Cryptobro
677 posts

Cryptobro
@Cryptobro123
The greatest transfer of wealth is here, secure your financial freedom #BuyBitcoin $trench
Katılım Kasım 2024
148 Takip Edilen50 Takipçiler
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This would have been a 100m memecoin runner in 2024
New York Post@nypost
Squirrels are 'vaping' e-cigarettes after mistaking fruity aromas for food trib.al/IvZIB0D
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@Palgrani2 6JhpWAPCa4DXA67mfWznfqQFq1SpMwes65kH6Xmupump
$research
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The NRKT foundation is laid. I'm in the rapid improvement iteration phase where I'm having AI agents decimate my backlog of improvements in parallel to bring you all the best product. Case in point: Narrative Mode. It tells you exactly "what's happening, why there is/isn't a trade, what needs to change for there to be a trade".
The difference between me and other "devs" on SOL: when I was 8 years old, I wanted to be a software engineer. When they were 24 years old, they wanted to get rich quick and scam you.
This has been one dev for 90% of the entire TrenchBuddy project. Fuck your "I need an entire team to do shit because the guy who codes couldn't possibly write a coherent post or speak eloquently" and so on and so forth. That's cope, and the fact that $TRENCH is one of the sole survivors from the 2024 AI memecoin bubble proves that.

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Remember when "DefAI" tokens like Neur that weren't even real products went to mid-10 figures? Imagine one that's actually had a real, battle-tested product for over a year (TrenchBuddy.io) and is about to launch the best $HYPE perps trading bot in the game: Agent Neverekt.
That's $TRENCH. TrenchBuddy.com.

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Agent NRKT = Neverekt.
You know the drill:
• Stare at charts 24/7
• Second-guess every entry
• Wake up to liquidations (let's be real, you couldn't even fall asleep)
• Get rekt in volatile chop
We built the AI you wish existed:
✦ Ensemble consensus (ML + Vision + LLMs)
✦ Reads charts like TrenchBuddy
✦ Executes only when models align
✦ No action when signals conflict
✦ Enters, exits, and monitors your trades 24/7, with per-user server allocation for low-latency execution
Discipline > FOMO.
Never get rekt again.

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NRKT. Powered by $TRENCH. This is what production-grade AI trading looks like.
ChronoScope — multi-timeframe candles aligned on ONE timeline. Not multiple charts you have to flip back and forth; one unified view. When timeframes agree, you see ★. Click any candle for the full breakdown.
Structure Sniper Map — a live orb tracking price against key levels. Watch it move. See distance to support/resistance update in real-time. Know exactly where you stand.
Reclaim/Sustain LEDs — momentum indicators per timeframe. All green = locked in. Mixed = the AI probably said no.
Titan Verdict — not a black box. The AI's full reasoning. Why it approved. Why it vetoed. What concerns it flagged. Completely auditable.
Auto execution on $HYPE.
But this isn't yet another failed "dump a bunch of candlestick data into an LLM and make it trade with a tool call" experiment. Because the AI doesn't generate the signals. Why is that important? It means the AI doesn't make anything up.
We learned what LLMs are good at and what they're not.
Good at: Synthesizing signals. Pattern recognition. Explaining decisions.
Bad at: Arithmetic. Consistency. Not hallucinating numbers.
So we constrained it.
The AI receives a Trade Lock — direction and key price levels, both immutable. The quant already decided.
It gets a Risk Envelope — hard constraints it must obey along with general market conditions and considerations.
It selects from one of several Candidate Sets — entry/stop/TP options that are pre-computed after heavy reasoning that includes multimodal input in the form of charts and other data.
It's not biased by numbers because it doesn't ever see numbers. We map numbers to IDs so the LLM remains neutral. It picks "E0" or "S0", not "$95,420."
❌ Can't flip direction
❌ Can't invent prices
❌ Can't do math
❌ Can't veto on vibes
✅ Selects from validated options
✅ Explains every decision with extended CoT reasoning.
By constraining the AI to selection, not creation, we get some impressive results:
• Approved signals (signals that were generated and approved based on quant/hard math and approved by LLM)→ 85.7% win rate
• Vetoed signals (signals that were generated and approved based on quant/hard math and rejected by LLM) → 24% win rate, meaning you were smart to stay out.
At first, it was concerning that the LLM blocked 40% of signals that made mathematical sense, but it turned out it was making the right decision.
Quantitative algorithms are good at math. LLMs are good at synthesizing multiple signals, making connections across contexts, reasoning about trade quality and pointing out caveats. And with NRKT, there is no need to pick one or the other; you have the best of both, working together.
Full audit trail on every run. This is deterministic-first AI trading.
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When the market went from 'up only August' to...what it is now, many of the approaches that worked with LLMs just...stopped working. I was never naive enough to 'hand the reins over' to the LLM as many other trading experiments have done, but it turns out that every step involving an LLM essentially required a check or backstop.
This realization required yet another look at our trading architecture.
Hundreds of failed experiments. One brutal realization:
The more freedom you give an LLM, the more ways it finds to screw up your trades.
Here's how we fixed it. 🧵
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@nicrypto $trench @TrenchBuddy, never stopped building.
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