Liberty Rising | IQ 313

🇬🇧 ENRAGING - BRIT STABBED BY THE SIKH COURT VIDEO BITS: Mr Nowak can be heard saying “can’t breathe.” Police put handcuffs on Mr Nowak, who was lying on his side, telling officers he had been stabbed and that he could not breathe. The officer told Mr Nowak that he was under arrest for suspicion of assault. Mr Nowak repeated that he had been stabbed. A male voice said: “I don’t think you have, mate.” -> He drowned in own blood, as his lungs filled with blood … and died while the cops handcuffed him for racism.

Zoning and red tape stop this, there is no reason to not install solar panels over a car park other than government beurucrats

- j'utilise Claude tous les jours - je me crois assez bon là-dedans - je regarde deux ingénieurs Anthropic pendant 2 HEURES - l'ingénieur de Claude explique les Skills from scratch - les 5 premières minutes - attends. Les Skills c'est juste des dossiers ? - des dossiers qui retiennent ton workflow ? - ton domaine ? ton expertise ? - pause. retour arrière. je regarde a nouveau - je pense à chaque prompt que j'ai réécrit de zéro - chaque contexte que j'ai expliqué 100 fois - chaque session qui a tout oublié - ça n'aurait pas dû se passer comme ça - 16 minutes. tout change - skill issue détecté

the skill gap between $95K and $300K right now is Claude Opus agent architecture this 2-hour guide closes that gap companies are paying $150K-300K/year for engineers who know this most of them have no idea this guide exists watch it. build it. charge for it

Can you reduce all of political philosophy to one diagram? A pretty good attempt. (From a book on Machiavelli by Gabriele Pedulla.)

Ask Claude to map your entire app's architecture into a single HTML page and JSON file. The HTML is for you. The JSON is for the next agent working on a new feature. Your codebase now explains itself.

🚨Por qué nadie está hablando de ESTO? NVIDIA está regalando acceso GRATIS vía API a más de 80 modelos de IA hosted. Modelos incluidos: • MiniMax M2.7 • GLM 5.1 • Kimi 2.5 • DeepSeek 3.2 • GPT-OSS-120B • Sarvam-M y muchos más. Funciona directo con Cursor, Zed, OpenCode, Hermes, OpenClaude, etc. Cómo configurarlo en 30 segundos: 1. Consigue tu API Key gratis → build.nvidia.com 2. Base URL: integrate.api.nvidia.com 3. Elige el model ID (ej: `minimaxai/minimax-m2.7`) Si estás prototipando o experimentando con IA esto es inferencia gratis. La mayoría de builders aún no lo sabe. Me das las gracias despues.

Vibe coders are getting sued. People are launching apps with real users but skipping the boring stuff that can actually kill the product. A developer with 20+ years of experience just shared the pre-launch checklist every AI builder should run: → privacy policy if you collect user data → know where user data is stored → check security headers → scan against OWASP basics → look for SQL injection / XSS / auth issues → make sure .env values are not leaking → check API responses for sensitive data → remove secrets from logs → never expose API keys in frontend code → move keys server-side or behind a proxy → add rate limits before someone burns your API bill This is what most vibe coders are missing. AI can help you build the app. But if you launch without security, privacy, and abuse checks... you didn't ship a product. you shipped a liability.

@obsdmd genuinely think is the most complete approach I've seen for using AI with Obsidian: Self-Improving Obsidian LLM Wiki 📷 github.com/Bahgs/Self-Imp… The simple version: Drop raw sources into a folder → your AI agent turns them into linked notes, concepts, entities, and summaries

Obsidian CEO personally wrote the official Agent Skills for his own app 🤯 These are 5 skills that fix every layer agents get wrong: → obsidian-markdown (wikilinks, callouts, embeds, frontmatter) → obsidian-bases (database views with filters, formulas, aggregations) → json-canvas (visual canvases linked to your notes) → obsidian-cli (search, create, manage tasks from the terminal) → defuddle (clean markdown from any web page) MIT licensed. Works with Claude Code, Codex CLI, OpenCode.

After 2 months of everyday use, I can say that setting up a personal research engine is one of the highest-ROI things you can do if you like to learn and stay on top of things at the edge - Use a cloud-hosted agent, probably hermes or openclaw - Learn about memory systems and encoding (cognee is very good at this) - Build the right commands for parsing data and storing it (tag things properly, encode and save full text and key ideas) - Build recurring jobs so the system grows itself (rss ingestion, auto twitter scroll, newsletter following) - Build advanced skills that create connections between ideas, surface the most important info, and create digests for you automatically - Build search retrieval skills that actually pull what you need and don't forget or miss things Will change your life

LLM Wikis + HTML Artifacts are insanely powerful. You should seriously consider this in your workflows. LLM Wikis captures all the important information that lets you and your agents do meaningful work. HTML artifacts present that information in interesting ways that allow you to take important actions along with your agents. My HTML artifacts sit on top of my LLM wikis. They are dynamic and are easily extended as needs arise. I have hooked my Artifacts to talk to my agents, and similarly, the agents can talk to artifacts. This has allowed me to build powerful artifacts that reduce my inbox to zero, keep me updated on any topic of interest, fast prototyping, do deep research, design/trigger new experiments, generate figures to improve understanding, schedule research, search relevant information, discover topics, and so much more. What you see in the clip is not a website. It's a simple interactive HTML artifact. HTML artifacts are useful for designers, engineers, researchers, students, and anyone working with agents. Lastly, HTML doesn't replace Markdown. They are a much better combination working together.

This Chinese guy built a Second Brain in Obsidian and every morning gets 3 trading ideas that brought him $180,000 in 6 months. Inside he runs a pipeline of 6 workflows on N8N that automatically pulls every read article, listened podcast, and voice note into a shared Obsidian vault, and a neural network analyst every morning at 6:00 finds connections between the fresh and the old and puts the 3 strongest trading ideas for the day into the inbox. No analytics desk, no Bloomberg terminal, no Telegram chats with traders. Just a Mac Mini by the wall, an iPhone in the pocket, and 1 local Obsidian vault. And traditional quant funds keep entire teams of 8 people on salary for the same flow of insights, while his expenses are only subscriptions to Readwise, Whisper API, and N8N hosting. 6 pipelines process about 200 sources a day and close the monthly API bill at about $120. The Mac Mini itself stores the entire vault and keeps the neural network analyst running 24/7, and from the iPhone the owner drops any idea he hears on the go into a Telegram bot, and it lands in the vault inbox in just 30 seconds. The starting instruction that sits in the VAULT.md file at the root of his vault looks like this: "you are the AI analyst of a solo trader. you read his vault every morning at 6:00, find connections between fresh and old notes, and deliver 3 trading ideas he can verify in the hour before the market opens. pipelines: // Reader (pulls every article and highlight from Readwise, Twitter bookmarks, and Kindle into /notes) // Listener (transcribes podcasts through Airr and voice notes through Whisper, puts them in /notes) // Catcher (accepts any message from the Telegram bot and writes it to /inbox with a timestamp) // Connector (every night reads across the entire vault and updates the connection graph between 4,000 notes) // Briefer (at 6:00 AM writes a brief: 3 trading ideas for today plus the emerging thesis of the week, puts it in /inbox) // Mobile (lives in the iPhone, answers any question about the vault by voice, and confirms alerts while the owner is on the go). you wake the owner with a push notification only when a fresh note contradicts his active thesis or when 1 of the 3 morning ideas has a confidence score above 90%." This instruction immediately sets the role for the system and the limits of its autonomy. It knows it is supposed to connect new with old on its own. It knows it is supposed to prepare 3 trading ideas every morning on its own. It knows it connects the live trader only when a thesis is contradicted or an ultra-confident idea appears. → Reader pulls about 80 articles and highlights a day from Readwise, Twitter, and Kindle → Listener transcribes 4 to 6 podcasts a week through Airr and Whisper → Catcher intercepts all voice and text ideas through the Telegram bot, averaging 15 to 20 a day → Connector updates the connection graph between 4,000 notes every night, adding 25 to 30 new edges → Briefer puts a fresh brief with 3 trading ideas and the emerging thesis into the inbox at exactly 6:00 → Mobile answers any question about the vault by voice and confirms alerts right from the iPhone And only when a new note contradicts his active thesis or 1 of the ideas breaks 90% confidence does the orchestrator raise the owner with a push notification. And when the trader at that moment is driving to the gym or eating breakfast, the Mobile agent in his iPhone answers any quick question about the vault by voice: what he wrote about this ticker last week, which 3 sources support the idea of long NVDA, and what counter-thesis already sits in his notes. The trader makes the decision and sends the order before New York opens. The fresh brief from last Monday looks like this: "reader: 78 materials added over the weekend, 11 of them about semiconductors, 4 about energy, 3 about biotech. passing to connector." "connector: 27 new connections found between fresh materials and the vault, the strongest one is that the Goldman report from Wednesday matches the NVDA thesis you wrote 3 weeks ago." "briefer: 3 trading ideas for today: long NVDA (confidence 0.84), short Tesla at the close of the quarterly report (0.71), watch URI (0.62). emerging thesis of the week: the market is underpricing capex on data centers." "alert: your fresh note about long-term risk in semis contradicts the NVDA thesis. sending for review." In his work setup there is no cloud server, no team of analysts, and not even a Bloomberg subscription. At home sits a Mac Mini with a local Obsidian vault, on top run 6 N8N pipelines and a neural network analyst, and the same vault mirrors to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo trading setup on a second brain: $120 a month on the API, about $30,000 a month into the account, and between them 6 pipelines, 4,000 connected notes, and 1 iPhone in the pocket.

Obsidian + Claude Code = 24/7 personal operating system. Works while you sleep. The people who build this tonight will never work the same way again. Watch it and Bookmark it now.

🇩🇰 Copenhagen's Green-led council is limiting elderly care residents to 80 grams of beef per week for climate reasons. That works out to 11.4 grams a day, which is less meat than most people put in a single taco. A Green party rep explained the logic: the elderly "have been the biggest climate sinners throughout their lives." So the plan is apparently to make them atone for it in their final years, one thimble of mince at a time. Critics, including opposition parties and elderly advocates, say the policy risks undernutrition in a population already vulnerable to it. The council says it's flexible, but the elderly eating climate penance for dinner might disagree. Source: BT, Ekstra Bladet

Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch. Stanford taught the entire thing in 1 hour lecture & released it for free. Bookmark & watch this today before someone takes it down.

The personal knowledge base build, in 60 seconds: Total setup: 45 minutes this weekend. Then it compounds forever. 1. 5 minutes: Setup Create 3 folders: raw/, wiki/, outputs/. Drop a CLAUDE.md schema file in the root. Done. 2. 10 minutes: Dump Copy-paste articles, notes, screenshots, meeting transcripts into raw/. Don't rename. Don't organize. 3. 30 minutes: Let the AI build Point Claude at the folder. "Read everything in raw/. Compile a wiki following CLAUDE.md rules. Create INDEX.md first." Walk away. Come back to organized articles, [[linked]] topics, and a searchable index. 4. Ongoing: The compounding loop Ask questions. Save answers back to raw/. Every query makes the next answer better. 5. Monthly: Health check Tell the AI to flag contradictions, find unexplained topics, and suggest 3 new articles to fill gaps. The system gets smarter the longer you use it. Day 1 it's basic. Day 90 it's a company asset nobody else has.