Taste Is the Bottleneck Now
AI can make more content than ever. The hard part is knowing what is worth publishing.
I turned a 10-minute interview into a full content package.
Two short clips. One longer compilation. Three new b-roll clips. A LinkedIn carousel. LinkedIn and Instagram drafts ready to schedule.
The tool cost was about a dollar.
That sounds like the story.
It is not.
The real story is this: AI made the work cheap. Taste made it useful.
AI can make the pile bigger
Most people still talk about AI like the hard part is getting output.
It is not.
Output is easy now. You can get captions, clips, images, posts, carousels, and drafts from one source file. You can make more in one afternoon than a small team used to make in a week.
That is powerful.
It is also dangerous.
Because more content does not mean better content. It can just mean more noise.
If you hand AI a video and ask it to make clips, it will make clips. It will not always know which moment matters. It will not know which pause makes the point land. It will not know which sentence makes a coach think, “That is me.”
That is still your job.
The new role is director, not editor
The old role was editor.
Cut the video. Pick the music. Add the captions. Export the file.
AI can now do a lot of that.
The new role is director.
A director asks better questions:
- What is the real idea in this clip?
- Who needs to hear it?
- What should they feel in the first three seconds?
- What should be cut because it weakens the point?
- What visual makes the idea easier to understand?
That is taste.
Taste is not being fancy. Taste is knowing what belongs and what does not.
A practical example
In the project I just finished, the AI could generate b-roll.
But the first versions felt like moving photos. Nice camera motion. Pretty lighting. No life.
The fix was simple.
Use verbs.
Instead of asking for “a person in an office,” ask for “a person leaning forward, exhaling, and closing a laptop.”
Instead of “a coach thinking,” ask for “a coach pulling a notebook from a shelf, pausing, and writing one line.”
The cost was the same.
The quality changed completely.
That is the point. The AI did not need a better model. It needed better direction.
The practical rule
Here is the rule I would use for any AI content pipeline:
Never let the expensive step happen before a human reviews the cheap step.
For video, that means review the still image before animating it.
For writing, review the outline before asking for the full draft.
For a carousel, review the slide idea before designing all five slides.
For a product, review the plan before writing code.
This saves money, but that is not the main reason.
It protects taste.
It gives you a chance to stop the wrong idea before the machine makes ten versions of it.
What coaches and creators should do
If you have a podcast, webinar, or client teaching session, do not start by asking, “How many clips can I make?”
Start here:
- Find the one sentence that makes the clearest point.
- Ask what belief it challenges.
- Turn that into one strong post.
- Then make the video, carousel, and email from that idea.
One sharp idea can become five useful assets.
Five weak ideas become clutter.
The hidden tax
The hidden tax of AI content is not the tool bill.
The tool bill is cheap.
The hidden tax is publishing things that make your audience trust you less.
Every weak post teaches people to ignore you. Every generic clip trains them to scroll past. Every AI-looking carousel makes the next one harder to earn attention for.
That is expensive.
The better way
Use AI to make the work lighter.
Do not use it to avoid judgment.
The future of content is not “AI makes everything.”
The future is this:
AI handles the production.
Humans handle the taste.
That is a better job anyway.