thousands to make progress. Start small and scale up as you grow. You can learn so much with a $20 book, a low-cost webinar, or even just asking the right questions to the right people. Don’t let anyone make you feel like you need to forgo that “cup of expensive coffee” to be “serious” about your business.

2. Make it count. Every time you sit down to learn something new, don’t focus on just finishing the course or the book. Focus on implementing what you learn. Even if it’s one small thing, it’s better than rushing through content for the sake of saying you’re done. Learning without action is just busywork and consumption.

3. Celebrate action. This one is key! Too often, we reward ourselves for finishing things, but not for actually applying what we’ve learned. Next time you take action on something—whether it’s a new strategy, a marketing technique, or a workflow improvement—reward yourself then. Celebrate the fact that you’re moving forward.

Why This Advice Works

Most people don’t succeed because they’re focused on spending more money or collecting more certificates and badges. They forget magic happens when you take action and the results you bring to the table.

This advice works because it’s sustainable. You’re not burning out, financially or mentally. Instead, you’re building real, lasting skills that will actually help your business grow over the long term.

Sure, investing in yourself does take money. But it’s more about where and how you spend that money, as well as the time and energy you put in.

You don’t have to be the person who spends thousands of dollars on courses you never finish. You don’t need to run yourself into the ground to prove you’re serious about your business. And you definitely don’t need to follow every single piece of advice out there just because some expert said it’s what you should do.

What Do You Truly Want?

Do you hate the pressure to spend thousands of dollars just because some expert says you need it to grown your business?

Do you hate that sinking feeling of being overwhelmed by all the options—books, courses, coaches, programs—without knowing what will actually work?

Do you hate the cycle of working hard but not seeing the results you hoped for?

Yes, yes and hell yes.

What you really want is:

• To see real progress from the skills you’re learning and applying.

• To feel confident that you’re making smart investments in your business growth, without the pressure of going broke or burning out.

• To enjoy the process of building your business, without the constant feeling of overwhelm.

Here’s the bottom line:

Putting skin in the game is crucial, but do it wisely.

Invest in your skills, but only what you can afford. Apply what you learn. And most importantly—celebrate every little win along the way. Those small actions will snowball into big results if you stick with it.

So, next time you’re about to hit “buy” on that expensive course, or when you’re feeling guilty for not finishing yet another book, ask yourself: “Am I investing wisely? Or am I ready to make this investment count?”