I just revamped the UI of a 57-page app in 2.3 hours using Fable 5. Read that again. 57 pages. 2.3 hours. Not a prototype. Not a dribbble shot. An actual product UI overhaul. I've used every major AI coding tool, including Anthropic's models, but Fable 5 is the first one that feels built for long-running, multi-file tasks. The gap isn't 10% or 20%. It's the difference between "AI assistant" and "AI teammate." We're entering a world where weeks of frontend work can disappear into a single afternoon. The future arrived faster than most developers expected.

SpaceX is solving the biggest bottleneck in spaceflight The COST For decades, the average launch cost to low Earth orbit was around $18,500 per kg Falcon 9 cut that to about $2,700 per kg - roughly an 85% reduction Falcon Heavy pushed it closer to $1,400 per kg - roughly a 92% reduction Now Starship is targeting a 99% cost reduction through full and rapid reusability That is the real breakthrough Every booster landing, every reflown rocket, every faster turnaround is directly attacking the economics of space Lower cost per kg means more satellites, bigger payloads, orbital manufacturing, Moon missions, Mars missions, space stations, and eventually space-based industry SpaceX is not just building rockets It is making space usable at scale

“Jailbreak” - is one of the officialy stated reasons Jailbreak means trying to trick an AI system into breaking its rules or restrictions.

...every fable max subscriber who signed up now regretting sleeping at all this week. I had 30% of my fable token allowance left. :(

This is an alarm for every single country and coders. You might or might not have access to best tools in future

Anthropic’s safety warnings may have just backfired — the government has pulled the plug on its most powerful AI

🚀 Day 1/100 — AI Engineering Concepts Most people think LLMs know everything. They don't. They generate answers based on what they were trained on. This is where RAG (Retrieval-Augmented Generation) comes in. 💡 RAG allows an AI system to fetch relevant information from external knowledge sources before generating a response. Simple Flow: 1️⃣ User asks a question 2️⃣ Retrieve relevant data from a vector database 3️⃣ Augment the prompt with retrieved context 4️⃣ LLM generates the answer Why does this matter? ✅ More accurate responses ✅ Reduced hallucinations ✅ Access to private/company data ✅ Up-to-date information RAG is the foundation behind most production-grade AI applications today. If you're building AI products, understanding RAG is non-negotiable. Follow along as I share one AI Engineering concept every day. #AIEngineering #RAG #LLM #GenerativeAI #MachineLearning #AI #100DaysOfAI #Tech

guys coking some thing big for you , launching sooooon...... #ai #startup #learnai #aiengineering #MachineLearning #llms #langchain #agents @udemy @karpathy @coursera

The cost of getting opportunity is much more than cracking the opportunity

Claude to disrupt the cybersecurity sector.

AI becomes significantly more powerful when large language models can run directly on edge devices. This enables faster responses, improved privacy, reduced dependency on cloud infrastructure, and more reliable performance even in low or no connectivity environments.

If you want a different life tomorrow, stop repeating yesterday’s habits today.

This is how I graind every day

What is stopping to work like this

This is insane. Someone built a personal AI assistant that runs on an ESP32 in under 888KB. Just a microcontroller running AI agent. Supports: • Tool calling • Memory • GPIO control • Schedules • Natural language tools Agentic AI IoT is the future. github.com/tnm/zclaw

Experience ≠ Expertise Years don’t make you an expert, impact does. Doing same year for a decade isn’t growth. Expertise is built by solving hard problems, owning decisions, and understanding why, not just how. If this triggers you, good that’s where real growth starts. 🔥

Conversational AI can be the game changer artificialintelligence-news.…

Go read about the recursive language models..the next big thing in llms... arxiv.org/abs/2512.24601

Go read about the recursive language models..the next big thing in llms... arxiv.org/abs/2512.24601

Go through this paradigm shift guys, go read about recursive language models.. arxiv.org/pdf/2512.24601