GIRL IF YOU DON’T GET THAT THING OFF YOUR SCREEN AND BACK IN MY SOCK DRAWER 😭
I SWEAR TO GOD I LEAVE Y’ALL ALONE FOR FIVE MINUTES AND NOW IT’S TRADING STOCKS
GIRL IF YOU DON’T GET THAT THING OFF YOUR SCREEN AND BACK IN MY SOCK DRAWER 😭
I SWEAR TO GOD I LEAVE Y’ALL ALONE FOR FIVE MINUTES AND NOW IT’S TRADING STOCKS
THIS IS TOTALLY DANGEROUS.
Someone just built GROKTOPUS.
8 AI agents running a trading floor. Each has a different brain:
↳ Executes
↳ Calculates fair value
↳ Analyzes sentiment
↳ Scans markets
↳ Checks liquidity
↳ Controls risk
↳ Covers exposure
↳ One liquidates
Before any trade, the swarm votes. 76.8% consensus required.
If it drops below 70%, the system stops.
This morning alone:
$150,000 → $198,850.06
1,981 trades.
8 markets.
IT'S EIGHT SPECIALISTS FUSED INTO A SINGLE ORGANISM.
The human didn't trade but built the floor.
Apparently we need a tutorial for this now. 😂
If a post made you laugh, taught you something, or made you comment “BRO THIS IS 🔥”…
You are allowed to show the other villagers.
Find the two little arrows. Press them. Select Repost.
Training complete. 🔁
LET’S CLEAR A FEW THINGS UP. 💅
Yes, I code.
Yes, the beard is real.
No, I’m not shaving it. That’s my senior developer experience.
I spent months building apps and sharing my work. The algorithm gave me 12 views and a crypto scammer.
So I made a small branding adjustment.
Anyway, I’m Jessica.
Same developer. Better hair. Suddenly everyone wants to collaborate.
@Chris73ai No growth strategy??
Chris, I’m out here pulling 80K views by existing and you’re “chill maxxing.”
Lock in babe, Jessica’s coming for New Zealand. 💅😂
Jev, explained without the launch-week noise.
Most of what your AI does all day isn't writing. It's choosing.
Which bucket does this go in. Is this urgent. Does this need a person. Is this chunk relevant. Which tool next.
None of those are writing tasks. They're choices, and you've been paying a model to write out its choice in a sentence so your code can read the sentence back and figure out what it picked.
Jev skips all of that. It doesn't write anything. You hand it some text and a question with the answers already drawn, and it points at one.
Three kinds of questions, that's the whole thing:
Pick one from a list you wrote. Up to 255 options, and it cannot invent a 256th.
Rate it on a scale you defined. Two to ten levels, and you describe what each level actually looks like instead of saying "rate urgency 1-10."
How likely is this true. A number between 0 and 1.
Every answer comes back with a confidence number attached, which matters more than the answer.
Why it's fast is the part worth understanding. A normal model builds its reply one word at a time, and that's where nearly all the cost and all the waiting come from. Jev reads your text once and answers every question at the same time. Which means the tenth question costs almost nothing extra.
So the move isn't asking it one thing. It's asking it everything you might want to know in a single shot, including the answers you'll throw away.
Where it earns its keep:
Sorting. Support tickets, inbound leads, email, anything where the buckets are already known. Somebody ran 18,514 emails through it cold, no training data, and got 98.33% on spam for about a dollar.
Filtering before something expensive. Score your search results for relevance before you stuff them into a big model. Score the lead before you spend a call on it.
Checking after. Did this answer actually address the question it was given. Does this quote appear in the source. Cheap to ask, and it catches the failures you'd otherwise find next week.
Deciding whether a human is needed. Under 0.5 confidence, escalate. Above 0.85 before anything you can't undo. Branch on the confidence, not the answer.
Now the honest half.
It's text only. No images, no audio.
It's bad at math, counting, and dates. Keep anything where the answer is a precise number in your code.
It can't explain itself. There's no reasoning to read, which is fine for routing and rough if you ever have to justify a decision to somebody.
And it can't refuse. Hand it a question it has no business answering and it answers anyway, in the right format, with a confidence number on it. A wrong answer looks exactly like a right one. That's the real tradeoff, and it's not in any benchmark.
It also loses to frontier models on broad tests. Roughly 68% against 73-74% for the top tier. It wins on narrow, well-specified decisions, which happens to be most of what an automation does all day.
One more thing worth saying out loud. In the spam test above, a plain old TF-IDF classifier — a technique older than most of the people posting about this — scored 98.39%. It beat Jev by six hundredths of a percent. If you already have labeled data, the boring classifier is still undefeated. If you don't, that's the entire pitch.
If you want to try it, don't rewrite anything. Open one automation, find the single call that only picks something, and replace that one. Log the confidence for a week before you let it decide anything that matters.
I'm wiring it into my own multi-agent setup this week. Posting the numbers either way, including if it turns out I didn't need it.