I want to share something practical from live trading that builds on my previous post about XAUUSD and my workflow:
https://forexsb.com/forum/topic/10057/building-robust-eas-on-xauusd-a-structured-workflow-that-works/

This is not about building strategies, but about what happens after they go live and start interacting with each other.

I currently run a group of EAs (for example magic numbers 628, 165, 712 and others).

Most of these robots were built in 2024 in the same week using EA Studio.

They all use different indicators, logic, and entry conditions, so they are not identical strategies.

Over time, and especially once these robots were exposed to real portfolio conditions, I noticed something important.

To be honest, I was not really paying close attention to exposure on the demo accounts in that way.

The reason is simple: at that time I was running 70+ XAUUSD robots per demo account, so having 20 or 30 trades stacked at the same time was normal in that phase.

On demo, I mainly used them to observe broader behavior, metrics, and consistency.

But live is different.

Fewer robots, real money, real sizing, real conditions, and real emotions.

That is where the portfolio-level exposure becomes much more real.

Even though they are different, in live conditions they often open trades around the same time

This does not always happen in exactly the same way.

For example:

628 often opens first
284 (a variation of 628) often opens around the same time, but not always
165 sometimes follows later, but not consistently
712 often aligns with 165 or enters slightly after

So there is overlap, but not identical behavior.

Sometimes only one robot enters, sometimes multiple, sometimes they stack.

At first, this did not seem like a problem.

Individually, the strategies were solid.

They showed consistent behavior across:

EA Studio backtests
MetaTrader tick data backtests
demo trading
live trading

The patterns were very similar across all stages, which is a strong confirmation.

The real issue appeared at the portfolio level.

Because I was running around 8 robots together, all using relatively wide stop losses and no fixed take profit (mostly indicator exits or SL), exposure could build up.

Even with small lot sizes, the combined drawdown can still become significant if multiple robots are in the market at the same time and all use very wide stop losses. That was the real issue. A 0.02 lot size sounds small, but with an extremely wide SL, the loss can still go above 1000 euros if that stop gets hit. So if the market moves against me while 8 positions are all exposed in the same direction, the total exposure becomes too large. That is exactly why I had to interfere against my normal rules and use partial closes, not out of panic, but simply to protect the account.

That is when I started thinking differently.

Instead of rebuilding strategies, I focused on structure and risk.

I asked myself:

what happens if I reduce stop loss and rebalance position sizing?

So I went back and tested each robot individually in MetaTrader using tick data.

I adjusted stop loss values and observed how each robot behaved.

Once I found stable levels, I increased lot sizes accordingly.

This change made a big difference:

the robots started taking more losses, but those losses became smaller and more controlled
when they catch a move, they ride the trend as long as possible
because of that, winning trades have a much stronger impact
overall performance improved significantly

The strategies themselves did not change, but their efficiency inside the portfolio improved.

Another important step was creating variations.

For example:

Robot 628 mainly opens buy trades, with occasional reverse trades depending on the logic.

I used that idea to create a variation (robot 284):

628 → mainly buys
284 → both buys and sells

They are structurally similar, but behave differently.

Sometimes they enter together, sometimes only one enters.

This creates variation instead of full overlap.

On top of that, I added a take profit to robot 284 based on historical behavior.

This allows it to secure gains earlier, while other robots continue running without TP.

So instead of all robots behaving the same, they now complement each other.

At the moment, I run these robots across multiple accounts with different risk profiles (some more aggressive, some more conservative).

What I observe is that they consistently participate in strong movements on gold.

They are not perfect, but they behave in line with expectations.

The main lesson for me is this:

Building good strategies is one step.

Understanding how they behave together in live trading is another level.

Sometimes the biggest improvement does not come from new strategies, but from managing existing ones better.

To make this more concrete, I am sharing a few real examples from my main live account.

Robot 628:
- one screenshot shows the earlier phase, from March 2025 to September 2025, when it was still running with lower lot sizes and wide sl
- another screenshot shows the transition phase, which started around early December, when I began adjusting the structure and increasing lot sizes after testing

Robot 284:
- this is the variation of 628, with both buy and sell behavior and a different role inside the portfolio

I also included a real example of partial closes when exposure became too heavy.

These screenshots do not show the full stack of all robots, but they do show the kind of live behavior that led me to rethink the overall portfolio structure.