Introduction

In the past, EA development was a specialized skill accessible only to a limited number of people.

By learning MQL, understanding MetaTrader’s specifications, and fixing errors, we could finally create an EA.

However, with the advent of AI, this premise is beginning to change drastically.

Nowadays, even people who cannot write code can have ChatGPT or Cursor generate a basic EA template upon request.

This is the democratization of EA development.

Yet democracy has its good and dangerous sides.

While more people can create, not everyone can create correctly.

People who can’t code can still create an EA

Before AI, EA development faced a major barrier: programming knowledge.

For example,

“buy when the moving average crosses upward”

Even such a simple logic required extensive knowledge to implement as an EA.

Retrieving the current price.

Retrieving MA values.

Front/previous bar assessment.

New entry control.

Position verification.

Lot calculation.

SL/TP settings.

All of these had to be implemented one by one.

But with AI, you can generate code by giving natural language instructions.

This is a major change.

We are moving away from an era where ideas stall due to lack of implementation power.

Value shifts from code to ideas

As AI becomes capable of writing code, the value of writing code itself decreases.

Instead, the value increases in ideas.

Which market to target.

Which time frame to view.

Under which conditions to enter.

Under which conditions to exit.

How to control drawdown.

What to validate.

The design of these aspects becomes more valuable.

In other words, EA development will shift from programming competition to hypothesis-design competition.

Democratization may lead to more low-quality EAs

However, just because anyone can create doesn’t mean anyone can create good EAs.

Missing this point can be dangerous.

AI can generate an EA that looks plausible.

However,

・Reasons it can win
・Conditions that cause it to fail
・Risk management
・Backtest validity
・Risks in live operation
・Accuracy of MQL

are not guaranteed.

Therefore, while AI creates a large number of EAs, there is also a possibility of a flood of poor-quality ones.

Democratization broadens the market.

At the same time, it widens the quality gap.

Skills that will become important from here

What becomes important in the AI era is not only the ability to instruct AI.

But also the ability to doubt AI’s output.

For example,

・Is this code correct as MQL5?
・Is old MQL4 syntax mixed in?
・Is the backtest result due to overfitting?
・Is the live-operation design safe?
・Is the money management sound?
・Does the expected value truly exist?

These verifications are necessary.

More people will have AI create stuff.

But only a limited number can judge what AI created.

That is where the gap appears.

What comes after democratization

First, AI makes EA development easier.

Next, a flood of EAs appears.

After that, there will be selection through elimination.

Working EAs.

Selling EAs.

EAs that survive for a long time.

EAs that endure in live operation.

These are separate things.

In the AI era, the market for EAs values longevity more than mere creation.

To achieve that, quality standards are necessary.

From MAEP perspective

MAEP does not deny the democratization of EA development through AI.

Rather, democratization is a natural progression.

However, if EAs are mass-produced without AI properly understanding MetaTrader, problems will increase.

Therefore, AI must be educated about MetaTrader.

Record misgenerated cases in the Error Database.

Show correct designs in Pattern30.

Organize reusable components in Component20.

Define generation rules with AI Rules.

This can bring AI-driven EA development closer to quality development rather than mere mass production.

✅Summary

AI will democratize EA development.

This is an inevitable trend.

A era will come when people who cannot write code can also create EAs.

But democratization is not a guarantee of quality.

Because anyone can create, the ability to judge quality becomes important.

What is needed in future EA development is not only the ability to use AI but also to supervise AI.

?CTA

The era of creating EAs with AI has begun.

However, simply leaving it to AI is not enough.

Teach MetaTrader correctly to AI.

Reduce erroneous AI generations.

Improve the quality of AI-generated EAs.

MAEP is a MetaTrader education package for that purpose.