Christos Ι.

Eric Schmidt (former Google CEO): “If you want to make money, it’s actually easy, start an agentic AI company.” We’re in the agent era now, and it favors builders. What matters isn’t your resume, it’s what you shipped this week. probably be the only article you need to learn and understand AI in 2026.

STANFORD JUST PUT ITS ENTIRE ARTIFICIAL INTELLIGENCE CURRICULUM ON YOUTUBE FOR FREE. CS221. The same course that produced engineers now running AI labs, building frontier models, and getting paid $500,000 a year at the companies everyone is trying to work for. Most people have never heard of it. The ones who have are not telling you about it. Here is what the course actually covers: Search algorithms. The mathematical foundation behind every AI that finds optimal solutions in complex environments. Constraint satisfaction. How AI reasons through problems with thousands of interdependent variables simultaneously. Markov decision processes. The probabilistic framework behind every AI agent that makes sequential decisions under uncertainty. Machine learning from first principles. Not how to use sklearn. How the math actually works underneath it. Neural networks. Built from the ground up before jumping to applications. Logic and knowledge representation. How AI systems reason about the world formally. Natural language processing. The foundation of everything happening in LLMs right now. Robotics and computer vision. How AI perceives and acts in physical environments. Every concept that powers every AI product you use daily is in this curriculum. Not a surface level overview. The actual mathematics. The actual algorithms. The actual reasoning. This is what separates engineers who build AI from operators who use it. Stanford charged $60,000 a year for students to sit in this classroom. They put the whole thing on YouTube. Bookmark this before you open any other AI resource today. Follow @cyrilXBT for more elite resources that build real depth the moment they drop.

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.

📂 SaaS Stack ┃ ┣ 📂 Frontend ┃ ┣ 📂 React ┃ ┣ 📂 NextJS ┃ ┣ 📂 Vue ┃ ┣ 📂 TailwindCSS ┃ ┗ 📂 Shadcn UI ┃ ┣ 📂 Backend ┃ ┣ 📂 NodeJS ┃ ┣ 📂 Django ┃ ┣ 📂 Laravel ┃ ┣ 📂 FastAPI ┃ ┗ 📂 Express ┃ ┣ 📂 Database ┃ ┣ 📂 PostgreSQL ┃ ┣ 📂 MySQL ┃ ┣ 📂 MongoDB ┃ ┣ 📂 Redis ┃ ┗ 📂 Supabase ┃ ┣ 📂 Auth ┃ ┣ 📂 Clerk ┃ ┣ 📂 Auth0 ┃ ┣ 📂 Firebase Auth ┃ ┣ 📂 Supabase Auth ┃ ┗ 📂 NextAuth ┃ ┣ 📂 Payments ┃ ┣ 📂 Stripe ┃ ┣ 📂 Paddle ┃ ┣ 📂 Dodo Payments ┃ ┣ 📂 Lemon Squeezy ┃ ┗ 📂 Polar ┃ ┣ 📂 Emails ┃ ┣ 📂 Resend ┃ ┣ 📂 SendGrid ┃ ┣ 📂 Mailgun ┃ ┣ 📂 Postmark ┃ ┗ 📂 Amazon SES ┃ ┣ 📂 Storage ┃ ┣ 📂 AWS ┃ ┣ 📂 Cloudflare ┃ ┣ 📂 Google Cloud Storage ┃ ┣ 📂 Supabase Storage ┃ ┗ 📂 Uploadcare ┃ ┣ 📂 Deployment ┃ ┣ 📂 Vercel ┃ ┣ 📂 Netlify ┃ ┣ 📂 Railway ┃ ┣ 📂 Render ┃ ┗ 📂 AWS ┃ ┣ 📂 Domains and DNS ┃ ┣ 📂 Namecheap ┃ ┣ 📂 Hostinger ┃ ┣ 📂 Cloudflare DNS ┃ ┣ 📂 Google Domains ┃ ┗ 📂 SiteGround ┃ ┣ 📂 Analytics ┃ ┣ 📂 Google Analytics ┃ ┣ 📂 Plausible ┃ ┣ 📂 PostHog ┃ ┣ 📂 Mixpanel ┃ ┗ 📂 DataFast ┃ ┣ 📂 Monitoring ┃ ┣ 📂 Sentry ┃ ┣ 📂 LogRocket ┃ ┣ 📂 Datadog ┃ ┣ 📂 NewRelic ┃ ┗ 📂 UptimeRobot ┃ ┣ 📂 DevOps ┃ ┣ 📂 Docker ┃ ┣ 📂 Kubernetes ┃ ┣ 📂 GitHub Actions ┃ ┣ 📂 CI CD ┃ ┗ 📂 Terraform ┃ ┣ 📂 Search ┃ ┣ 📂 Algolia ┃ ┣ 📂 Meilisearch ┃ ┣ 📂 Elasticsearch ┃ ┣ 📂 Typesense ┃ ┗ 📂 OpenSearch ┃ ┣ 📂 AI Integration ┃ ┣ 📂 OpenAI API ┃ ┣ 📂 Anthropic API ┃ ┣ 📂 Replicate ┃ ┣ 📂 HuggingFace ┃ ┗ 📂 Gemini API ┃ ┣ 📂 Integrations ┃ ┣ 📂 Zapier ┃ ┣ 📂 Make ┃ ┣ 📂 n8n ┃ ┣ 📂 Pabbly ┃ ┗ 📂 Webhooks ┃ ┣ 📂 Security ┃ ┣ 📂 SSL ┃ ┣ 📂 Cloudflare ┃ ┣ 📂 WAF ┃ ┣ 📂 Rate Limiting ┃ ┗ 📂 Secrets Management ┃ ┣ 📂 Marketing ┃ ┣ 📂 Search Console ┃ ┣ 📂 Outrank ┃ ┣ 📂 Buffer ┃ ┣ 📂 Analytics ┃ ┗ 📂 Kit ┃ ┗ 📂 Customer Support ┣ 📂 Intercom ┣ 📂 Crisp ┣ 📂 Zendesk ┣ 📂 Tawk ┗ 📂 HelpScout

Neural networks and machine learning, visualized

YOUR AI AGENT CAN FINALLY SCRAPE WEBSITES WITHOUT GETTING BLOCKED - Zero bot detection - Bypasses Cloudflare naturally - 774 times faster than BeautifulSoup - No need for selector maintenance GitHub: github.com/D4Vinci/Scrapl…

A man spends 50 years teaching at MIT. He knows his time is running out. So he records one last lecture — everything he knows, distilled into a single hour. He died 5 months later. This is that lecture. The most important hour you'll watch this week. 👇 Bookmark it for later

SOMEONE JUST OPEN SOURCED AN ENTIRE AI COMPANY MADE OF 147 AGENTS. The system includes AI teams for engineering, marketing, sales, finance, support, and more, all deployable through a single command.

They quoted him $18,000. He opened Claude instead. Same result. One afternoon. $20/month. The gap between knowing how to use Claude and not knowing is worth $18,000. This article below fixes that.

This is crazy !! Cursor now has built a Kanban board where you can just drop in tasks and the agent will pick those up and complete them.

Every app I vibe code has the tech stack below Easy for beginners and free to start If you've never built an app before, just paste this list into Codex or Claude Code and you'll be good to go: Web framework: NextJS Hosting: Vercel Database: Convex Auth: Clerk Payments: Stripe Styling: Tailwind AI: logic- OpenAI, creativity- Claude, cheap tasks- Gemini Flash 3 Emails: Resend Design apps with: GPT image gen 2 + Claude Design AI I use to build it all: Codex desktop app w/ GPT 5.5 Any questions let me know!

With the Autodesk Fusion connector, designers and engineers can create and modify 3D models through conversation.

T̶e̶x̶t̶ Sketch to CAD is here

“Physics is the law, everything else is a recommendation.” — Elon Musk

Someone connected Claude Opus 4.7 to a professional CAD tool It can design real 3D models from a single text prompt: Just type what you want, and it builds it - step by step, in real time. It works through "Adam AI Tools", a free app inside Onshape (cloud-based CAD tool). You type a prompt in the sidebar, Claude writes FeatureScript code, and Onshape executes it live. It can: → Plan a full design from a single prompt → Create sketches, extrudes, shells, and fillets → Add precise dimensions (it knows real board specs like Pi 4B: 85 × 56 mm) → Cut out ports, vents, and mounting holes → Fix its own errors and keep iterating In the demo, the prompt was "create a Raspberry Pi case." In 30 seconds, Claude delivered a complete enclosure - with mounting posts, port cutouts for USB, HDMI, Ethernet, power, SD card, vents, and fillets. This isn't image generation. It's real parametric CAD - the kind engineers actually manufacture from.

Create a house with any shape on ➡️ drafted.ai

“You get paid in direct proportion to the difficulty of the problems you solve.” ~Elon Musk.

MICROSOFT JUST DROPPED A 4B MODEL THAT TURNS ONE IMAGE INTO A FULLY TEXTURED 3D ASSET IN SECONDS

To generate 3D models in Codex with text-to-cad: Start a new project, write your prompt for a 3D model, and include a link to clone the text-to-cad repo. Codex handles the rest. The repo is open source and all scripts / ui run locally. Link below.