The Unoptimised Human — We Can See Everything and Still Get It Wrong
July was a strange month to be in marketing.
July was a strange month to be in marketing.
We have more data than any generation of marketers in history. We have AI that can write copy, generate creative, segment audiences, and optimise spend in real time. We have behavioural science frameworks that map exactly how humans make decisions. And yet, watching the output from most brands this month, you’d think we’d learned nothing at all.
That’s not a technology problem. It’s a thinking problem.
The thread running through everything I wrote in July is deceptively simple: knowing more doesn’t automatically mean understanding better. In fact, it often means the opposite. More data can create more confidence with less comprehension. More AI tools can produce more output with less intelligence. More behavioural research can generate more papers that prove whatever you already believed.
The gap between information and insight is where the interesting work happens. Here’s what I explored this month.
The Vibe Marketing Paradox: Technical Competence Without Brand Intelligence
The “vibe coding” conversation hit marketing this month, and it exposed something uncomfortable. Yes, AI can generate technically competent marketing. The copy is clean. The structure is sound. The A/B tests converge. But competence without distinctiveness is just noise at scale.
I called this the Vibe Marketing Paradox: the easier it becomes to produce marketing that looks right, the harder it becomes to produce marketing that feels right. When everyone has access to the same tools, the tool stops being the advantage. The thinking behind it becomes the advantage.
The brands that will struggle aren’t the ones without AI. They’re the ones who let AI make the decisions that should be human.
“Competent Beige”: When AI Optimises the Soul Out of Your Brand
This one came from a simple observation: three posts from three different brands, in completely different sectors, could have been written by the same person. Same rhythm. Same safe, balanced tone. Same vaguely inspirational sign-off.
I called it “Competent Beige” — the phenomenon where AI-optimised brand communication converges on a mean that is technically proficient and emotionally invisible. It’s the marketing equivalent of airport architecture. Everything works. Nothing stands out. You forget it the moment you look away.
The uncomfortable truth is that optimisation, by its very nature, moves towards the average. If your brand differentiation depends on being distinctive, and you hand the wheel to a system designed to converge on what works best across all inputs, you will end up in the same place as everyone else. Beige. Competent. Invisible.
Action Bias: The Fallacy of “We Have to Do Something”
Every football fan has watched a goalkeeper fling themselves dramatically to a penalty corner while the ball rolls gently down the middle. It looks like poor judgement. It isn’t. It’s action bias — the deeply human tendency to prefer doing something over doing nothing, even when inaction would produce a better outcome.
Marketing is saturated with it. The quarterly panic that demands a new campaign. The competitive anxiety that triggers a rebrand. The algorithm change that provokes a strategy pivot. We confuse motion with progress and activity with strategy.
The most valuable discipline in marketing isn’t knowing what to do. It’s knowing what not to do, and having the confidence to hold your nerve when everyone around you is demanding action.
Attention Architecture: Emotionally Intelligent AI
I ended the month with a big swing. The original Transformer paper was called “Attention Is All You Need.” I think the next chapter of AI needs a subtitle: “But Only If You Know What to Pay Attention To.”
Current AI systems are extraordinary pattern-matchers. They attend to everything with equal mathematical rigour. But human attention doesn’t work that way. We attend to what matters emotionally, contextually, and motivationally. The gap between computational attention and human attention is where the next breakthrough lives.
If we can build AI that understands not just what people are saying but why they’re saying it — what psychological need is driving the communication, what emotional state is shaping the word choice, what motivational direction is behind the request — we move from tools that process language to tools that understand people.
That’s not a small ambition. But it’s the one that matters.
What I’m Watching
The EU AI Act enforcement deadline landed on August 2nd. I wrote about what it actually means for marketers (short version: more than you think, less than the panic suggests). The real impact isn’t compliance — it’s that regulation is now treating AI as infrastructure rather than novelty. That shift in framing will reshape how organisations invest in and deploy these tools over the next eighteen months.
Social proof dynamics are getting weird. I explored how tribal identity can override quality signals in market adoption, and why the “tipping point” model is too simplistic for how communities actually shift. If your acquisition strategy depends on social proof, the mechanics of which social proof matters are changing fast.
The Question
Here’s what I keep coming back to: we built tools to understand human behaviour at scale, and we’re using them to produce output that ignores human behaviour at scale.
The brands that win the next three years won’t be the ones with the best AI. They’ll be the ones who understand that AI is a capability amplifier, not a strategy substitute. The technology is the easy part. The thinking is the hard part. And the hard part is where the value lives.
What are you seeing? Are brands actually getting smarter, or just getting faster at producing the same things? I’d genuinely like to know.
David Chadderton spent his twenties and thirties teaching people how to make life-or-death decisions at forty thousand feet. He now applies the same principles to consumer psychology, which, depending on the brief, can feel equally high-stakes. He’s the creator of the STAR Framework and the author of The STAR Framework: Rewriting the Rules of Consumer Engagement (NYC Big Book Award 2025), The STAR Operating System: Decode Mindset, Understand Motivation, Transform Human Behaviour, and Dear Algorithm, It’s Not Me, It’s You. By day, a Chief Marketing Officer. By night, a behavioural science obsessive who writes The Unoptimised Human because he can’t stop thinking about why people do what they do.
The STAR Framework
If you enjoyed this essay, you'll find the full argument — and the framework behind it — in the book.