As AI eats more of our creative labor, the last moat left is “taste.”

Everyone’s suddenly selling it — philosophers, founders, designers — each trying to define it, teach it, or trademark it.

But most of these conversations miss each other completely.
Some frame taste as intellect — a product of culture, context, and critique.
Others call it instinct — a gut feeling you’re either born with or not.

The truth? Both are real — and they feed each other.

What I’m seeing is that there are two kinds of taste — Epistemic and Empirical.

Epistemic taste comes from understanding — studying why something is beautiful, balanced, or meaningful. It’s what curators, critics, and artisans cultivate through context and reflection.

Empirical taste, on the other hand, comes from exposure and consequence. It’s forged through repetition, failure, and the feedback loops of reality. It’s what operators, designers, and founders build by running enough experiments to know — almost subconsciously — what will probably work.

At its core, empirical taste is pattern recognition with emotional confidence.

It’s the ability to recognize what “feels right” because you’ve internalized the patterns of proportion, timing, and response. A person with good empirical taste isn’t necessarily more creative — they’re just better calibrated.

All of them are different dialects of the same language: prediction through pattern.

I’d argue this is slightly different to judgement. Judgment is the output — the conscious act of choosing A over B, approving one direction, rejecting another.

Taste is the underlying calibration that makes that choice feel right before you can explain why. Taste is fast, subconscious, emotionally weighted. “this layout feels off”.

Today I want to dive into empirical taste.

The Apprenticeship of Feedback Loops

Taste compounds through feedback loops.

Every cycle — build → test → learn → adjust — sharpens intuition.
You can’t develop taste in a vacuum; you need friction, feedback, and consequence.

You need tight loops that connect what you felt would work to what actually happened.

That loop is how taste becomes judgment.
At first, you’re guessing.
Then you’re sensing.
Eventually, you’re predicting — and your predictions start to sound like confidence.

Corporate environments kill this process with delay.
You ship, you wait three months, and by the time the data arrives, the intuition that birthed it has expired.

Startups compress time. You test daily, learn fast, and each iteration etches a new micro-rule into your brain. Taste becomes instinctive.

If you zoom out far enough:
Empirical taste = the number of feedback cycles survived.

Translating Gut Feel

I often think the real magic isn’t just knowing what is right but translating that intuition it into reality.

When I tell our design lead, “the layout feels too uniform — nothing pops,” she instantly knows how to turn that into reality.

Or if I say, “the text isn’t popping — I’m skipping over the headers,” she somehow fixes it in a way I couldn’t have articulated if I tried.

And every time, I’m left thinking, oh damn — that’s exactly what I meant.

When someone says, “it feels off,” what they’re really doing is subconsciously comparing against hundreds of prior patterns — hierarchy, pacing, emotional temperature.

Data Isn’t the Enemy of Taste — It’s the Training Data

People love to pit intuition against data. It’s a false dichotomy.

Data doesn’t kill intuition — it trains it.

Every A/B test, campaign, and post-mortem adds another weight to your internal model.Over time, those weights turn into instincts.

That’s what empirical taste really is — intuition trained on enough examples to stop needing dashboards. (Though you should still use dashboards!)

You don’t abandon data; you absorb it.
You start to feel the numbers before they arrive.

That’s not arrogance — it’s calibration.

The difference between superstition and mastery is that one’s been trained on truth.

Closing Thoughts

Empirical taste isn’t mystique — it’s mileage.
It’s intuition sharpened by exposure and consequence.

You don’t get better taste; you get faster feedback.
And over time, the feedback moves inside you.
You might measure less and start feeling — because you’ve earned the pattern.

Until next time,

Ajay

🧠 Ajay’s Resource Bank

A few tools and collections I’ve built (or obsessively curated) over the years:

• 100+ Mental Models
  Mental shortcuts and thinking tools I’ve refined over the past decade. These have evolved as I’ve gained experience — pruned, updated, and battle-tested.

• 100+ Questions
  If you want better answers, ask better questions. These are the ones I keep returning to — for strategy, reflection, and unlocking stuck conversations.

• Startup OS
  A lightweight operating system I built for running startups. I’m currently adapting it for growth teams as I scale Superpower — thinking about publishing it soon.

• Remote Games & Activities
  Fun team-building exercises and games (many made in Canva) that actually work. Good for offsites, Zoom fatigue, or breaking the ice with distributed teams.

✅ Ajay’s “would recommend” List

These are tools and services I use personally and professionally — and recommend without hesitation:

• Athyna – Offshore Hiring Done Right
  I personally have worked with assistants overseas and built offshore teams. Most people get this wrong by assuming you have to go the lowest cost for automated work. Try hiring high quality, strategic people for a fraction of the cost instead.

• Superpower – It starts with a 100+ lab tests
  I joined Superpower as Head of Growth, but I originally came on to fix my health. In return, I got a full diagnostic panel, a tailored action plan, and ongoing support that finally gave me clarity after years of flying blind.
  (Want a discount code? Just reply to this email.)