u/The_AI_Trader

quick follow up to my last post since a bunch of you asked specifically about EURUSD. ran the system live for 60 days, 183 sessions, 14 trades. 64% TP1 at 1.1R, 57% TP2 at 1.7R, 43% TP3 at 2.5R.

the part i actually want to talk about is how the macro and trend agents feed into the EURUSD-specific trader. macro agent runs the desk view. DXY direction, session bias, what oil/gold/VIX are saying, what came out of the london/NY handoff. trend agent runs pure structure on EURUSD itself, the CMT array, VWAP behavior across sessions, where the session high/low is sitting relative to the prior day, and has access to the macro agent output. neither one calls the trade. they hand a packaged read to the EURUSD trader and the trader builds the thesis from scratch each session.

strategies aren't hardcoded. the trader builds the play based on what the agents handed it, volatility, liquidity, momentum structure, session conditions. so in theory every trade should look different. in practice there's a pattern and it's been bugging me.

across the 14 trades it keeps converging on three setups. pullback into trend after VWAP reclaim. fade the session high into prior-day resistance. mean reversion off session support when macro reads flat. not exotic, textbook desk patterns. brilliant in the sense that a seasoned trader would nod at all three. but i didn't tell it to prefer them. it found them on its own from a much wider menu of plays it could have built. i keep going back to the journals trying to figure out if it's converging because those three actually fit EURUSD's character at this volatility regime, or because something in the agent handoff is biasing it toward mean-reversion-flavored structure. honestly don't know yet.

the other thing i'm sitting with is the rejection rate. every session the agents produce roughly 1.8 setups on average, so across 183 sessions that's somewhere around 330 candidate trades the system built and monitored. only 14 made it through to execution. that's a 96% rejection rate against considered setups, or about 92% against sessions. that's not the trader being lazy, it's the trader being patient. it builds the thesis, watches conditions evolve in real time, and waits for the confluences to actually line up. if they don't, the setup expires. control like that was the thing i wasn't sure an LLM could hold session after session.

not going to dump the full conflict resolution logic in this post for length, but the short version is the trend agent sees the macro agent's read before it builds its own. one-way visibility. trader sees both and gets to weight. all of it running on live real-time data, full CMT indicator array (RSI, MACD, ATR, VWAP, session H/L, S/R, fibs across 5m/15m/60m), macro context (DXY, VIX, oil, gold, yields, ADD), built around the way a chartered market technician would actually frame a session. early data says the asymmetry matters more than i expected. ask away if you want to get into how the model logic is built inside.

4.7 only has 2 trades on it so i'm not calling that a comparison. ask me at session 300.

Looking for traders to give me feedback on an I've been devoloping for over 2 years.

It basically uses multi agentic AI models to trade on multiple markets. It's not an a set ALGO or strategy. The AI monitors the US market on specific assets for 2 hours, builds trading setups, filters for the more qualified ones, then monitors when the price goes in the entry zones, and then decides to take the trade or not. It usually takes around 5% of the trades it generates.

Just looking for overall feedback on the UI design. I have tried to simplify it as much as possible, but it's freaking trading. It's already a complex beast.

What I did work on is having a side bar, where the user can see the current stats of the AI trader . So it can see how many trades it has taken, and the win ratio per Take Profit level, and the total R per take profit.

The idea is for the users to monitor the performance, and assign risk accordingly. Then if the user wants, it can be connected via cTrader and MT5 to execute the trades as the AI gave it , with the 3 TP levels, and SL, automated.

Plus the user can see the full analisis, and interact with the model with additional questions. As well as seeing the AI Macro agents works, and the AI Trend agents work. And the model is queried with almost 50k of token data for analysis , plus the other agents output, so it can analize the particular instrument in depth.

If you guys have any feedback on the visual design, that would be great. I appreciate it.

today went 6 for 6 and honestly that makes me trust it less, not more. clean days are when i go looking for the leak.

quick context on the setup. i've got three agents doing prep work then handing off to an LLM for the actual call. one watches trend, one watches macro, one runs a CMT indicator array. the LLM doesn't get to invent entries. it sees what the agents produced, picks from a constrained set of options, and a lot of the time the right answer is just no trade. today it wasn't. EURUSD USDJPY GBPUSD all went short on pullbacks, then US30 US500 NAS100 on opening-impulse pullback logic. six TP1 hits.

the part i keep poking at is what happens when macro and trend disagree. right now i just default to flat. macro says one thing, trend says another, no trade. keeps me out of the chop and i think that's correct most of the time. but i've definitely watched a clean trend setup go exactly where it should have while i sat there because macro was throwing noise. the US30 short almost didn't fire today for that reason.

so i guess the question is whether anyone running something similar actually solved that. hard veto, some kind of weighted score, or do you just let the model arbitrate and live with it. i've been scared to let it arbitrate.

other thing i'm curious about, does constraining the decision menu but leaving the reasoning open match what other people found. that combo has worked better for me than a rigid checklist but n is small.

six green days is six green days. i care more about session 300 than session 6. if you've run an LLM-in-the-loop system past the point where it stops feeling exciting, what was the first thing that went wrong.

***EDIT

edit since a few people asked for more implementation detail:

It’s a multi-agent setup. one agent handles macro context for the session/day trade, another focuses only on trend regime + strength, and another watches execution/risk conditions.

The main model gets all of that context together and reasons from there. the strategies themselves aren’t hardcoded. it builds the trade thesis dynamically depending on volatility, liquidity behavior, momentum structure, macro alignment/disagreement, session conditions, etc.

The important part is that it also self-monitors conflict. a decent percentage of outputs are just no-trade because the agents disagree or conditions don’t look clean enough. Close 90-95% of the setups are rejected, and not taken.

the trend agent is intentionally sees the macro agent output, and all of the data. Which is a full array of CMT indicators, which a professinol day trader would use, plus market context data, etc. The main model, also gets all of this technical info . (RSI, MACD , ATR, VWAP, Session h/l, Support - Resistance levels, FIBS, over 5min 15min 60min candles in a 5 hour vecinity , daily aggregate info of OIL, GOLD, ADD, VIX, DXY, ). Basically modelling a professional day trader workflow, with access to a rich risk and macro desk.

everything gets journaled with the full agent outputs + reasoning chain because i care a lot more about reviewing failures and consistency over hundreds of sessions than posting one clean day.

Feel free to ask.