For a long time, I thought my problem was just that I was getting bad advice. I’d read the threads, the blog posts, and those perfectly structured AI breakdowns that sounded so smart. They’d explain the situation, cover the edge cases, and warn me about every possible risk.
And yet, after all that, I’d still feel... nothing. Not clearer, not more confident. Just informed and completely stuck. It took me a while to realize the issue wasn’t the quality of the advice itself—it was that none of it answered the only question that actually matters.
Advice avoids values by design
Most advice—especially the stuff coming out of an AI—is designed to be broadly acceptable. It tries to help everyone, which means it can’t actually take a real stance. It tells you how to optimize, but not what’s actually worth optimizing. It explains the trade-offs, but it won’t tell you which ones you should be willing to live with.
That’s not a flaw in the system; it’s a feature. AI can help you move faster once you’ve picked a direction, but it has no way of telling you which direction deserves your time, your energy, or your risk. That decision requires values, and values aren’t data.
Why everything sounds "reasonable" but useless
I kept running into this pattern. Whenever I asked the AI something like, “What’s the best approach?” or “What should I focus on?” the answers were always calm, balanced, and logical.
And they were completely hollow.
Real progress rarely comes from choosing the most “reasonable” option on a spreadsheet. It comes from choosing the option that aligns with what you actually care about—even if it looks a bit irrational on paper. AI can tell you what minimizes risk, but it can’t tell you what is worth risking everything for.
Clarity comes after you commit
I used to believe that clarity came first, and then commitment followed. Now, I’m starting to think it’s the exact opposite. Most of the time, clarity only shows up after you’ve committed to something and started living with the consequences. You don’t think your way into caring; you act your way into understanding.
AI encourages this illusion that if you just analyze things long enough, the “right” answer will eventually appear. But there is no right answer without a chosen frame of importance—and only you can provide that frame.
How I use AI without losing the meaning
The shift for me was subtle. I stopped asking the AI what matters, and I started telling it what matters to me—even if my definition was shaky.
Instead of asking, “What should I do?” I’ll say, “I care about X way more than Y. If that’s true, what’s going to break in my plan?”
That changes everything. Suddenly, the AI is a stress-test for my values, not a replacement for them. It helps me see blind spots and inconsistencies, but it doesn’t pretend to make the choice for me.
Why this feels so uncomfortable
Choosing what matters is scary because it’s irreversible. Once you admit you care about something, you’re accountable to it. You can’t hide behind “more research” or “better optimization” anymore. You’ve drawn a line in the sand, and lines create tension.
AI can remove friction almost everywhere—except for the one place that counts: deciding who you want to be on the other side of the work. That discomfort isn’t a bug; it’s the signal that you’re actually doing something that matters.
Final Thought
AI doesn’t fail at giving advice; it fails at telling you what deserves your life.
The emptiness people feel when they use these tools isn’t because the AI is shallow—it’s because meaning can’t be automated. If you don’t decide what matters first, every answer you get will feel technically correct and personally useless.
I’m still learning how to make those choices without hiding behind “better” advice. One uncomfortable choice at a time.