Kyu 🇵🇸 @cryptokyu

FOUND A @NousResearch and @openclaw KILLER. FASTER AND CHEAPER THAN BOTH Saw this and had to test it myself: → Summarize my emails → The exact same prompt → Same inbox, same task Ran them side by side and the speed gap is wild. Plus OpenHuman shows you: → Your context window live → What each session costs After testing both on real work, @tinyhumansai - openhuman is my agent now.

Steven Enamakel 🐥 @senamakel

2 days ago

Why is @openclaw so damn slow for really simple things? 🤷‍♂️ A search query opens a full browser and over 10 mins?? Who tf designed that? OpenHuman is far more lightweight, consumes lesser RAM & CPU, and gives much faster results.

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this open-source agent harness is the #1 trending tool on GitHub right now. that’s because it beat OpenClaw and Hermes on efficiency. it’s built to be more lightweight, uses less RAM & CPU, and delivers results much faster. 🔗: github.com/tinyhumansai/o…

marcus @marcusyul

2 days ago

FOUND A @NousResearch and @openclaw KILLER. FASTER AND CHEAPER THAN BOTH Saw this and had to test it myself: → Summarize my emails → The exact same prompt → Same inbox, same task Ran them side by side and the speed gap is wild. Plus OpenHuman shows you: → Your context

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whoever built this realized we’ve been using our smartest AI for the dumbest possible jobs your $20-$200/mo frontier model is researching, writing code, planning… and then you’re paying the same brain to decide YES / NO. Jev flips that. it’s a tiny decision model that sits in front of the expensive stuff and handles the boring forks: -> which agent goes next? -> is this worth researching? -> reply or ignore? -> publish, wait or escalate? -> BUY / SELL / HOLD? -> click this or keep looking? then I saw the numbers people are reporting and the whole architecture started making a lot more sense. ~1,000 papers classified for around $0.08 ~500 emails sorted for around $0.035 browser-agent loops demonstrated around 7 seconds for ~$0.0039 and at the quoted pricing, roughly 10,000 ~1K-token decisions comes out around $0.42. that’s not because Jev became smarter than Claude. it’s because nobody asked it to be Claude. the setup is stupidly simple: -> big LLM gets the hard thinking, research and writing -> Jev gets the thousands of tiny decisions between those steps -> code actually clicks, saves, sends and executes and suddenly you start noticing these little decisions everywhere. > your inbox. > X feed. > support queue. > meetings. > leads. > video clips. > browser agents. > even paper-trading loops. that’s the part I think most agent builders are missing. the expensive model doesn’t need to touch every step just because it’s capable of touching every step. > let Claude think. > let Jev decide what deserves Claude. > let code do the actual work. I broke down 12 places you can wire this into an agent today + the exact router setup in the article below

kiosa @thegreatest_sv

2 weeks ago

x.com/i/article/2102…

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Basically.. kita bisa spend, send, trade, sampai grow aset kita langsung onchain dalam satu platform.. Bentar lagi launch nih @WieldMoney Udah makin deket ke early access 🤫

A time based stop loss is one of the simplest ways to improve your trading system's profitability I've written a full guide to teach you how to start using this:

Koroush AK @KoroushAK

5 months ago

x.com/i/article/2050…

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barusan nemu bot execute baru, mirip cove dengan perpaduan copyfomo, namanya @dawndottrade. fyi, sebenernya pernah dikasih tau cuman gw belum yakin dan masih nanya2 dulu terus abis nyoba, kayaknya nambah strat execute nih buat ngetrenching hehe. playbooknya: COVE = punya thesis tokennya DAWN = punya thesis ke wallet-nya Cove → conviction trade kalo token datang dari GMGN/Cielo/Fomo atau research sendiri, jangan lupa cek MC, liquidity, volume, holder, top-10 sama contractnya dulu. misal lolos, baru execute di Cove. Starting setting: Slippage 20% Liquidity Protection ON Auto Max Buy ON Price Impact Check ON Degen Mode OFF Buy/Sell Confirm ON Gas Surplus $3 Auto TP/SL ON SL -25% buat entry bertahap, gw prefer Limit/DCA/Ladder, misalnya $300 dibagi $100/$100/$100 daripada full entry di satu harga. Cove udahnyediain guardrail itu buat batesin liquidity/price-impact risk. Dawn → wallet copy nah, kalo alphanya datang dari wallet, inget jangan langsung copy. Track dulu 50–100 trade, misalnya nih: Win rate = 58% Avg win = +2R Avg loss = -1R Expectancy = (0.58×2) - (0.42×1) = +0.74R baru pake Dawn. buat early-meme wallet, starting filter yang gw pake: First Buy ON MC $50k–$500k Liquidity >$15k Volume 24h >$50k Holders >100 Top 10 <45% Age >5m Copy $25–$50 SL -20% TP +50% MEV Protection ON Dawn udah mendukung filter MC, liquidity, volume, holders, top-10, token age, fixed copy size sama Auto TP/SL. btw jangan lupa after 100 trade, lihat lagi filter mana yang beneran ningkatin expectancy. remember! jangan copy nominal whale ya (kecuali lu whale juga hehe) Leader buy $10k bukan berarti kita ikut $10k, kalo copy $50 dengan SL -20%: $50 × 20% = $10 = 1R jadi yang dicopy decision-nya, bukan ukuran modalnya. ada satu metrik penting di Dawn: namanya copy latency, kalo leader masuk $100k MC tapi kita baru masuk $120k, bisa jadi udah gak worth. jadi janga lupa track juga missed trade, entry deviation, slippage sama execution cost, Dawn punya mekanisme Copytrade Missed ketika harga udah melewati tolerance. rule-nya simpel aja sih: Punya thesis token? → COVE Punya edge wallet? → DAWN gak punya keduanya? → SKIP BOS! hehe Cove = control. Dawn = automation. keduanya tetap harus diukur dari net PnL + expectancy, bukan PnL wallet yang kita copy. kayaknya gue bakal pake keduanya + copyfomo, jadi ada 3 hehe. nih linknya: Dawn (My Second Choice): t.me/DawnTradeBot?s… Cove (Tetep My Jagoan): t.me/cove_trading_b… CopyFomo (My Alert): t.me/copyfomo_bot?s…

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Bot tracking wallet LP gua sekarang sudah selesai & siap di pakai !! Sudah support 2 chain: - Robinhood - solana Silahkan manfaatkan: t.me/beneraly_bot Diskusi & sharing: t.me/yallbyalert Semua gratis, gaada biaya apapun.. Sekiranya membantu dan profit, gua udah siapkan fitur donasi untuk support gua terus berkembang 🤝

Nemu strat LP yang dibahas @MeteoraIDN terus gua rangkum step by step nya jadi video biar lebih gampang dipahami !! Buat yang masih bingung alurnya cek video ini:

Gua seharian ngetest strat LP yg diajarin di @MeteoraIDN ini jirr 😅 ternyata beneran lebih cuan kek gini woii kan awalnya Sol side only nih, trus ngedump tuh sampe nabrak nabrak garis Bollinger band bawah + MACD udah merah merah tuh di tf 5m sama 15 menit nah setelah itu gua klik Manage → Withdraw → pas withdraw pilih yang token doang → buru buru klik tombol Add → masukin semua token yg di withdraw tadi → pilih Bid Ask nanti bentukannya langsung kek yg di gambar gua tuh ✅ exitnya serah dah gimana lu aja nyamannya, tapi gua pas nabrak garis BB atas biasanya

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btw ini artikel ini bagus sih, jadi dia menganalisis 100 wallet teratas di leaderboard PnL FOMO dengan total gabungan sekitar $141 juta. tujuannya mencari pola trading yang bisa direplikasi based data on-chain, jadi bukan sekadar meniru wallet yang lagi profit besar. so, ada lima temuan utama. 1. Frekuensi trading tinggi bisa menggerus edge. wallet dengan kurang dari 300 trade menghasilkan rata2 sekitar $4.162 per trade, sedangkan wallet dengan lebih dari 2.000 trade hanya sekitar $417. salah satu faktornya adalah biaya transaksi dan slippage sebesar 2–6% per round trip, semakin sering melakukan transaksi marginal, semakin besar akumulasi biaya yang harus ditutup oleh profit. artinya, seleksi setup dan expected value setelah biaya lebih penting daripada jumlah transaksi. 2. Popularitas menciptakan market impact. wallet dengan kurang dari 10 ribu follower menghasilkan rata2 sekitar $2.791 per trade, sementara wallet dengan lebih dari 100 ribu follower hanya sekitar $462. copy-trader yang masuk terlambat dapat mendorong harga entry, saat exit, penjualan serentak juga berpotensi memperbesar slippage. cuman, korelasi ini belum membuktikan bahwa keuntungan wallet populer berasal dari likuiditas pengikut, jadi perlu analisis arus order, waktu transaksi, dan harga eksekusi buat mastiin. 3. Win rate rendah tetap bisa menghasilkan profit besar. salah satu wallet hanya memenangkan 8 dari 30 trade, atau sekitar 27%, meski begitu, PnL-nya mencapai jutaan dolar. kuncinya adalah asimetri hasil: kerugian relatif kecil, sedangkan satu atau beberapa posisi pemenang menghasilkan keuntungan berlipat. secara matematis, strategi ini mengandalkan expectancy positif: E=(WinRate\\times AvgWin)-(LossRate\\times AvgLoss) resikonya, strategi sangat bergantung pada kemunculan beberapa posisi dengan return ekstrem, kalo token pemenang tidak muncul, rentetan kerugian dapat menggerus modal. 4. Hold panjang menjadi sumber keuntungan sekaligus risiko. di salah satu wallet, $3,58 juta dari total PnL $4,37 juta masih berasal dari satu posisi yang belum direalisasikan, jadi sekitar 82% keuntungannya masih berupa unrealized PnL. ini menunjukkan potensi strategi membiarkan posisi pemenang berkembang, cuman valuasi di atas kertas belum tentu bisa direalisasikan karena likuiditas, market impact, dan tekanan jual. 5. Konsentrasi posisi meningkatkan efisiensi sekaligus risiko. wallet yang holdingnya kurang dari 10 token terlihat lebih efisien dalam PnL per trade. lebih sedikit posisi memungkinkan modal lebih terkonsentrasi pada aset dengan potensi tinggi, tapi ketergantungan pada satu atau dua token juga meningkatkan risiko penurunan PnL secara drastis. jumlah token aja gak cukup, distribusi modal, korelasi aset, sama kontribusi PnL tiap posisi tetap perlu diperiksa. implikasi untuk strategi trenching dan on-chain research - Ukur edge bersihnya: perhitungkan fee, slippage, sama market impact, gak cuman win rate atau gross PnL. - Rekonstruksi perilaku wallet: analisis entry, ukuran posisi, holding period, sama exit buat nemuin pola yang bisa direplikasi. - Pisahin realized dan unrealized PnL: wallet dengan profit besar belum tentu sudah mengamankan keuntungan atau memiliki likuiditas untuk mencairkannya. fyi, perlu diingat, sampel 100 wallet teratas rentan terhadap survivorship bias. posisi ekstrem juga bisa mendominasi hasil, jadi performa mereka belum tentu mewakili strategi yang konsisten. kesimpulannya? edge trading meme coin lebih ditentuin sama kualitas seleksi, efisiensi eksekusi, asimetri return, dan pengelolaan posisi daripada sekadar frekuensi trading atau popularitas wallet. daftar wallet teratas lebih tepat dijadikan bahan riset buat menguji strategi daripada sumber sinyal entry buat di copy-trading.

𝗰𝘆𝗰𝗹𝗼𝗽 @nobrainflip

3 days ago

x.com/i/article/2106…

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The Hugging Face ban that started it all: audnai/penc1aw-GLM-5.3-abliterated-for-offensive-cyber by @audn_ai Is now listed on Pirate Face. Because EVERY model needs a continuity plan. Model profile ↓

Blackfrost_AI @Blackfrost_AI

3 weeks ago

Y'all thought I was lying. Backup Your models people. Stay Frosty

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🚨 THIS IS ACTUALLY INSANE Python developers are still installing five different tools to manage one project. `pip` for packages. `virtualenv` for environments. `pyenv` for Python versions. `pipx` for CLI tools. `poetry` for project management. uv replaces all of them with one tool. And it’s written in Rust. The headline number: 10–100× faster than pip. But speed isn't even the most interesting part. uv can: → Create and manage Python projects → Resolve dependencies with a universal lockfile → Create virtual environments → Install and switch between Python versions → Run standalone Python scripts with dependencies → Install CLI tools with `uvx` → Compile and sync requirements → Manage Cargo-style workspaces The workflow becomes ridiculously simple: `uv init` → create a project `uv add` → add dependencies `uv run` → run your code `uv lock` → lock dependencies `uv sync` → reproduce the environment And if you're already using pip? You don't have to throw your workflow away. The `uv pip` interface is designed as a drop-in replacement while giving you the speed boost. The other clever bit: uv uses a global cache to deduplicate dependencies and save disk space. So instead of assembling a Python toolchain piece by piece, you get one fast CLI that covers the whole workflow. And unlike a lot of newer developer tools, uv is already considered stable and production-ready. If you work with Python, this is one of those tools you should probably try once. You might not go back. #Python #DevTools #Rust #OpenSource #Programming #AIEngineering x.com/vicky_grok/sta…

Vikas gupta @vicky_grok

a month ago

x.com/i/article/2093…

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Ollama now supports Jev-like decision models all locally. Use decision models like Nimble for tasks like ticket triaging, model routing, and content moderation. ollama pull nimble Here’s Nimble playing Ollama racer through the new local /v1/systemone API by making decisions in real-time. 🏎️

jadi semalem gua coba nge LP di meteora... dan gua dapet pelajaran berharga dari situ, dan bakal gua breakdown lah di post ini Jadi semalem gua liat koin yg namanya NearPad lagi kenceng"nya naek, jadi gua coba buat open posisi disana, pertamanya itu gua open posisi spot wide, dan pas koinnya turun dikit, gua coba open posisi -50% Nah ceritanya itu koinnya sempet turun sampe OOR kiri dari dua posisi gua ini, tapi akhirnya sempet rebound sampe gua profit lumayan lah 25% dan juga 15% dari dua posisi ini Tapi gua ngerasa koinnya bakal naek lagi dan back to ATH lagi, dan ujung" nya malah turun lagi, sebenernya disitu udah ga kenapa", tapi salahnya gua bukannya nge CL coinnya, malah gua nginepin semaleman Alhasil gua jadi minus lebih dari $90 dan salah satu posisinya minus 70% So yg gua pelajari adalah jangan terlalu greedy kalau jadi orang, kalau udah profit 10% lebih di LP it's already good, jadi TP aja, kecuali momentum di koinnya bener" bullish, dan kalau emang udah salah, CL aja... Btw ini ga bermaksud menggurui ya, ini bagian dari dokumentasi perjalanan gua aja... Adakah tambahan dari abang" yg lain??

i still don't understand why everyone is NOT using this 100% free alternative to TradingView it does everything TradingView charges $2,399/year for FREE i plugged openmarket into my Opus 5.5 + Jev stack and built an ORDER FLOW trading desk that is running autonomously 24/7 here is the EXACT system you can build today: 1. openmarket streams three things live for free, the liquidation heatmap, the order book depth, and CVD, the exact order flow a fund pays thousands for 2. the liquidation map shows where the stops are stacked, price hunts those clusters, so it tells you where the market wants to go next 3. the order book shows if there is more size on the buy or the sell side, that is who is actually in control right now 4. CVD shows if the buying is real, price up but CVD down means the move is fake and about to fail, the read most people never see 5. i pull all three through the OpenMarket API and pack them into one clean snapshot on every candle 6. Jev scores that snapshot in < 100 ms, is a cluster about to get hunted, is the flow real or fading, buy sell or hold 7. Opus 5.5 sits on top, after fixed time it reads which order flow reads actually worked and rewrites the questions Jev asks, so it gets sharper and becomes powerful itself 8. a hard risk layer holds every limit and now the desk trades institutional order flow on its own, for ZERO dollars a month in data the full build is in my article below:

Roan @RohOnChain

3 weeks ago

Jev is the FASTEST AI model ever built for trading It makes calibrated buy/sell decisions in under 100 ms That is one real decision on every single block, 24/7 In this article I've shown EXACTLY how to build HFT trading system with Jev (from scratch) x.com/i/article/2100…

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kalo udah cuan di TP, kalo udah TP sebagian tabung di wallet dan sebagian di WD ke bank kalian. ENTRY │ ▼ POSITION │ ├── LOSS ──→ CUT / ACCEPT LOSS │ └── PROFIT │ ▼ TP │ ▼ REALIZED PROFIT │ ┌────┴────┐ ▼ ▼ COMPOUND WITHDRAW │ │ ▼ ┌──┴──┐ RE-TRADE WALLET BANK

LP YANG DEWASA VS YANG BELUM Entry → Bukan karena liat volume gede, discan terus di degen-dlmm terus gatel mau entry → Ada kriteria sendiri, baru masuk Harga di tengah atau di bawah range? → Bukan ngomel di discord → Bukan minta orang "tiupin chart dong" atau "telpon gake" → Liat structure chart dan indicator fav kalian terus decide mau nunggu atau adjust (reposisi atau udahan) Sistem → Tiap keputusan ada alasannya → Salah pun, tau letak salahnya di mana Posisi lagi IL atau rugi? → Bukan marah-marah, bukan ngomong kasar → Yang ada cuma satu: review play-nya Market gak peduli emosi lo Semua balik lagi kediri lo yang bisa act on what market give us @MeteoraAG @met_lparmy

ini cukup menarik sih, biasanya kalo bikin concentrated LP, liquidity dibagi cukup merata di dalam range. misalnya: Token: $1 Range: $1 → $0.50 Modal: $500 dengan LP biasa, saat harga turun ke $0.50, average entry contoh ini sekitar $0.707. artinya dari $0.50, harga perlu naik sekitar 41.4% hanya buat kembali ke BE sebelum fee. nah Bid Ladder ini mengubah distribusinya. jadi gak dibagi rata, tapi makin rendah harga, makin gede liquidity yang ditempatin: $1.00 → 5% $0.90 → 7% $0.80 → 9% $0.70 → 12% $0.60 → 15% $0.55 → 21% $0.50 → 31% jadi pas harga turun: harga makin murah → size pembelian makin besar → average entry makin turun. dalam contoh tersebut, average entry menjadi sekitar $0.615. kalo harga sampai $0.50, drawdown sekitar 18.7%, dibanding sekitar 29.3% pada distribusi biasa. dan buat balik ke BE, cukup rebound: $0.50 → $0.615 = +23% jadi setelah aku coba dikit2, kayanya Bid Ladder lebih tepat dipahami semacam DCA yang dijalanin via concentrated liquidity. kita gak perlu nebak bottom, jadi lebih ke menentukan dari awal: - range akumulasi - level harga - size di tiap level - kapan inventory mulai keluar pas rebound fee menjadi bonus selama pool masih punya real trading volume. tapi ada trade-off penting: kalo token terus turun sampai mati, ladder akan terus mengubah modal menjadi inventory token. jadi filter pool tetep lebih penting daripada APR: real volume + healthy liquidity + token yang memang bersedia kita hold kalo turun lebih dalem.

liquidityladder @liquidityladder

a week ago

The best strategy for making money in LP pools right now let me show you with $500 let’s take a token trading at $1 and a range down to $0.50 option 1: one sided Spot $500 is distributed evenly across the entire range if the price drops to $0.50, the average entry becomes

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x.com/i/article/2040…

it's a bit "toxic" actually that you still staring at the chart and terminal while travelling. but $27k while travelling? only possible on @MeteoraAG it's fun, we not really that glued to the chart, except there's runner with 2m volume this is my manual wallets looks like, it's 4 wallets, since i got cted every 3 days so need rotating all gween, no red days, because i play safe, i know when to stop (gonna write or make videos about this) even tho, there's a day that i didn't lp, because i'm not forcing it, i learn it while travelling there's red positions but it's covered in the end of the day. $40k this month with agents wallets.

yunus @0xyunss

2 weeks ago

yang mau belajar LP sambil travelling seperti mas @Voidgoesbrr yang dapet duit $18k atau 300jutaan disambi jalan jalan ke luar negeri dengan @MeteoraAG dlmm langsung saja ikut LP Academy Live @MeteoraIDN malem ini, gratis, gaperlu daftar apa apa sung saja liat live dari X atau

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