last time I posted this here it was still pretty static (fixed entries, indicator voting, etc.)

since then I changed a lot under the hood and honestly the biggest shift wasn’t “more signals” — it was when the bot actually decides to enter

instead of forcing entries at a fixed point in the 15min window, it now continuously scores every moment and only fires when:

so it basically learned where the actual edge is inside the window, not just what direction

what changed technically:

moved from a simple classifier → hybrid CNN + LSTM (so it actually learns sequences instead of snapshots)
recency-weighted training (recent market behavior matters more than old patterns)
dynamic entry optimizer → no more fixed entries, it waits for high-quality moments
EV + risk-based sizing → trades get graded (A/B/C) and sized accordingly
regime detection → behaves differently in chop vs trend vs volatility spikes

what’s interesting:

the bot trades less now, but the trades it takes are way cleaner

early version was basically:

“see signal → take trade”

now it’s more like:

“wait → skip → wait → ok this one actually has edge”

mostly small consistent wins, a couple losses, but overall pretty stable behavior

nothing crazy, just clean execution

this is where it gets interesting — you can literally see it skipping setups until the score crosses a certain threshold

a lot of time it just does nothing, which turned out to be way better than overtrading lol

still early obviously and I’m not pretending this is some magic system, but it’s behaving way less “robotic” than before

curious if anyone else here moved from fixed strategies → more adaptive / ML-driven setups

btw I ended up calling the bot Polybread lol

been running a small Discord around this and we somehow already hit ~100 members which is kinda crazy to me

if anyone wants to check it out / test it / just talk about

always happy about anyone who joins and gives the project a shot — feedback has been super helpful so far

I’ll keep posting updates here as things evolve