Google Gemini vs No Doubles: Why Position-Based AI Misses the Point of Golf Improvement

When Google and Bryson DeChambeau released the Gemini swing analysis demo, most golfers had the same reaction: “Cool tech, but will this actually help me get better?”

And almost immediately, instructors and knowledgeable players began pointing out what the demo got wrong.

Lion Golf Academy summarized it perfectly with one line:
“AI sees the what, but never the why.”

They were not attacking AI. They were pointing out a truth the golf world keeps ignoring.

Labeling positions does not help golfers improve. Understanding causes does.

And that is where every model-matching AI system, including Gemini, falls apart.

The Real Problem Golfers Face (And Almost Nobody Talks About)

Golfers do not fail because they lack information.
Golfers fail because they lack clarity.

Our research, coaching interviews, and conversations with hundreds of golfers all pointed to the same frustrations.

1. Lessons give information, not transformation

Most golfers walk away with a few tips but no structured plan to ingrain the right pattern.

2. Advice contradicts itself

Different coaches use different priorities and language. The result is confusion.

3. Golfers practice incorrectly when they are alone

Without feedback, they reinforce the very flaws they are trying to fix.

4. YouTube wins because it is repeatable, not because it is better

Golfers rely on videos because instruction has not provided continuity.

None of these problems are AI problems.
They are instruction problems.
And AI that simply labels positions makes them worse, not better.

The Flaw With Pose-Based AI: It Measures What Does Not Matter

Gemini uses pose detection to compare your body positions to a reference model.

This is impressive on a technical level.
It is useless on a learning level.

Golfers do not get stuck because they do not look like tour pros.
They get stuck because they move differently due to:

• mobility
• age
• injury history
• personal swing DNA
• realistic biomechanical limits
• compensations created over time

A golfer who comes over the top does not have a path problem.
That is just the visible symptom.

The real cause might be:

• grip
• alignment
• backswing geometry
• pressure shift
• sequencing
• chest stall
• early extension

Pose-based AI cannot see any of that. It can only label the output.

Labeling flaws without understanding causes is noise disguised as insight.

Why Coaches Reacted Strongly to Gemini

Good coaches were not worried about being replaced.
They were frustrated on behalf of golfers.

Because coaches know what the demo did not show.

Golf improvement is emotional.
It is pattern-based.
It requires a progression, not a snapshot.
It depends on understanding why flaws appear under pressure.

Model-matching AI cannot do that.
It does not understand feel, fear, fatigue, or compensation patterns.

So coaches pushed back, not against technology, but against shallow solutions that pretend to be breakthroughs.

What Golfers Actually Need (And What AI Has Ignored)

Across all our research, the needs were consistent and clear.

1. One clear priority

Golfers need to know the one thing that matters right now.

2. Cause over symptoms

They need to understand why a flaw is happening, not just what the flaw is.

3. A drill that corrects the real issue

Not a tip. Not a position. A corrective pattern.

4. A progression that builds a real skill

Golfers need stage-by-stage guidance, not isolated advice.

5. Feedback when practicing alone

They need reinforcement so they do not slip back into old patterns.

This is what golfers are asking for.
This is why AI tools have felt gimmicky.
This is why the Gemini demo created skepticism.

Golfers are not resisting technology.
They are resisting noise.

What No Doubles is Actually Building (And Why It Is Different)

We are not building another pose-matching tool.

We are designing a system that gives golfers something AI demos have never delivered.

A clear, root-cause path to real improvement.

Here is what that looks like.

1. No Doubles identifies the cause behind the flaw

We do not stop at “you are over the top.”

We ask what broke first, what is upstream, and what pattern the golfer is compensating for.

If you do not fix the cause, the flaw always comes back.

This is exactly where Gemini-style AI fails.

2. Every cause maps to a drill that changes the pattern

Not a tip.
Not a position.
A correction based on how humans actually learn skills.

Motor learning research is clear.

Concept
Feel
Repetition
Reliability

So we are designing No Doubles around that exact sequence.

Flaw to cause.
Cause to drill.
Drill to progression.

A system, not a highlight reel.

3. No Doubles provides a daily improvement plan

Golfers do not want insights.
They want direction.

What to work on today.
How many reps.
What success looks like.
When they are ready to move on.

We remove the guesswork that ruins practice sessions.

4. No Doubles complements great coaches, not replaces them

AI handles consistency, root-cause clarity, and daily accountability.
Coaches bring nuance, feel, motivation, and emotional connection.

We are not eliminating humans.
We are eliminating confusion.

The Truth

Lion Golf Academy captured the core issue with a single line.

“AI sees the what, but never the why.”

That is true of Gemini and most AI swing tools today.

No Doubles is being built to show the why.

We explain the cause behind the flaw.
We map it to a drill that creates real change.
We guide golfers through the stages of learning.
We give everyday golfers clarity and confidence instead of confusion.

Golfers do not need another tech demo.
They need a system that helps them improve.

Gemini shows the what.
No Doubles shows the why.

And that difference is what moves golfers forward.