ACrypto·

A LOOK BACK · MAY–AUG 2026

What the first three months showed

ACrypto lets an AI place the trades. After the first stretch — about 11k decision cycles and 154 finished trades — I sat down with the logs. This is the short version: what went well, what got weird, and what I am not ready to claim yet.

Data through 2026-08-11 Written 2026-08-13

Short version: It made money, survived a nasty drawdown, and the plumbing got a lot better. Sustainability is not yet proven — interesting sample, not a victory lap.

Equity change

+14.4%

Where the account ended up

Max drawdown

−24.1%

The ugliest stretch along the way

Completed trades

154

May–Aug 2026

Win rate

58.4%

A bit more wins than losses

01 / THE RIDE

How equity actually moved

If you only glance at one chart, make it this one. Trade-by-trade scorekeeping told a rosier story than the account curve — fees, partials, and bookkeeping gaps still need tidying.

02 / FAQ-ISH

Questions you might care about

Can it keep making money?

So far, yes-ish — but I would not call it proven. Finished trades looked pretty good (profit factor 2.83), while the account itself only climbed about 14%. Those two stories do not fully line up yet, so I am not treating the nicer number as gospel.

Was it mostly luck?

Not pure coin-flip luck. Dropping the best few trades still left the sample in the green, and 11 of 15 weeks were profitable. That said, a handful of symbols and a few big winners did a lot of the heavy lifting — so luck (or concentration) still matters.

Did all the strategy tweaks help?

The system got sturdier for sure: better risk rules, sizing, exits, and fewer silly failures. The P&L path was less tidy. The best stretch was an earlier round of risk tightening, not the latest “manage everything actively” version.

What am I working on next?

Less prompt tinkering, more boring-but-important stuff: cleaner trade books, clearer version tracking, and checks that hold up outside this sample. Until then, the honest take is: promising, not proven.

03 / BY MONTH

Most of the juice came early

Month Trades Return Win rate PF
2026-05 44 +51.1% 56.8% 5.60
2026-06 40 +34.1% 62.5% 2.27
2026-07 38 +17.8% 34.2% 1.84
2026-08 32 +6.9% 84.4% 11.07

Later months won more often, but each win got smaller. Feels less like “alpha exploding” and more like “take profits quicker, sleep a little better.”

04 / VERSIONS

Reliability improved more than returns

E1

Getting started

LLM calling more of the shots, wider coin list, simpler stop/take-profit habits.

26 trades · +13.8% · PF 4.11

E2

Rules + patience

Best stretch in this sample — clearer entries, less churn, nicer expectancy.

21 trades · +39.6% · PF 6.32

E3

Learning to short

Less long bias, more willing to fade when the market was ugly.

37 trades · +31.9% · PF 2.22

E4

Sessions & sizing

More engineer energy on when and how much to trade. Small sample, mixed results.

10 trades · +5.0% · PF 1.93

E5

Structure context

More support/resistance and ATR context. Also the soft patch in this review.

17 trades · −5.9% · PF 0.55

E6

Bigger-picture filters

Fear/greed, open interest, BTC daily context. Fewer trades, chunkier winners.

12 trades · +20.1% · PF 8.30

E7

Hands-on exits

Partial closes, trailing, faster risk loops. Lots of little wins, smaller average size.

31 trades · +5.6% · PF 9.16

These eras follow nearby code changes, not a perfect deploy diary. Markets changed too — so the best window is not automatically “credit the commit.”