Hearing the Signal in the Noise

How AI Abundance is Training Us to Become Better Curators

The LinkedIn Scroll Paradox

You're scrolling through LinkedIn, and 90% of what passes by is the algorithmic equivalent of road noise—carousel posts about "5 Leadership Lessons from My Toddler," AI-generated motivational quotes overlaid on stock photos, and the endless parade of "Agree? Thoughts?" engagement bait. What's intended to be "impactful" content becomes highway hypnosis of bland, fungible billboards.

But then something stops you. Something makes you pause mid-scroll, back up, and actually read. In that moment of recognition, you've just demonstrated an evolutionary adaptation you didn't know you developed: expert-level signal detection in information-saturated environments.

This isn't just about social media consumption. It's about a fundamental shift in how creative work happens when AI can generate infinite content but human attention remains finite. As we've been drowning in AI-generated mediocrity—we've also trained ourselves to become better curators.

Take the Goblins Bowling

Last week, I was scrolling through a Facebook art group—another torrent of AI-generated fantasy art, mostly warrior women in impractical armor. Background noise, highway hypnosis of décolletage. Until one image had me pulling a u-turn: a quartet of goblins at a bowling alley, all with matching team shirts.

That single moment of pattern recognition—seeing past the noise to spot something genuinely interesting—triggered a cascade that demonstrates how creative work actually functions in the age of AI abundance.

Within minutes, I was asking "what if?" What if these goblin bowlers were characters from The Big Lebowski? What if we made this into a game? What if we collaborated with AI to build it out?

One hour later, we had "TiGGR: The Green Lebowski"—a complete, playable tabletop RPG that fits on eight pages and delivers a full gaming experience in 30-45 minutes. But the real story isn't the game itself. It's what that one hour of creation time unlocked.

The Multiplication Effect

When you can go from concept to complete product in an hour, you flip the risk/reward calculus of creative work.

Traditional model: 90% creation, 10% refinement
New model: 10% initial creation, 90% iteration and optimization

That one hour wasn't just impressive speed—it was runway clearance for everything that actually matters: playtesting, balancing, simulation, load testing, and iterating based on real user feedback. All the "niceties" that wouldn't have had bandwidth in the unaugmented approach.

When initial creation is an hour investment, you can afford to experiment with wild ideas that might not work. You can test five different approaches in the time it would have taken to outline one traditional project, and because of the AI augmentation the sunk cost fallacy of time invested slinks to the corner to sulk.

You're not just making things faster—you're making better things because you have bandwidth for the parts that actually matter to users.

The Orchestration Model

The process revealed something crucial about how human-AI collaboration actually works. This wasn't "AI made a game"—it was human curation plus AI amplification creating something neither could have achieved alone.

I lit four different fuses to four different LLMs: Claude for mechanical clarity, Grok for creative riffing, Gemini for structural feedback, ChatGPT for polish suggestions. Each AI contributed specialized strengths, like sections of an orchestra responding to a conductor's direction.

But here's where it gets interesting: I had AIs talking to each other. Output from one model became input for another, creating a kind of AI-to-AI creative dialogue with a human pruning and feeding the Venus fly traps. There's a LinkedIn post making the rounds this morning about the future of sales and marketing becoming fully automated: "Have your bot talk to my bot. Oh wait, we're both bots!"

That's exactly what was happening—except I was playing mixmaster, MC, DJ, and talk show host all at once. When the conversation between Claude and Grok wasn't producing useful results (or started ramping up into a recursive chain reaction), I'd delete the session and start again. When ChatGPT's polish suggestions were taking things in the wrong direction, I'd redirect. When Gemini's structural feedback was spot-on, I'd amplify it across the other models (all of which would wryly comment on its academic tone—every comedy troupe needs a foil).

The human role wasn't diminished—it was elevated. I became the creative director of a multi-AI ensemble, making hundreds of micro-decisions about what to keep, what to discard, what to push further, and when to stop. The creative "spark" remained entirely human; the AI provided amplification and specialized execution under continuous human oversight.

The Adaptation Thesis

This may seem counterintuitive, but the more AI-generated content floods our environments, the better we become at recognizing what's actually worth our attention. Slop fatigue isn't the problem—it's the training ground and evolutionary pool.

Think about it biologically. When environments become more complex, organisms don't just adapt—they often develop enhanced sensory capabilities. The cacophony of AI-generated content isn't drowning out human creativity; it's creating selective pressure for better creative judgment.

Because of that torrent of slop, fatigue also hones recognition. The more the algorithmic noise becomes background, the more interesting signals pop out. We're not becoming worse at creative work—we're having to become superhuman at pattern recognition and curation.

Business Implications

This has massive implications for how we think about professional skill development in this age of machine minds:

Yesterday's skill: Creating content from scratch
Today's skill: Recognizing exceptional signals in noisy environments
Tomorrow's skill: Orchestrating AI tools to amplify those signals

Organizations that understand this shift and encourage the humans to evolve accordingly will enjoy a significant advantage. They'll stop trying to compete with AI on volume and start focusing on what humans are uniquely good at: judgment, curation, and creative direction.

The companies that thrive won't be the ones that generate the most content—they'll be the ones that consistently identify and amplify the most interesting signals. They'll treat AI abundance as a competitive advantage rather than a threat.

The Evolving Creative Economy

We're not in a creative crisis—we're producing the training montage for our feature film. Every scroll through LinkedIn, every interaction with AI tools, every moment of "this is noise, this is signal" is building cognitive muscle that becomes more valuable as the environment becomes more complex.

Creative professionals may feel like they're the victims of AI abundance, but they can flip the script and become expert curators whose judgment becomes more valuable as the noise increases. The goblin bowler moment becomes proof that human pattern recognition is getting sharper, not duller.

This positions us not as competitors with AI, but as creative directors of AI ensembles. We're developing the ability to spot the one interesting thing in the feed, ask the right "what if?" questions, and then orchestrate multiple AI systems to amplify that insight into something genuinely valuable.

The Undertow Reality

But let's be clear about who gets to surf these AI-augmented waves. This essay describes a path available primarily to knowledge workers with economic security, access to premium AI tools, and jobs that reward curation and creative direction. That's a sliver of the workforce thin enough to shave with.

The grossly unequal distribution of opportunity in this sea change means that while a handful ride the wave, scores get sucked into the undertow. Truck drivers, radiologists, customer service representatives, not to mention the ranks of entry level analysts and developers—they're not being offered evolution into creative directors. They're facing replacement.

The skills I'm describing—pattern recognition, AI orchestration, creative curation—these build on existing educational and economic advantages. You need the luxury of experimentation, access to multiple AI platforms, and work environments that value human judgment over raw output.

This isn't everyone's story. For millions of workers, AI abundance isn't a creative training ground—it's an existential threat. The benefits are accruing to those already positioned to adapt, while the costs fall disproportionately on those with the least agency to respond.

The goblin bowler moment works when you have the privilege to say "what if?" instead of "how will I pay rent?"

Afterword: The Triple Recursive Loop

There's something beautifully meta about how this essay came to exist. I started by writing about creating a game through human-AI collaboration. Then I had a conversation with an AI about the broader business implications of that creative process. Now I'm publishing an essay about adaptive expertise in AI-saturated environments—an essay that was itself created through the exact process it describes.

Right now, as I write this, I'm playing intellectual racquetball with an LLM to transform a story about making games into insights about creative work. The ball keeps coming back with new angles, and I keep hitting it from different positions until something clicks.

You're reading content that was created using the exact methodology it advocates: human curation spotting signal in noise, followed by AI amplification, followed by iterative refinement. Each recursion demonstrates how human discernment plus AI capability creates something more sophisticated than either could produce independently.

The future of creative work isn't about choosing between human and AI—it's about developing the judgment to know when to scroll past and when to stop and back up. And then knowing how to turn that moment of recognition into something worth sharing.

Because in a world full of algorithmic noise, the ability to spot genuine signal—and amplify it into something meaningful—might be the most valuable skill of all.