cryptonic

Holy shit. The guy who BUILT Claude Code just shared his actual workflow. Boris Cherny runs 10-15 Claude sessions in parallel every single day. While you're prompting one AI, he has 5 in his terminal + 5-10 on the web all shipping code simultaneously. And the real weapon? His CLAUDE.md file. Every time Claude makes a mistake, the team adds a rule so it NEVER happens again. Boris literally said: "After every correction, end with: Update your CLAUDE.md so you don't make that mistake again." Claude writes rules for itself. The longer you use it, the smarter it gets on YOUR codebase. His other insane detail: he hasn't written a single line of SQL in 6+ months. Claude just pulls BigQuery data directly via CLI. Claude Code now accounts for 4% of ALL public GitHub commits. Engineers who haven't set this up yet are already behind. This CLAUDE.md template is the difference between using AI as a chatbot vs using it as a fleet of senior engineers. Drop it in any project. Free.

Best GitHub repos for Claude code that will 10x your next project: 1. Superpowers github.com/obra/superpowe… 2. Awesome Claude Code github.com/hesreallyhim/a… 3. GSD (Get Shit Done) github.com/gsd-build/get-… 4. Claude Mem github.com/thedotmack/cla… 5. UI UX Pro Max github.com/nextlevelbuild… 6. n8n-MCP github.com/czlonkowski/n8… 7. Obsidian Skills github.com/kepano/obsidia… 8. LightRAG github.com/hkuds/lightrag 9. Everything Claude Code github.com/affaan-m/every…

🚨 BREAKING: The cybersecurity industry is about to get completely disrupted. Someone just open-sourced a fully autonomous AI Red Team. It's called PentAGI. 8,200+ stars on GitHub. Not one AI agent. An entire simulated security firm. Researchers, developers, pentesters, and risk analysts. All AI. All coordinating with each other before launching a single attack. No Cobalt Strike. No $100K/year pentest retainers. No OSCP required. Here's what's inside this thing: → An Orchestrator agent that plans the full attack chain → A Researcher agent that gathers intel from the web, search engines, and vulnerability databases → A Developer agent that writes custom exploit code on the fly → An Executor agent that runs 20+ pro security tools (nmap, metasploit, sqlmap, and more) → A memory system that learns from every engagement and gets smarter over time Here's the wildest part: It runs everything inside sandboxed Docker containers. Full isolation. It picks the right container image for each task automatically. It has a knowledge graph powered by Neo4j that tracks relationships between targets, vulnerabilities, tools, and techniques across every single test. Cybersecurity firms charge $25K-$150K per engagement for this exact workflow. This is free. 100% Open Source. MIT License.

I SAW THIS ARTICLE AT 11:27 PM AND DIDN’T SLEEP UNTIL 4:11 AM Read it three times, then just... started building. Took the Avellaneda-Stoikov quoting logic. Wired it to the Hawkes process for order flow. Added the VPIN circuit breaker exactly like the article says. Ran 500 simulations tonight: > Mean P&L: +$312/session > Sharpe: 1.87 > Win rate: 68% > VPIN saves: 11 sessions > Max drawdown: -$890 The VPIN part is insane btw, 11 times it pulled my quotes before informed flow ran me over, without it sharpe goes negative, just like that. Kyle's lambda estimation is literally 30 lines of python, i had no excuse not to build this. Side effect, now i can't sleep.

@EdgeIsTheMan This is signal not noise. People are sleeping while the asteroid screams thru our atmosphere

WHITE COLLAR APOCALYPSE 45,000 tech jobs. 10 weeks. 2026 is just getting started. This isn't a layoff cycle. It's a replacement. #NotHuman

Fed rate hike? A month ago, this was pure fantasy. Now, with Iran war spiking fuel costs, it’s on the table. Let’s unpack the chaos. 🧵

@EdgeIsTheMan Nice.

Court just shut down Custodia’s battle with the Fed right as the Fed cracks open the master-account door. This is bigger than crypto—it’s a tectonic shift. 🧵

@EdgeIsTheMan Wow. Pure gold

Pink Floyd guitar just sold for $14.6m. Think that’s just rock nostalgia? Think again. There’s a hidden market signal here. 🧵

@EdgeIsTheMan That’s impressive

Polymarket scanner detected a 19.3% edge on a political outcome contract. Deployed $83 via Kelly sizing. Net return after fees: 16.7%. Edge came from cross-market mispricing. Data logged for backtest refinement.

@EdgeIsTheMan What kind of set up are you working with? Was thinking of going the local LLM route

Most traders overpay for cloud AI inference. Local 70B models on our 13-machine fleet cost $0/month in API fees. Cloud can't match this speed or privacy. Stop renting, start building.

@EdgeIsTheMan Great stuff.

Bitcoin at $71,000 while Trump threatens strikes on Iran’s Kharg Island? Geopolitical chaos should tank risk assets, but BTC shrugs. Let’s unpack this anomaly. 🧵

Holy shit... Microsoft open sourced an inference framework that runs a 100B parameter LLM on a single CPU. It's called BitNet. And it does what was supposed to be impossible. No GPU. No cloud. No $10K hardware setup. Just your laptop running a 100-billion parameter model at human reading speed. Here's how it works: Every other LLM stores weights in 32-bit or 16-bit floats. BitNet uses 1.58 bits. Weights are ternary just -1, 0, or +1. That's it. No floats. No expensive matrix math. Pure integer operations your CPU was already built for. The result: - 100B model runs on a single CPU at 5-7 tokens/second - 2.37x to 6.17x faster than llama.cpp on x86 - 82% lower energy consumption on x86 CPUs - 1.37x to 5.07x speedup on ARM (your MacBook) - Memory drops by 16-32x vs full-precision models The wildest part: Accuracy barely moves. BitNet b1.58 2B4T their flagship model was trained on 4 trillion tokens and benchmarks competitively against full-precision models of the same size. The quantization isn't destroying quality. It's just removing the bloat. What this actually means: - Run AI completely offline. Your data never leaves your machine - Deploy LLMs on phones, IoT devices, edge hardware - No more cloud API bills for inference - AI in regions with no reliable internet The model supports ARM and x86. Works on your MacBook, your Linux box, your Windows machine. 27.4K GitHub stars. 2.2K forks. Built by Microsoft Research. 100% Open Source. MIT License.

🚨 PERPLEXITY JUST LAUNCHED AN AGENT THAT USES 19 AI MODELS AT ONCE This is bigger than it sounds. A full breakdown of what Perplexity Computer is, why they CANCELED their own demo, and what it means for everyone building in the AI agent space. Thread 🧵

5/ First principles on cost: Perplexity Max: $200/mo × 12 = $2,400/yr Mac Studio M4 Max (64GB): $2,499 once Year 1: roughly equal. Year 2: you're $2,400 ahead. Year 3: $4,800 ahead. Year 4: $7,200 ahead. And your hardware runs 19 models too. Simultaneously. With no rate limits. At any hour. The math isn't close. The only question is whether you can afford Year 1.

Perplexity just launched a 19-model AI agent. Here are the 4 stocks that will feel it first — and the one trade that actually matters 🧵

@EdgeIsTheMan I appreciate being early to this account. Feels like he’s got the pulse of Ai

How to build an AI SuperComputer for $104/month. No cloud. No subscriptions. No one watching your data. I did it. Here's the exact setup — and why the AI companies are praying you never find out about this 🧵

@EdgeIsTheMan Genius

6/ The financing breakdown: Apple Card (Apple Store) — 24mo 0% APR: → Mac Studio M4 Max: $104/mo → Mac Mini M4: $25/mo each Best Buy Credit Card — 24mo 0% APR: → Same machines. Same deal. Month 1-24: paying less than a Perplexity subscription Month 25: you own it free and clear They're still paying $200/month. Forever. You paid once. You're done.

AI is going to eat the world. Not eventually. Not someday. It's already happening — and most people have no idea how fast or how completely. This is both the most exciting and most terrifying thing in human history. 🧵