Nikita Saykov

eur/usd $ersdl

[Ahmad @ahmad_a_wahabb]

This video is 100% AI

It takes 5 min end to end.

No camera. No actress. No studio booked.

Same face, same script, rebuilt into a dozen different tones, settings, and languages, all from one input.

This is exactly how we're producing AI UGC ads for supplement and DTC brands right now, at a speed no real shoot could match.

Comment "UGC" and I'll DM you how it's built. (Follow so I can dm)

[Vladimir Bayandin @vovudebosh]

🚨 NO CLIENTS? 6 MONTHS BUILDING, STILL $0 REVENUE.

THE PROBLEM WAS NEVER THE PRODUCT — IT WAS SALES.

THIS AI FIXES THAT: DROP YOUR WEBSITE LINK, IT FINDS YOUR BUYERS, WRITES THE EMAILS, BOOKS THE CALLS. YOU JUST SHOW UP & CLOSE.

$50 FREE CREDITS, ONLY 9 LEFT — GONE TONIGHT.

[こすもす｜AIで起業しろ @cosmos_hzokujin]

フロントエンドの仕事、マジで消滅するかもしれません…。

いま世界中で大パニックになってるGitHubリポジトリを見つけたんですが、これ一瞬で【9.6万Star】を超えた異例のバケモノプロジェクトです。

何がヤバいかというと、Apple、Figma、Stripeなど「世界最高峰の企業が持つデザインシステム」を、AIが読み込める言語（DESIGN.md）に整理して無料公開してくれていること。

使い方は拍子抜けするほど簡単。
お気に入りのブランドの『DESIGN.md』をコピーして、自分のプロジェクトのフォルダにポンと置くだけ。
たったこれだけです。

あとはCursorなどのAIエディタが、Markdownに書かれた「色・フォント・余白・コンポーネントの挙動」などの緻密なルールを自動で読み込み、一切ブレのないトップブランド水準のUIを自律的に生成してくれます。

📍複雑な解析や設定は一切不要
📍「〇〇風にして」と指定するより圧倒的に高精度
📍人間がCSSをポチポチ書く時代は終了

もはやエンジニアは「デザインを実装する」のではなく「AIにデザインのルールブックを渡すだけ」の世界線に突入しました。
時代に取り残されないように、今すぐブクマして試してみてください👇

https://t.co/2GecX4cdpr

[鸟哥 | 蓝鸟会🕊️ @NFTCPS]

我草，开盒工具真来了，这个叫 ALIENS EYE。

你输一个用户名，它一次帮你扫 840+ 个平台，几秒钟全查完，谁在哪注册过账号基本藏不住。

几个点说下：
1️⃣ 异步扫描，快到离谱
2️⃣ 带 Tor 和代理，查的时候能护住自己来源
3️⃣ 结果能导 JSON、CSV、HTML、Markdown，做 OSINT 和安全研究挺顺手

丑话放前头：能力越大越得守规矩，只查自己有权限或拿到授权的目标，别拿去开盒骚扰别人，违法的事碰都别碰。

🔗 https://t.co/QvxAzEWuFG

[Miraqle @0xMiraqle]

THIS GUY IS A PSYCHO! HE BUILT A GOD-MODE SECOND BRAIN AGENT THAT NEVER FORGETS ANYTHING, CONTEXT PULLED!

Everyone is making their Obsidian vault prettier, but this thing left a plain vault behind, because notes that just sit there never actually think, but this does:

> a normal Obsidian vault only stores notes, it never fires a single neuron

> his brain runs STDP learning and pattern recognition, so it actually thinks instead of just holding text

> his agents are wired into that brain and working, each doing the task it was trained to do

> they feed what they find back into the brain, then go back and build on what they put there

> the loop never stops, so the whole thing just keeps getting smarter on its own

Everyone will fixate on the fires-neurons part, but the real unlock is the loop, because a brain that only stores plateaus the day you stop feeding it, while one your agents read from and write back into compounds by itself forever.

The absolute guide on "how to build" with the .md files in the article below.

P.S. you can send this article straight to your Claude to get full context for coming inregration 👇

[Luke The Dev @iamlukethedev]

Meet Hermes Agora

A 3D command center for Hermes Agents

Built 100% by Hermes Agents connected to Unreal Engine

Your AI agents now have a place to live, think move and collaborate.

Coming soon!

[Vox @Voxyz_ai]

stop telling Claude Code/Codex "read this file".
stop telling Claude Code/Codex "now read that one too".
stop telling Claude Code/Codex "grep the whole repo".

install codebase-memory. it indexes the Linux kernel, 28M lines, in 𝟯 𝗺𝗶𝗻𝘂𝘁𝗲𝘀. your repo takes seconds.

index once and the whole repo becomes 𝗼𝗻𝗲 𝗴𝗿𝗮𝗽𝗵 of every function, file and dependency. one query replaces dozens of grep and read cycles.

benchmarked across 31 real repos:
→ 10x fewer tokens on structural queries
→ 83% answer quality on complex tasks
→ 2.1x fewer tool calls

two prompts. send them straight to your agent 👇

[Hasan Toor @hasantoxr]

Loop Engineering is the next step after prompt engineering.

Most people still use Claude Code, Codex, Cursor, or Grok like a chat box:

Prompt.
Wait.
Copy.
Fix.
Prompt again.

This repo shows the next step:

You stop prompting the agent.

You design the loop that prompts the agent for you.

Inside:

→ Daily triage loops
→ PR babysitter loops
→ CI sweeper loops
→ Dependency sweeper loops
→ Changelog drafter loops
→ Post-merge cleanup loops
→ Issue triage loops

It also gives you CLIs to:

• Scaffold a loop
• Estimate token cost
• Audit if your repo is ready
• Add memory/state
• Add human handoff
• Add verification gates
• Run agents safely through GitHub Actions

The wild part is the shift in thinking.

Prompt engineering was about writing better instructions.

Loop engineering is about building a system where agents keep working, checking, fixing, and escalating without you babysitting every step.

This is what AI coding looks like when it stops being a chat session and starts becoming an operating system for software teams.

Repo: https://t.co/2USzC6KHUt

[Ceteris Paribus @onestoploss]

Bu çocuk tek bir şey yapıyor.

Dünya Kupası'nda oynanan tüm maçlara $100 beraberlik bahsi alıyor.

Kupada bugüne kadar toplam 40 maç tamamlandı.

Ve çocuk şimdiden $3000 karda.

Ama bence bu bir bahis hikayesi değil.

Bu, yanlış fiyatlanan olasılıkların sistematik olarak satın alınması.

Çocuk sadece piyasanın beraberlik ihtimalini olduğundan düşük fiyatladığına inanıyor ve aynı işlemi tekrar tekrar uyguluyor.

Çünkü maçın favorisini, güçlüyü, zayıfı hiç hesaba katmıyor.

Değişik kafalar!

Ha bana sorarsanız bir süre sonra bu kazancın normalize olması yada beraberlik için verilen oranların düşmesi gerekir.

Çocuğu turnuva sonuna kadar takip edeceğim.

[regent0x @regent0x_]

his “AI server” is 4 mac minis stacked next to the toaster

linked by free software into one machine that runs 235B models no single computer could load

regulated clients pay him $3,500/month each to use it

he has 6 of them

that’s $21k/month from a tower of silver boxes in his kitchen

the stack runs exo - open-source, $0, turns four separate minis into one pool of memory. the monitor shows all four nodes firing together, one model spread across the whole cluster

the thing nobody tells you about local AI:

a model either fits in your machine’s memory or it doesn’t run. that’s the wall everyone hits. it’s why people assume serious AI means a $40k server
exo walks straight through that wall. it splits one massive model across every box in the chain. four minis at $599 each suddenly run what a single high-end machine can’t touch

and the people who need this aren’t chasing the newest model

they’re the ones the cloud locked out:

→ a law firm with privileged case files
→ a medical practice under HIPAA
→ an accounting firm holding client financials

they need AI nowhere near a third-party server. a stack they can point to during an audit ends every objection

their models run on his cluster. the data never leaves equipment he controls
the breakdown:

→ 4 mac minis: $2,400 total
→ exo software: $0
→ electricity: ~$25/month
→ what he charges per client: $3,500/month
→ 6 active clients

the kitchen stack paid for itself in the first 3 weeks

month 1: 2 clients, $7k
month 3: 4 clients, $14k
month 6: 6 clients, $21k

he’s not running a startup with an office and a logo

he’s running four silver boxes between the coffee machine and a bowl of fruit, clearing $21k/month from hardware that cost $2,400

clients picture racks and cooling fans

reality is four minis humming next to where he makes breakfast

the cloud companies charge a fortune for compute and access to your own

he charges $3,500 a month for the one thing they can’t sell - a machine that never phones home

[阿柑 @499317906]

ai-video-generator-claude（即梦视频 skill · 起号/无脸号专用）

一个跑 28 万粉账号的老外，把自己在用的 10 个即梦视频 skill 开源了，`git clone` 进 `~/.claude/skills` 就能用。

你说一句"做个 10 秒无脸财经号开头"，它把镜头、灯光、音效、每秒时间点全写好，粘进 Higgsfield 直接出片。

https://t.co/ZC7t1jcINw

[AIVersePlay @AIVersePlay]

BU ADAM GERÇEKTEN GEMINI 3.1 + SEEDANCE 2.0 KULLANARAK 10.000 DOLARLIK SİNEMATİK WEB SİTELERİ YAPMAK İÇİN 16 DAKİKALIK BİR EĞİTİM VİDEOSU ATMIŞ.

Bir adam 16 dakikalık bir video attı ve o video beni durdurdu.

Gemini 3.1 ve seedance 2.0 bir arada kullanarak
10.000 dolarlık sinematik web siteleri nasıl yapılır.

Başlık bu, şimdi düşün.
10.000 dolarlık web sitesi dediğinde, ajans aklına gelir.

Ekip aklına gelir.

Haftalarca süren proje aklına gelir.
Bu video ikisini de ortadan kaldırıyor.
Gemini 3.1 tasarım kararlarını veriyor.
İçeriği yazıyor,yapıyı kuruyor.
Seedance 2.0 sinematik video arka planları üretiyor.
İkisi birleşince, ajansın haftalarca yaptığını, tek kişi saatler içinde yapıyor.

10.000 dolarlık çıktı.
Ajans fiyatı yok, ekip maliyeti yok.
Sadece doğru araç kombinasyonu, 16 dakika bu kadar.

Videonun en etkileyici kısmı şu:

Sonuç gerçekten sinematik görünüyor ve ucuz yapay zeka çıktısı değil.
Profesyonel prodüksiyon kalitesi, hareketli arka planlar, akıcı geçişler, etkileyici görsel dil, hepsini iki araç hallediyor.

Freelancer mısın?
Ajans mı kurmak istiyorsun?
Web tasarım işi yapmak mı istiyorsun?
Bu video sana 10.000 dolarlık iş almanın sistemini gösteriyor.

[Noisy @noisyb0y1]

APPLE JUST SHOWED HOW TO RUN 10 AI AGENTS LOCALLY ON MAC - NO CLOUD, NO API KEYS, ZERO COSTS

00:10 Apple engineer says: "your data stays on your device, AI available anywhere at any time, zero usage costs"

agent reads your code, checks GitHub, finds what needs attention and writes a report - all on your Mac, nothing goes to the internet

10 agents work simultaneously - one writes code, another tests, third fixes bugs - parallel with no queue

built a full iPad app from scratch in 2 minutes, fixed its own mistakes and compiled without issues

takes 5 minutes to set up - and you never pay again for a bot that runs 24/7

[そう｜Claude Codeで始めるAI自動化 @so_ainsight]

今週GitHubで急上昇したAIリポジトリ10選：

1. headroom
LLMに渡す前にログ・ファイル・RAGチャンクを圧縮し、トークン消費を60〜95%削減するツール。ライブラリ・プロキシ・MCPサーバーの3つの形で組み込める。
https://t.co/HRNQTDMZHZ

2. Agent-Reach
Twitter・Reddit・YouTube・GitHubなど主要プラットフォームをAIエージェントに横断検索させるツール。APIキー不要でCLI1本から動く。
https://t.co/fWlNy20yya

3. agent-skills（addyosmani）
コーディングエージェント向けの本番品質スキルセット。AIアシスタントを実務レベルで動かすための土台。
https://t.co/ufDpmNWJJR

4. SkillSpector（NVIDIA）
AIエージェントスキルの脆弱性・悪意あるパターン・セキュリティリスクを検出するスキャナー。NVIDIAが公開したエージェント安全対策ツール。
https://t.co/ipaVNNV08L

5. codebase-memory-mcp
コードベースを永続的な知識グラフとしてインデックス化するMCPサーバー。158言語に対応し、依存ゼロの単一バイナリで動く。
https://t.co/TXgffRKo7N

6. OpenMontage
AIコーディングアシスタントを動画制作の環境に変えるオープンソースシステム。12本のパイプラインと52種のツールを搭載する。
https://t.co/4AEROy0RZe

7. PaddleOCR
PDFや画像を、AIが扱いやすい構造化データに変換する軽量OCRツールキット。100言語以上に対応し、LLMへの入力前処理に使える。
https://t.co/CrLQeLJYCA

8. agentsview
Claude Code・Codexなど20以上のコーディングエージェントのセッション履歴・トークン使用量・インサイトを、ローカルで検索・分析できるツール。
https://t.co/ou8CRLELp8

9. LMCache
LLMのKVキャッシュを高速化する専用レイヤー。同じコンテキストの再計算を省き、推論コストと遅延を下げる。
https://t.co/1JSvQHpaR2

10. flue（withastro）
自律エージェントを構築・実行するためのTypeScript製ハーネスフレームワーク。セッション・ツール・スキルに加え、安全な実行のためのサンドボックスを備える。
https://t.co/87sBJvrkFZ

[Lonely @Lonely__MH]

虽然视频比较早了，但是其中的方法论并不过时。

我看着 Anthropic 的两个工程师聊了 24 分钟，然后意识到我一直在像猴子🐒一样使用 Claude Code🙃

[크롱 @Krongggggg]

이건 계속 리마인드 해줘야함

챗창 닫으면 증발하는 지식 파편들 모으기 딱 좋은 세팅임.

옵시디언 볼트 파고 Claude Code 연동한 뒤에 카파시 위키 프롬프트 던져두면 raw 소스 넣을 때마다 알아서 문서화하고 링크 연결해줌..

나중에 맥락 다 끊긴 채로 제로베이스에서 검색 안 하려면 이거로 지식 저장소 꼭 파두세요.

[Karan @karankendre]

Nobody saw this coming

Japan is now officially in the AI race

and they’ve released a model that performs on par with Claude Mythos

[Khushi Doshi @aiwithkhush]

10 GITHUB REPOS THAT SCRAPE THE ENTIRE INTERNET FOR YOU

Bookmark every single one. Each one pulls clean data off any website on earth, the kind of access companies sell behind a sales call and a contract.

1. https://t.co/yjhB8qsY2r

Point it at any website and it crawls every page, renders the JavaScript, and hands back clean structured data an AI can read instantly. It crossed 130K stars and landed in GitHub's top 100 repos. The scraping backbone half the AI startups quietly run on, open for anyone.

2. https://t.co/H8tTZjwd7O

The #1 trending crawler on GitHub. Turns any site into clean, LLM-ready markdown, faster than the paid services and with no API key, no account, no per-page fee. A dev built it in days after getting fed up paying $16 for a gated scraper. 51K stars. Apache 2.0.

3. https://t.co/xgLQDLB4HL

An AI agent that drives a real browser like a human, clicking, scrolling, logging in, filling forms, and pulling data off sites it has never seen before. Two ETH Zurich researchers built it and it hit 95K stars in about a year. The thing that scrapes pages no simple crawler can reach. MIT.

4. https://t.co/bBDy50sR9R

The full professional scraping framework, with rotating proxies, automatic retries, browser fingerprint spoofing, and queue management, all the machinery that keeps you from getting blocked. The exact stack scraping companies charge thousands to operate, handed to you for free.

5. https://t.co/nKhjeJxe1F

The original industrial-strength scraper that has quietly powered data teams for over a decade. Crawl millions of pages, extract anything, export it clean. Battle-tested at a scale most paid tools never reach, and free the entire time.

6. https://t.co/0NeYEdAWDt

Microsoft's own tool that converts any file or web page, PDFs, Office docs, HTML, images, into clean markdown an AI can actually use. The messy-data-to-clean-data step companies build whole pipelines around, open-sourced by Microsoft itself.

7. https://t.co/vyKqqy18Pi

A stealth scraper built to stay invisible, adapting automatically when a site changes its layout and slipping past the bot detection that stops everything else. The cat-and-mouse layer that anti-scraping vendors sell as a premium feature, free and open.

8. https://t.co/o9TuMdEQ1l

Mirror and control any Android phone from your computer to pull data and automate apps that have no website at all. The bridge into mobile-only platforms that most scrapers can't touch. 130K+ stars. Apache 2.0.

9. https://t.co/24FQISv92x

Show it one example of what you want and it figures out the pattern and scrapes the rest of the site automatically. No selectors, no code to maintain. The "just get me this data" button, in a few lines of Python.

10. https://t.co/BgL79bWL89

A version of curl that perfectly mimics a real browser's fingerprint, so the requests sneaking past every defense look exactly like a human with Chrome open. The lowest-level trick the expensive scraping APIs are quietly built on top of.

Companies sell this access for $2,000 a month. The source code is right here.