I scroll LinkedIn, what do I see?

Perfect headshots. Studio lighting, crazy sharp, precise smiles, not a hair out of place. Perfect posts and comments. Flawless grammar, zero typos.

It’s all clean, polished and soulless.

This is the Great AI Flood. The cost of looking competent, of sounding smart, has just dropped to zero.

And this is where the problem begins.

The Collapse of Signal

In economics, when you flood a market, the asset’s value collapses. For many years, polished content was a signal of professionalism. Now that AI can produce it instantly, polish has just become noise.

The burden of effort has shifted from the creator to the consumer.

My mental energy as a reader is no longer spent understanding your idea. It’s spent on a exhausting calculation: Is this real?

  • Is this a real photo, or Stable Diffusion, or Gemini?
  • Is this a real insight, or a ChatGPT] remix of the top 10 blog posts?
  • Is this a real comment, or a bot?

This is the collapse of the signal-to-noise ratio. And it’s eroding the one thing that matters: Trust.

The Return of “Rough Edges”

When a signal becomes cheap, it’s no longer a reliable signal.

For years, a professional headshot was a signal: “I care enough about my career to spend $200.” Today, a perfect AI headshot is a signal: “I care enough to spend 30 seconds on a prompt.”

When “polish” is cheap, rough edges become the new status symbol.

A slightly blurry selfie from your office? I think it’s real. It’s Proof of Effort. A post with a small typo or an awkward sentence? It’s Proof of Thought.

But here’s the deeper signal, the one that really proves expertise: The Bumps and Bruises.

An AI-generated case study is perfect: “We increased ROI by 400%.” It’s clean. It’s also unbelievable.

The real signal of human expertise isn’t perfection; it’s the messy story. It’s the Proof of Experience.

“This was a tough project. We chose the wrong database and had to migrate for 3 weeks. Here’s what we learned…”

An AI can generate a plausible-sounding failure story. It can say, ‘we chose the wrong database,’ and even invent a ‘stubborn VP of Engineering’ or a ‘4 AM call.’ It’s a perfect remix of the thousands of ‘war stories’ it was trained on.

But that’s a script, not a memory.

The real signal isn’t hearing the story anymore; it’s interrogating it. Ask why. Ask for the specific details. ‘What exact query failed?’ ‘Why Postgres and not MSSQL?’ An AI’s story is perfect most of the time, but it collapses under deep, specific questioning.

And even then, where is the proof of history? An AI can’t show you the messy GitHub commit history. It doesn’t have three real former colleagues you can call for verification.

An AI can talk about the mess. It can’t prove the mess. It has no verifiable bumps and bruises.

What’s Next?

I keep thinking about what’s next. Honestly, I don’t think it’s going to be a better AI. I bet it’s going to be the mess of tools and habits we come up with to deal with this AI flood.

For example, it seems like we’ll go back to trusting things that are hard to fake. Why do I feel like a podcast is more real than a blog post lately? Because it takes effort. You can’t just generate one in 10 seconds. We’ll instinctively trust formats that are expensive in time and energy to produce.

This also means those hard-to-join communities suddenly become more valuable. Their annoying rules accidentally make for the best bot filters.

In the end, I guess it all comes down to origin. I find myself caring less about how polished something looks and more about where it came from. It wouldn’t be surprising if we start seeing tools that can actually certify that a real human wrote this or this photo was taken by a Sony Camera.

Conclusion

In the Age of AI, polish is no longer the signal. It’s just the baseline.

A polished surface with no proof is the new noise. A messy truth with no polish is just sloppy work.

The real signal of trust isn’t about being messy.

It’s about proving that your polish is earned.