The Liberating Power of Self-Honesty: Why You Haven’t Earned What You Want (Yet)

Last week, a tweet from @_iamEtornam punched me straight in the ego: “If you haven’t gotten what you want, you’re not worthy of it yet… You’re not struggling with imposter syndrome. You’re a student pretending to be the teacher.” At first it stung like hell. Then it felt like someone had finally opened the windows and let the fresh air in. For years I’d been treating accurate self-assessment as a psychological problem, calling my obvious skill gaps “imposter syndrome” so I could stay comfortable. The truth is simpler and more brutal: the market pays for proof, not potential, and my income had been giving me an honest performance review I kept refusing to read. Accepting that my results were a direct reflection of my current ability—not my worth as a person—was the most liberating realization of my career.

Once I stopped demanding to be paid like an expert and started acting like a hungry beginner, everything accelerated. I began asking the questions I used to avoid: “Can you walk me through how you’d do this?” “I thought I knew this—clearly I don’t; start from the basics.” Every time I swallowed my pride and admitted ignorance, I leapt forward. Pretending to know gave me a temporary ego shield and permanent stagnation; admitting I didn’t know gave me momentary discomfort and lifelong mastery. The people I admire most aren’t the ones who never doubted themselves—they’re the ones who turned doubt into fuel instead of hiding behind it.

So now every Sunday I run a 10-minute honesty ritual: What am I actually world-class at today (evidence required)? Where am I still faking it? What’s the single skill bottleneck holding everything else back? Then I go find someone better and beg for help. The fastest way out of beginner status is to embrace it on purpose instead of pretending you’ve already arrived. When was the last time you looked in the mirror and said, out loud, “I’m not good enough at this… yet”? That moment of raw admission is where real growth begins.

Are We Losing the Ability to Explain Tech?

A wake-up call from one simple tweet

“One of the biggest side effects of over-relying on AI? We’re losing the ability to explain concepts to other humans.” — @uxderrick

That single line, posted on X in 2025, hit the tech timeline like a quiet thunder. It’s short, unadorned, and terrifyingly accurate—especially for anyone who writes code, designs systems, or ships products for a living.

The New Normal in Engineering Workflows

Open any modern IDE in 2025 and you’ll see it: GitHub Copilot, Cursor, Claude Code, Gemini—AI is no longer a helper; it’s the co-author of most production code. Pull requests now contain entire features written in seconds. Architecture diagrams are generated with a prompt. Documentation? AI can spit out a 2,000-word README faster than most engineers can open Notion.

The output is impressive. The velocity metrics are through the roof. But something subtler is slipping away.

The Vanishing Skill of Human-to-Human Explanation

Think about the last time you had to:

• Whiteboard a distributed system for a skeptical principal engineer
• Justify a caching strategy to a staff+ reviewer
• Walk a product manager through why a certain database choice matters
• Onboard a junior dev by explaining the mental model behind your team’s codebase

These moments used to be daily rituals. Now they’re becoming rare.

When the AI already “knows” the answer and can generate a flawless explanation, the incentive to internalize and rephrase, and teach disappears. We copy-paste the AI’s answer, ship the ticket, and move on. The loop of deep understanding → articulation → feedback → deeper understanding is quietly breaking.

Real-World Symptoms I’ve Seen This Year

1. Code reviews turning into “LGTM” fests because no one can explain the clever trick the AI used.
2. System design interviews where candidates freeze when asked to explain their own AI-generated solution without the model’s help.
3. Incident post-mortems that read like polished ChatGPT output but leave the on-call team unable to answer basic follow-up questions.
4. Senior engineers struggling to mentor because they haven’t manually reasoned through a problem in months.

This Isn’t Anti-AI; It’s Pro-Craft

AI is the most powerful leverage engineers have ever been handed. The goal is not to reject it, but to refuse to let it atrophy the very skills that make us valuable in the first place.

Some practical ways to fight the erosion:

• Force yourself to re-explain every AI-generated solution in your own words before merging.
• Run “no-AI” pairing sessions or design reviews once a week.
• When reviewing PRs, ask the author to record a 90-second Loom walking through the change without reading the AI comment.
• Treat prompts as code: store, review, and iterate on them so the human reasoning stays in the driver’s seat.

Final Thought

Tools amplify skill; they don’t replace it. The moment we forget how to explain the magic is the moment the magic stops belonging to us.

@uxderrick didn’t just write a tweet. He diagnosed a slow-moving crisis in our industry. The good news? It’s entirely within our power to fix—just as long as we keep practicing the uniquely human art of turning complexity into clarity.

Let’s keep building with AI. But let’s never stop teaching like humans.