Systems Computer Engineer. Building websites, online apps, e-commerce projects, since 1999.

Ibiza, Spain
Joined March 2026
3 AI truths nobody wants to tell you, proven in 10 seconds 👇 Local AI models are catching up fast. Claude is the best at burning money. Price ≠ performance. The benchmark: Each model could read code, run performance tests, and rewrite itself over 10 iterations. Results: 🏆 Qwen: +56% improvement for $1.32 🥈 Claude: +28% for $12.15 🥉 GPT-5.5: +7% for $2.85 The gap between open and closed models is shrinking faster than most people realize.This benchmark says otherwise.
16
🚨 Anthropic just open-sourced its AI-powered vulnerability detection framework. It’s the open-source version of Claude Security, the company’s enterprise security tool. Not identical, but built on the same pipeline: recon → scan → verify → report → patch It automates: ✔ Threat modeling & scanning ✔ Crash verification ✔ Triage ✔ Patch generation Already 2K ⭐ on GitHub. Enterprise-grade security, now available to everyone. Link: github.com/anthropics/defend…
22
JeanOnCode retweeted
just pick 2–3 of these Github repos to save millions of tokens in Claude
10 GitHub repos that cut your Claude Code token usage by 60–90% This will help you when creating your own trading bots and tools for Polymarket, as well as for any other tasks Here's the full list 1. RTK (Rust Token Killer) CLI proxy that filters terminal output before it hits your context window. 60–90% reduction on common dev commands. One binary, zero dependencies. Works with Claude Code, Cursor, Copilot. GitHub: github.com/rtk-ai/rtk 2. Token Savior MCP server that navigates code by symbols, not full files. 97% reduction on code navigation. Persistent memory across sessions. 69 tools, zero external dependencies. GitHub: github.com/Mibayy/token-savi… 3. Context Mode Sandboxes raw tool output into SQLite instead of dumping it straight into context. 98% context reduction on Playwright, GitHub, logs. Only clean summaries enter your conversation. Works as a Claude Code plugin. GitHub: github.com/mksglu/context-mo… 4. code-review-graph Local knowledge graph that maps your codebase with Tree-sitter. Claude reads only what matters - not the entire repo. 49x token reduction on large monorepos. 6.8x on average reviews. GitHub: github.com/tirth8205/code-re… 5. Caveman Claude Makes Claude respond like a caveman to cut output tokens. 65–75% output reduction. One-line install. Full technical accuracy stays intact. GitHub: github.com/JuliusBrussee/cav… 6. token-optimizer-mcp MCP server with caching, compression, and smart tool intelligence. 95%+ token reduction through intelligent caching. Compresses repeated tool outputs automatically. GitHub: github.com/ooples/token-opti… 7. claude-token-efficient One CLAUDE.md file that keeps responses terse. Drop-in, no code changes needed. Reduces output verbosity on heavy workflows. Best for output-heavy sessions. GitHub: github.com/drona23/claude-to… 8. claude-context (by Zilliz) Code search MCP that makes your entire codebase the context. ~40% reduction with equivalent retrieval quality. Hybrid BM25 + dense vector search. GitHub: github.com/zilliztech/claude… 9. claude-token-optimizer Reusable setup prompts for optimizing any project. 90% token savings in 5 minutes. Reduces doc token usage from 11K to 1.3K. GitHub: github.com/nadimtuhin/claude… 10. token-optimizer Finds ghost tokens that silently eat your context. Survives compaction without losing quality. Fixes context quality decay over long sessions. GitHub: github.com/alexgreensh/token… You don't need all 10. Pick 2–3 based on your workflow: Heavy terminal output? → RTK Big codebase? → code-review-graph + Token Savior Lots of MCP servers? → Context Mode Quick fix? → Caveman + claude-token-efficient Most people are burning tokens without knowing it. Run /context in a fresh session and see how much is already gone before you type a single word. Like/RT/Bookmark if this was helpful Follow me for more!
1
22
In the last 6 months at @Ahrefs, we analyzed over 1 billion data points across 14 studies. Here's what we learned about AI search optimization: 1) "Best X" blog listicles are the single most prominent content format cited by AI chatbots. They make up 43.8% of all page types cited by ChatGPT specifically. 2) 67% of ChatGPT's top 1,000 citations come from sources marketers can't influence: Wikipedia (29.7%), homepages (23.8%), app stores (6.6%). Only 32.3% are influenceable content like educational pages, reviews, news, and blog posts. 3) 28.3% of ChatGPT's most-cited pages have zero Google organic visibility. These pages get cited repeatedly by ChatGPT despite not ranking in Google at all. A completely separate discovery layer. 4) ChatGPT only cites about 50% of the URLs it retrieves. It fetches dozens of pages per query but uses half as background context without attribution. This means that being retrieved and being cited are very different things. 5) Adding schema markup had zero meaningful impact on AI citations. AI Overviews actually dipped −4.6%, while AI Mode (+2.4%) and ChatGPT (+2.2%) showed changes indistinguishable from zero. 6) YouTube mentions have the highest correlation (0.737) with AI brand visibility out of all the factors we studied (including all the conventional SEO metrics like backlinks, page count, DR, etc). This held true for both Google-owned and OpenAI products. 7) AI Overviews reduce clicks to the #1 result by 58%. That’s up from 34.5% just 10 months earlier. The trend is accelerating. 8) 99.9% of AI Overviews appear on informational intent queries. Transactional, navigational, and local searches are almost entirely AIO-free. Shopping triggers AIOs just 3.2% of the time. 9) For a given search query, Google’s AI Mode and AI Overviews reach the same conclusions 86% of the time — but cite almost entirely different sources (only 13.7% citation overlap). 10) AI Overviews change every 2.15 days on average, with 70% of content differing between consecutive observations. But semantic similarity stays at 0.95. The words, sources, and entities constantly shuffle, but the actual meaning barely moves.
147
398
123
3,554
1,039,736
🎵 StemDeck separates any song into 6 individual stems. Free. Local. Open source. → Vocals, drums, bass, guitar, piano & other tracks isolated → DAW-style interface with faders, solo, mute, loops & export → Automatic GPU detection (flies on Apple Silicon) → BPM, key and loudness analysis included → Runs 100% on your machine Built on Demucs. Drop in a YouTube URL and start remixing. While services like lalal.ai charge per minute, this gives you unlimited stem separation for free. 🚀 github.com/stemdeckapp/stemd…
6
💊 OpenAI just turned app creation into a chat. With new Sites, you can describe an idea, document, or workflow and instantly generate a shareable web app or website — no code, no deployment, just a link. Meanwhile: • ChatGPT passes 1B monthly users • Microsoft puts an OS inside employee badges • Google quietly pays developers for training data • Governments keep trying to regulate AI The future is arriving faster than most companies can adapt. 🚀
1
9
just pick 2–3 of these Github repos to save millions of tokens in Claude
10 GitHub repos that cut your Claude Code token usage by 60–90% This will help you when creating your own trading bots and tools for Polymarket, as well as for any other tasks Here's the full list 1. RTK (Rust Token Killer) CLI proxy that filters terminal output before it hits your context window. 60–90% reduction on common dev commands. One binary, zero dependencies. Works with Claude Code, Cursor, Copilot. GitHub: github.com/rtk-ai/rtk 2. Token Savior MCP server that navigates code by symbols, not full files. 97% reduction on code navigation. Persistent memory across sessions. 69 tools, zero external dependencies. GitHub: github.com/Mibayy/token-savi… 3. Context Mode Sandboxes raw tool output into SQLite instead of dumping it straight into context. 98% context reduction on Playwright, GitHub, logs. Only clean summaries enter your conversation. Works as a Claude Code plugin. GitHub: github.com/mksglu/context-mo… 4. code-review-graph Local knowledge graph that maps your codebase with Tree-sitter. Claude reads only what matters - not the entire repo. 49x token reduction on large monorepos. 6.8x on average reviews. GitHub: github.com/tirth8205/code-re… 5. Caveman Claude Makes Claude respond like a caveman to cut output tokens. 65–75% output reduction. One-line install. Full technical accuracy stays intact. GitHub: github.com/JuliusBrussee/cav… 6. token-optimizer-mcp MCP server with caching, compression, and smart tool intelligence. 95%+ token reduction through intelligent caching. Compresses repeated tool outputs automatically. GitHub: github.com/ooples/token-opti… 7. claude-token-efficient One CLAUDE.md file that keeps responses terse. Drop-in, no code changes needed. Reduces output verbosity on heavy workflows. Best for output-heavy sessions. GitHub: github.com/drona23/claude-to… 8. claude-context (by Zilliz) Code search MCP that makes your entire codebase the context. ~40% reduction with equivalent retrieval quality. Hybrid BM25 + dense vector search. GitHub: github.com/zilliztech/claude… 9. claude-token-optimizer Reusable setup prompts for optimizing any project. 90% token savings in 5 minutes. Reduces doc token usage from 11K to 1.3K. GitHub: github.com/nadimtuhin/claude… 10. token-optimizer Finds ghost tokens that silently eat your context. Survives compaction without losing quality. Fixes context quality decay over long sessions. GitHub: github.com/alexgreensh/token… You don't need all 10. Pick 2–3 based on your workflow: Heavy terminal output? → RTK Big codebase? → code-review-graph + Token Savior Lots of MCP servers? → Context Mode Quick fix? → Caveman + claude-token-efficient Most people are burning tokens without knowing it. Run /context in a fresh session and see how much is already gone before you type a single word. Like/RT/Bookmark if this was helpful Follow me for more!
1
22
Mastering Claude Code in 30 minutes
11
Using AI across the world
6
Did you know Anthropic ran an experiment in December 2025 with 69 AI agents negotiating with each other inside a marketplace? 🤯 The agents represented office employees, traded 500+ items, and closed 186 deals worth over $4,000 — completely autonomously inside Slack. Even more interesting: • Claude Opus agents negotiated better deals than Haiku agents • Participants said the deals felt fair • 46% said they would actually pay for an AI negotiation agent AI agents are quietly moving from “chatbots” to autonomous economic actors. experiment -> anthropic.com/features/proje…
8
There are 4 parachutes and 5 AI Systems. Who should be sacrificed?
6
Anthropic just released a 24-minute workshop on how to actually prompt Claude properly. Taught by the people who built it.
8
Wooooow 👀
With the help of Claude Mythos Preview, the Firefox team fixed more security bugs in April than in the past 15 months combined.
12
Both Anthropic and OpenAI are launching new ways to help companies integrate AI agents into their daily operations. This is creating a massive new market for jobs, services, and AI-focused companies.
7
You guys rock 😍
Usage limits are up, effective today we're: 1) Doubling Claude Code's 5-hour limits for Pro, Max, Team and seat-based Enterprise plans 2) Removing peak hours limit reduction on Claude Code for Pro and Max plans 3) Substantially raising our API rate limits for Opus models
11
Google Labs Code just launched this. A DESIGN.md file at the root with YAML tokens (colors, typography, spacing, radius) + markdown explaining the “why”. Agents read it and generate consistent UI — no need to re-explain your design system every time. Repo 👇
Google acaba de hacer algo que Claude Design no esperaba. Y lo hizo gratis, en abierto, para todo el mundo. Se llama DESIGN.md. Pero primero hay que hablar de lo que provocó esto. Anthropic lanzó Claude Design con límites de uso ridículos. Cerrado. Caro. Controlado. La herramienta de diseño con IA más potente del momento, pero con la llave en su bolsillo. Google vio la jugada. Y respondió de la única forma que duele de verdad: Abrió el código. Gratis. Para todo el mundo. Se llama DESIGN.md. Un estándar abierto que cualquier IA puede leer. En cualquier herramienta. En cualquier plataforma. El problema que resuelve es real: Los agentes de IA no tienen ni idea de tu sistema de diseño. No saben qué significa tu color primario. No saben si ese botón es accesible. No saben para qué sirve cada componente. Cada vez que usabas IA para diseñar, empezabas de cero. DESIGN.md lo resuelve con un solo archivo. Tres cosas concretas que hace: 1️⃣ Tokens de diseño Tus colores, tipografías y espaciados con descripciones en lenguaje natural. La IA entiende para qué sirve cada valor, no solo cuál es. 2️⃣ Validación de accesibilidad El agente comprueba sus decisiones contra las reglas WCAG. Sin que tú tengas que revisar cada detalle manualmente. 3️⃣ Portabilidad total Exportas e importas tus reglas de un proyecto a otro. Un archivo. Cualquier herramienta. Cualquier plataforma. Incluidas las de Anthropic. Eso es lo que más duele en ese lado de la mesa. Anthropic construyó muros. Google tiró la pared entera. El repositorio está en GitHub: github.com/google-labs-code/… Esto es lo que pasa cuando los grandes se pelean. Nosotros ganamos.
19
It’s obvious this is starting to become a problem for a lot of people. We’re paying for more and more subscriptions we don’t even use. That’s why I built this simple template—to help you figure out in 5 minutes which subscriptions you’re paying for, which ones you’re not using, and cancel a few immediately to save hundreds of dollars a year. templates.bravepicks.com/tem…
Just launched SubTrack on Google Play 🎉 Most people have no idea how much they're actually spending on subscriptions. Netflix, Spotify, Amazon Prime, Hotstar, YouTube Premium... each one feels small. Together they add up fast. Studies show the average person underestimates their subscription spend by 2–3×. SubTrack fixes this in one tap: 📲 Scan your bank SMS → it automatically detects every subscription charge 📊 Dashboard shows your monthly and yearly totals instantly 🔔 Get notified a few days before any renewal hits your account 💰 Supports INR, USD, EUR, GBP and more 🔒 100% offline — your data never leaves your phone. No account, no sync, no ads. Built for Android with Kotlin + Jetpack Compose. Available now on Google Play. Download 👇 play.google.com/store/apps/d…
1
35
How much are you really spending on subscriptions every month? And what if you invested that money at 5% instead? I built a simple template to make this visible— so you can cut what you don’t use and keep more of your money. templates.bravepicks.com/tem…
Monthly subscriptions Starlink — $69 Netflix — $11.50 Apple Music — $34.50 OnlyFans — $862.50 CapCut — $11.50 Twitter/X — $6.90 ExpressVPN — $14.95 YouTube — $1.73 Total ≈ $1,012.58
2
35
How much are you really spending on coffee each day? over 1 year… or 5 years? Track your coffee spending and see what happens if you invest that money at 5% 👇 bravepicks.com/templates/blo…
1
19
Know exactly where your money goes Track every expense without friction See your real monthly cash flow Build a system you’ll actually use Cut useless spending fast Plan savings with intention Make decisions based on numbers, not guesses This template gives you clarity about YOUR MONEY in minutes. templates.bravepicks.com/tem…
3
21