LLM News and Articles

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Monday, 2026-04-13
07:24LangChain: The Engineer’s Complete Guide to Building LLM Applications
07:12AI Agents in 2026: The Rise of Autonomous AI
07:04The Last Generation of Data Engineers?
07:03Adam’s Law: The Hidden Textual Frequency Cheat Code for LLMs
07:03The Harness Is Everything
07:01Why Your Next LLM Might Run Out of Memory (And How TurboQuant Fixes It)
06:59GSTR-9 Annual Return Made Easy: How to Prepare It Directly from Your Invoice Data
06:56Building a Production-Grade Local RAG Pipeline — 100% Free, No Cloud Required
06:51Fine-Tuning an LLM on Your Own Data: The Complete No-Fluff Guide
06:48LangChain Demystified: How to Build Intelligent LLM Applications the Right Way
06:40ChatGPT praises mood and 'bedroom/DIY texture' of fart sounds
06:30Is Generative AI a Platform? Yes. And It Is Unlike Any Platform That Has Come Before.
06:01There is a Meaningful Difference between Context & Instruction
05:21I Let AI Start Coding Immediately… and Regretted It in 10 Minutes
03:56Mastering LangChain: Building Production-Ready LLM Applications
03:52Step-by-Step Guide: Integrate DGrid with Junie CLI
03:48Auto-Generate Wiki Documentation from Databricks Notebooks using AI (PySpark + LLM)
03:47The Journey to Find The Best Sparse and Dense Embedding Model (Aprik 2026)
03:46Topology of Ideas: When Thoughts Stop Being Lines and Start Becoming Landscapes
03:23Deep Technical Guide to LangChain: Building Modular LLM Applications with Python
03:14The Three Brains of Modern Computing: CPU vs GPU vs NPU (And Why It Matters for AI)
03:05OxiBonsai: The World’s First Pure Rust 1-Bit LLM Inference Engine
03:01A Small Company From China Shook the Entire AI World. Here Is What Nobody Told You.
03:00I Tested 20+ LLMs for Coding Tasks — Only 5 Actually Worked
02:45Before you build an agent, design the job
02:44Proximal Policy Optimization (PPO) from Background to Full Implementation
02:39Building an SLM from Scratch: A Journey That 1,100+ Learners Joined
02:08When Models Mistake Approval for Evidence: Epistemic Independence in Language Models
Sunday, 2026-04-12
23:46The Inference Stack: Routing and Serving Layers for LLMs in Production
23:46SideButton — Open Source Platform for AI Agents
23:45The AI Startup Playbook Silicon Valley Can’t Copy: Build Where the Internet Breaks
23:37EngLISP: Bridging Natural Language and Computation Through Minimal Structure
23:25Why Claude Code Hits “Usage Limit Reached” — And How You Can Delay It Dramatically
23:14Show HN: Local LLM on a Pi 4 controlling hardware via tool calling
23:04Computer-Use: The Clicking Isn’t the Hard Part
22:53Rust, MCP, DataFusion Devil’s Favorite Trifecta
22:50Prompt Engineering vs. Context Engineering
22:49Why LLMs Hallucinate — and How We Can Fix It
22:37Why Your AI Website Still Looks Like Garbage in 2026
22:30Sam Altman's home targeted in second attack
22:28The Context Layer That Turns Vibe Coding Into Software Engineering
21:52Meta AI and KAUST Researchers Propose Neural Computers That Fold Computation, Memory, and I/O Into One Learned Model
21:13Anthropic’s Claude Mythos release created a Glomar Trap for customers and rivals
20:19If you don’t have a word for it can you even think it?
19:50The 1,000 Repository Milestone - The Power of Sharding
19:32Retrieval-Augmented Generation (RAG): The Complete Guide
19:32The Silent “Token Tax”: Is AI Development Getting More Expensive?
19:25Deep Drive Into LangChain
19:21Better MoE model inference with warp decode
19:04Speed isn’t the problem. I analysed 4,472 quick commerce reviews to find out what is.
19:02Mission inbox zero: how I surgically nuked over 80,000 unread emails with my AI agent
18:51How Traditional ML Beats Powerful LLMs at Interpretability
18:451-bit inference of 0.8M param GPT running inside 8192 bytes of sram
18:41Anthropic Wants to Build Their Own Chips Now?
18:36OpenAI says to update Mac apps ChatGPT and Codex as security precaution
18:35LangChain Deep Technical Blog: Designing Modular LLM Applications with End-to-End Implementation
18:18From Prompts to Intelligent Systems: A Deep Dive into LangChain Architecture and Applications
17:55Artificial Intelligence Lab: A Practical Roadmap to Modern AI Systems
17:16What Large Language Models Imply About Machine Capabilities
16:41Mastering Agentic AI #1: Naive RAG’den Otonom Akıllı Ajanlara
16:30Data Pollution Is the Biggest Threat to AI -Not Model Size
15:59From Prompts to Agents: A Deep Technical Exploration of LangChain Architecture
15:57Top 7 Places to Learn Agentic AI in 2026
15:52The Gemma 4 Project, Cloud DevOps Engineer’s Guide, MIT & Stanford New Courses | Issue 83
15:51Beyond Flat Metrics: Brand Mention Surplus
15:51Test-Time Compute: What “Thinking” Models Actually Do (And What They Don’t)
15:49What I Learned Building a RAG Pipeline Over 644 Legal Documents
15:46What Actually Happens After You Click “Place Order” on an E-commerce Website?
15:42Marathon by Car
15:38Essential Concepts of System Design and Architecture
15:37Designing Modular LLM Applications with LangChain
15:28Designing and Deploying LLM Applications with LangChain: A Technical Deep Dive
15:20I’m studying future AI might erase
14:09Google Just Open-Sourced a Model That Beats GPT-Level Rivals at 1/20th the Size
13:59How I Built an AI-Powered LinkedIn Post Generator Using n8n and Google Gemini
13:52Why Is Training Large Language Models So Hard?
13:45Building LLM Applications with LangChain: A Deep Technical Guide
12:38LangChain
12:06An Insight to Production-Grade LLMs
11:54LLM Wiki Skill: Build a Second Brain With Claude Code and Obsidian
11:51.NET ile Yapay Zeka Uygulamaları Geliştirme: Akış, Yapılandırılmış Çıktı ve Fonksiyon Çağırma
11:49Claude for Word Just Launched. Here’s What Production AI Teams Should Know.
11:46CLAUDE CODE VS CHATGPT CODEX: Which is a better choice?
11:41Anthropic’s Claude Model Family in 2026: An Analytical Guide for Builders
11:40LangChain: Building Intelligent LLM Applications from the Ground Up
11:02Building an AI-Powered PR Reviewer with AWS Bedrock and GitHub Actions
11:01Anthropic's Mythos Will Force a Cybersecurity Reckoning–Just Not the One You Th
10:55The Last Person Who Could Think
10:54Designing LLM-Powered Applications with LangChain: From Concept to Code
10:53DAG vs LLM: Rethinking Orchestration in AI Systems
10:34Strong Model First or Weak Model First? A Cost Study for Multi-Step LLM Agents
10:319 Things That Break When You Ship an AI Agent to Real Users
10:27Agentic AI: The Shift from Chatbots to Autonomous Workers
10:24Building a Voice-Controlled Local AI Agent with Whisper, Groq, and Ollama
09:20MiniMax Just Open Sourced MiniMax M2.7: A Self-Evolving Agent Model that Scores 56.22% on SWE-Pro and 57.0% on Terminal Bench 2
09:18The hidden math behind running LLMs locally.
07:45Beyond the Prompt: Engineering LLM Systems with LangChain
07:41Building a Hebrew Podcast Pipeline: What I Learned About the State of Hebrew AI
07:35Building smarter text analysis agents with Azure Language and MCP
07:31Metadata & Filtering — Precision in Retrieval
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