1 You Can’t Skip Leg Day: Why Building AI Wings on Weak Foundations Is a Terrible Idea
AI tools are intoxicating. You ask a question, and suddenly you’ve got a report that would’ve taken you three days. You feed it some data, and it spits out insights that make you look like a genius in the morning meeting. It feels like you’ve discovered a cheat code for your entire career.
But here’s the uncomfortable truth nobody wants to admit: you’re still going to spend most of your time walking.
You can strap the most magnificent wings onto your back—feathered, AI-powered, holographic, whatever—but if your legs are weak, you’re not going anywhere that matters. And those wings? They start feeling pretty useless when you realize you don’t actually know how to use them.
1.1 The Wing Obsession Is Real (and Slightly Dangerous)
Picture this: A colleague unveils their AI-generated business strategy. It’s gorgeous—full of insights, projections, and buzzwords that sparkle. Then someone asks, “But what’s our actual revenue model?”
Blank stare. The AI didn’t know. Neither do they.
Or the team that automates their entire customer service flow, only to discover the bot confidently invents return policies that don’t exist. The demo looked amazing. The real-world deployment? A dumpster fire with a chatbot helpfully fanning the flames.
AI isn’t magic—it’s a really enthusiastic assistant who will cheerfully bullshit you if you don’t know better. And if you can’t tell when it’s making things up, you’re just a human-shaped megaphone for its hallucinations.
1.2 What “Not Skipping Leg Day” Actually Means
This isn’t about abandoning AI and going back to typewriters. It’s about being strategically smart about where you stay sharp.
1.2.1 Build Your Foundation (The Boring Stuff That Saves You)
Know your domain like you’ll have to defend it: - If you’re in marketing, understand consumer psychology, not just prompt engineering - If you’re in finance, know why the numbers move, not just how to chart them - If you’re in operations, understand the process, not just how to automate it
Practice the fundamentals regularly: - Write something longform without AI once a week—even a journal entry counts - Solve a problem manually before automating it, so you know what “right” looks like - Explain complex ideas without leaning on “well, the AI said…”
Develop your quality radar: The most valuable skill in an AI-saturated world isn’t writing perfect prompts—it’s instantly spotting when the output is subtly wrong. That only comes from knowing the terrain intimately.
1.2.2 Use Your Wings Strategically (The Fun Part)
Here’s where it gets interesting: when your legs are strong, AI becomes devastating.
I know a data analyst who spent months learning to clean messy datasets manually. Tedious work. Now she uses AI to automate 90% of it, but she catches edge cases that would’ve caused disasters downstream because she knows what data corruption looks like. Her AI doesn’t just make her faster—it makes her unstoppable.
The pattern that works: - Let AI handle the tedious, high-volume tasks so you can focus on strategy - Use it to prototype ideas and test hypotheses quickly - Deploy it for the boring-but-necessary work that drains your energy
But always: - Verify outputs against your domain knowledge - Understand the reasoning, not just the result - Stay accountable for the final product
1.3 The Three Tests (Are You Actually Ready to Fly?)
The Unplug Test: If AI tools vanished tomorrow, could you still do your job at 70% capacity? If not, your foundation needs work.
The Grandmother Test: Can you explain why the AI’s recommendation makes sense in terms your grandmother would understand? If you’re just vibing with the output, you’re in danger.
The Spot-the-Fake Test: Given ten AI outputs (nine good, one subtly wrong), can you find the broken one? If not, you’re trusting wings you can’t navigate.
1.4 Common Injuries (And How to Avoid Them)
Competence Theater: Using AI to fake understanding. Fix: Do the work manually once. Learn to walk before you try to sprint.
Shiny Object Syndrome: Deploying AI solutions nobody asked for. Fix: Ask “Does this solve a real problem, or just sound cool?” Be honest about the answer.
Maintenance Blindness: Assuming AI will self-maintain. Fix: Schedule regular quality checks. When the model drifts or data breaks, your legs need to carry you through the fix.
1.5 The Real Win: Legs + Wings = Unstoppable
Most of your career will be: showing up, doing incremental work, understanding context, making judgment calls in gray areas, and being accountable when things go wrong. That’s all walking. AI doesn’t make that obsolete.
The wings are for when you need to cross a canyon or scout from altitude. But you live in the valley. You build things step by step. You meet people on the ground.
The teams that win aren’t the ones with the fanciest AI tools. They’re the ones who combine old-school competence with new-school leverage. They know their craft well enough to spot when AI is helping and when it’s hallucinating. They use automation to reclaim time for thinking, not as a replacement for thinking.
1.6 The Bottom Line
So yes—absolutely use AI. Build the wildest wings you can imagine. Automate the tedious stuff. Scale the unscalable. Let it carry you over the boring parts so you can focus on the work that actually matters.
But do it standing on legs that could carry you home if every battery died tomorrow.
Because flight is spectacular. But walking is how you get anywhere that matters.
Now go build something cool. Just maybe do a few squats first.