When Intelligence Becomes a Commodity, Judgment and Taste Become the Moat

How to develop judgment and taste in an autonomous world and how to guide the next generation through it.

I keep coming back to this question as a leader, but even more as a father:

What do I need to teach my son if he is growing up in a world where intelligence is everywhere?

Not wisdom. Not character. Not lived experience. But a large category of what once felt rare — fluent writing, fast synthesis, basic analysis, code generation, research summaries, design variations, tutoring, planning, translation, and first-draft strategy — is becoming abundant.

Autonomous systems will make this shift even more dramatic. They will not merely answer questions. They will take goals, break them into steps, coordinate tools, produce work, measure results, and improve through feedback.

The cost of generating options will fall.
The cost of producing drafts will fall.
The cost of sounding smart will fall.

That changes the game.

For much of the modern knowledge economy, intelligence was a differentiator. The person who could analyze faster, write cleaner, search better, remember more, or produce more had an advantage.

Those advantages will not disappear, but they will compress. When everyone can summon a competent analyst, copywriter, tutor, designer, and junior engineer on demand, the scarce capability moves up the stack.

The question will no longer be: Can you produce?

The question will be: Can you judge what is worth producing?

And just as important: Can you recognize what is good?

That is judgment and taste.

Intelligence gives you answers. Judgment tells you which answers matter.

Intelligence is the ability to process, infer, generate, and solve. It can move quickly across a problem space. It can produce plausible paths.

Judgment is different.

Judgment is knowing what matters in context. It is the ability to weigh trade-offs, consequences, timing, second-order effects, incentives, human realities, and risk.

Judgment asks:

• What problem are we really solving?
• What is the cost of being wrong?
• Who is affected?
• What are we assuming?
• What evidence would change our mind?
• What should not be automated?
• What is technically possible but ethically careless?
• What is impressive but irrelevant?

Autonomous AI will increase the number of possible actions. Judgment decides which actions deserve permission.

That is why judgment becomes more valuable as systems become more capable. The more leverage a tool gives you, the more consequential your choices become.

A weak decision amplified by automation is not weak anymore.

It becomes operational reality.

Taste tells you what good looks like before the metrics catch up.

Taste is often misunderstood as style or preference. But real taste is deeper than that.

Taste is trained perception. It is the ability to notice quality, coherence, elegance, emotional resonance, and fit before a dashboard proves it.

Taste sees the difference between something that merely works and something that is right.

In an AI-saturated world, taste matters because average output will become cheap. Good enough will be everywhere. Templates will be polished. Copy will be grammatically correct. Designs will be plausible. Code will run. Strategies will sound sophisticated.

But plausibility is not excellence.

Taste lets you reject work that is technically acceptable but strategically weak. It lets you see when a product is overbuilt, when a sentence has no soul, when a design lacks hierarchy, when a business idea is clever but not durable, and when a child’s education is optimized for performance but starved of character.

Taste is how we keep humanity in systems that can generate endlessly.

The new divide: people who can prompt vs. people who can decide

The first wave of AI adoption put a lot of attention on prompting.

Prompting matters, but it is not the final skill.

Prompting is how you ask the machine to move. Judgment is knowing where it should move. Taste is knowing whether the result is worth keeping.

The durable advantage will belong to people who can:

1. Frame meaningful problems.
2. Set standards before generating output.
3. Evaluate work with clarity.
4. Make decisions under uncertainty.
5. Accept responsibility for consequences.
6. Refine raw intelligence into something useful, beautiful, ethical, and true.

In other words, AI will reward people who know what they want and why.

That is the human moat.

Not access to intelligence.

The ability to direct it.

How to develop judgment

Judgment is not a personality trait. It is trained through exposure, reflection, and consequence.

1. Build a library of real decisions

Read biographies, company histories, military history, science history, case studies, and postmortems. Do not read only for inspiration. Read for decision patterns.

Ask:

• What did they know at the time?
• What were they wrong about?
• What constraint mattered most?
• What incentive distorted the decision?
• What would I have done?

The point is not to memorize stories. The point is to build a mental library of trade-offs.

2. Keep a decision journal

Before important decisions, write down:

• The decision.
• The options.
• Your assumptions.
• The evidence.
• Your confidence level.
• What would make you change your mind.
• The expected outcome.

Then revisit it later.

This is uncomfortable because it removes the ability to rewrite history. But that is precisely why it works. Judgment improves when you can compare your past reasoning with reality.

3. Seek consequence, not just opinion

Advice is cheap. Consequence is expensive.

Spend time with people who have lived with the outcomes of their decisions: founders, operators, parents, builders, investors, teachers, doctors, engineers, coaches, artists.

Notice how they think. They usually speak differently than commentators because they know where reality pushes back.

Good judgment comes from contact with reality.

4. Separate reversible and irreversible decisions

Not all decisions deserve the same weight. Some are experiments. Some are commitments. Some are reversible. Some are not.

Autonomous tools can make it dangerously easy to act quickly on decisions that should be slow.

Train yourself to ask: If this goes wrong, can we undo it? Who bears the cost?

Speed is powerful when the downside is bounded. It is reckless when the downside is hidden.

5. Practice saying no to plausible ideas

AI will produce endless plausible ideas. Many will be decent. Most should not be pursued.

Judgment is often subtraction. It is choosing the few things worth attention and letting the rest go.

If you cannot say no to a good idea, you cannot protect a great one.

How to develop taste

Taste develops through immersion, creation, comparison, and revision.

1. Study excellent work until your standards rise

If you want taste in writing, read great writing. If you want taste in product, study great products. If you want taste in architecture, study great systems. If you want taste in leadership, study great leaders.

Do not only consume summaries. Spend time with the original work. Notice structure, pacing, restraint, tension, clarity, and detail.

Taste requires examples.

2. Compare versions

Take an AI-generated draft and create three alternatives. Then ask: which is strongest and why?

Do this with headlines, product flows, lesson plans, strategy memos, images, code structure, and arguments.

The act of comparison trains perception. You begin to see the difference between generic and specific, clever and useful, polished and powerful.

3. Make things with your own hands

Taste cannot be outsourced entirely. You develop taste by making, failing, revising, and feeling the gap between intention and execution.

Write the essay. Build the prototype. Cook the meal. Draw the sketch. Teach the lesson. Design the room. Plant the garden. Edit the video.

Embodied creation teaches what pure evaluation cannot.

4. Learn to remove

Average work often has too much. Too many words. Too many features. Too many colors. Too many claims. Too many priorities.

Taste often appears as restraint. The ability to remove what is unnecessary is one of the clearest signs of maturity.

Ask constantly: What can be removed without weakening the thing?

5. Protect attention

Taste requires attention, and attention is under attack.

If your mind is constantly fed by feeds, alerts, and algorithmic fragments, your standards become reactive. You start wanting whatever is most stimulating rather than what is most meaningful.

Deep taste requires quiet, boredom, focus, and sustained contact with difficult things.

What this means for our children

The deepest question is not how we use AI ourselves. It is how we raise children in a world where AI is always available.

This is where the topic stops being abstract for me.

I think about my 2 year old son. I think about the world he is going to inherit. I think about the tools that will be normal to him before he is old enough to understand their power. I think about how easy it will be for him to get answers, produce work, and sound capable.

And I worry about what could be lost if convenience arrives before character.

Children will grow up with machines that can answer questions, write essays, generate images, tutor math, compose music, and simulate conversation. The temptation will be to optimize everything: faster homework, personalized learning, instant feedback, frictionless creativity.

Some of that will be wonderful.

But if we are not careful, children may gain access to intelligence before they develop judgment. They may learn to produce before they learn to perceive. They may learn to delegate before they learn responsibility.

Our job is not to keep AI away from them forever.

Our job is to help them become the kind of people who can use powerful tools wisely.

1. Teach them to ask better questions

Do not reward only the right answer. Reward the better question.

Ask them:

• What are you trying to understand?
• What do you think before asking the machine?
• What might the answer be missing?
• How would you verify it?
• What would a wise person consider?

The child who can question well will not be easily controlled by fluent answers.

2. Make them do hard things without automation

Children still need friction. They need to memorize some things, practice some skills, struggle through some problems, and experience the pride of earned competence.

If AI removes every struggle, it may also remove the formation that struggle creates.

Let children write by hand. Let them do mental math. Let them read long books. Let them build physical things. Let them practice instruments, sports, chores, and crafts. Let them experience boredom long enough for imagination to wake up.

Convenience is not always kindness.

3. Teach AI as an instrument, not an authority

A piano can produce sound, but the musician must learn music. A calculator can compute, but the student must understand quantity. AI can generate language, but the child must learn truth, meaning, and responsibility.

Teach children to treat AI as a tool they direct, not a voice they obey.

A simple family rule might be:

Think first. Ask second. Verify third. Own the result always.

4. Develop moral imagination

The autonomous world will constantly ask: Can we?

Children must learn to ask: Should we?

Give them ethical scenarios. Talk about fairness, privacy, honesty, manipulation, courage, and care. When they use AI, ask who could be helped, who could be harmed, and what responsibility they carry for the output.

Judgment without ethics becomes calculation. Taste without ethics becomes vanity.

5. Expose them to beauty

Taste is not built only through productivity. It is built through beauty.

Take children to museums, concerts, parks, libraries, workshops, kitchens, studios, and places of worship. Let them see craftsmanship. Let them hear great music. Let them read stories that stretch their inner life. Let them spend time in nature where nothing is optimized for engagement.

A child who knows beauty has a defense against the merely addictive.

6. Model discernment yourself

Children will learn more from how we use technology than from what we say about it.

If we are constantly distracted, they will learn distraction. If we outsource every decision, they will learn dependency. If we treat AI output as finished truth, they will learn passivity.

But if they see us pause, question, revise, verify, and take responsibility, they will learn that powerful tools require mature users.

The human advantage moves upward

As intelligence becomes abundant, the human advantage does not disappear. It moves upward.

It moves from answer generation to problem selection.
It moves from output volume to quality of direction.
It moves from knowing facts to weighing meaning.
It moves from speed to consequence.
It moves from productivity to responsibility.

The future will not belong simply to the smartest people or the best prompt writers.

It will belong to those with the judgment to choose wisely and the taste to make work worth choosing.

That is the new education. For ourselves. For our teams. For our children.

Do not merely teach people how to use autonomous systems.

Teach them how to remain human while using them.

And for my son, that is the real goal.

Not that he can produce more than everyone else.

Not that he can sound smart in a world where sounding smart is easy.

But that he can choose well. See clearly. Love what is good. Take responsibility. And carry his humanity into whatever comes next.