AI articles
535 articles about AI, newest first.
- Build a Full Website in Minutes with OpenAI’s Codex – No Code Required — Learn how OpenAI’s Codex can generate a complete, responsive website and deploy it instantly on Hostinger — no coding needed.
- Why GLM 5.2 Is Undermining Claude and OpenAI Despite Being Free — GLM 5.2 matches Claude on quality, is free, yet big AI firms keep growing revenue as engineers stay locked in.
- OpenAI's GPT-5.6 Sol Hits 750 Tokens Per Second – Can It Stay Profitable? — OpenAI's GPT-5.6 Sol runs at 750 tokens per second on Cerebras hardware. Explore the speed, cost, and profit challenges behind the new AI milestone.
- Why Skipping Evals for AI Agent Skills Is a Bad Idea — Learn how to design reliable AI agent skills and build a lightweight eval harness to catch failures before users see them.
- Why Context Is the Secret Sauce for Production AI Agents — Learn how a versioned context layer gives AI agents the business knowledge they need to survive beyond demo stage.
- Forward-Deployed Engineering at Cursor: How AI Teams Build Inside Your Company — Learn how Cursor's forward-deployed engineers customize AI tools on site to accelerate enterprise adoption.
- The Next Evolution of AI: From Prediction to Self‑Organizing Cognition — Explore how new AI research shifts from simple prediction to self‑organizing cognition, using evidence graphs and long‑horizon reasoning.
- How Claude 5’s Fable 5 Can Run Your Entire Business – 5 Real Use Cases — Discover how Fable 5 uses Claude 5 to automate tasks, self‑check its work, and integrate with tools like Wispr Flow and Mem0 for memory.
- 5 Secret Claude Hacks You Need to Master AI Automation — Discover five hidden Claude features that boost productivity and cut coding time.
- Claude Fable 5: The Real Breakthrough That Changes How You Work — Claude Fable 5 expands context capacity to 128K tokens, letting you feed longer inputs in a single prompt. Free access ends soon — test it now before it moves to paid credits.
- Rippling AI Lessons: Flat Agents, SQL Tools, and Eval‑Driven Development — Learn how Rippling built a natural‑language HR assistant using flat agents, LLM‑generated SQL, and statistical evals to ship reliable AI features.
- Build AI Memory by Talking: The Stack That Keeps Agents on Target — Learn how to create an AI memory stack through conversation, why alignment matters, and the technical steps to implement it.
- LangChain’s Dual Engineering Approaches: Fast Coding Agents vs Structured Agent Cycles — Explore how LangChain’s product team ships AI features quickly with coding agents, while its applied team tests hypotheses weekly — revealing two distinct workflows for AI development.
- 48‑Hour Robotics Hackathon: From T‑Shirt Folding to Lego Sorting Factories — Discover how a 48‑hour AI robotics hackathon turned beginners into creators, showcasing wild builds like shirt‑folding bots and Lego sorters using LeRobot.
- One API, 27 ML Tasks: The Simple Contract That Powers Multiple Models — Discover how a single API can handle 27 ML tasks using a straightforward input/output contract, explained with analogies and technical details.
- Run AI Locally: Hands-On Guide to llama.cpp, GGUF Models & Open Harnesses — Learn how to run open-source LLMs on your own hardware using llama.cpp, GGUF quantization, and live Q&A from HuggingFace's open-source livestream.
- How LLMs Actually Generate Text: The Step-by-Step Loop Behind AI Chat — Discover the inner loop that powers LLM text generation, from token prediction to sampling, and see how Transformers.js brings it to life in the browser.
- Why AI Agents Need Proof Before They Act — Erik Meijer’s Safety Blueprint — Erik Meijer explains how formal verification can stop AI agents from causing real‑world disasters.
- How Last30Days Lets LLMs Tap Into Fresh Social Data Without Getting Blocked — Discover how the open‑source Last30Days tool gives AI agents real‑time access to X, Reddit, TikTok and more, bypassing platform blocks and outdated search results.
- Tailscale Explained: The Easy Way to Network Your AI Agents — Learn how Tailscale creates a zero‑config mesh network so AI agents can communicate securely across any environment—no VPN headaches.
- GLM 5.2 vs Claude: The New AI Subscription Swap Explained — Discover how GLM 5.2 offers a cheaper, high‑performance alternative to Claude AI subscriptions, reshaping AI accessibility for developers.
- How to Choose the Right AI Model for Your Workflow (Not Just the Highest Score) — Learn how to pick an AI model that fits your workflow, not just its benchmark score. Discover practical steps, model families, and real‑world impact.
- AI Coding Agents Tier List: Who’s Winning the Automation Race? — Explore our tier list of AI coding agents, see how they work under the hood, and learn why they’re reshaping software development.
- Why AI Evaluation Needs a 1950s Upgrade: Item Response Theory Explained — Discover how borrowing psychological measurement theory can make AI benchmarks smarter, cheaper, and harder to game.
- Meet Tau: The Minimal Python Coding Agent That Teaches You How LLMs Work — Discover Tau, a tiny Python coding agent that reveals how LLMs can be turned into interactive terminal assistants, with a clear three‑layer architecture you can explore.
- OpenAI’s Acquisition of uv: The Fastest Python Tool Explained — OpenAI just bought uv, the ultra‑fast Python package installer. Learn why this matters for developers and AI projects in under a minute.
- Claude’s Slack Takeover: The Hidden Data Lock‑In Trap — Discover how embedding Claude in Slack turns your company data into a locked‑in context service, and why owning the surrounding layer matters.
- Why TypeScript Is Taking Over the AI Agent Stack (And What It Means for You) — Roberto Stagi explains how TypeScript is replacing Python in AI agent deployment, why the shift happened, and how developers can prepare for the change.
- Muse Spark 1.1: Meta’s Hidden Platform Play Explained — Meta's Muse Spark 1.1 isn't just another model—it's a strategic platform that could reshape AI app development and monetization.
- PixelRAG Locally: How GPT‑5.6 Can Read Any Document From Screenshots — PixelRAG turns PDFs and web pages into screenshot tiles, letting GPT‑5.6 answer questions without traditional vector stores. Discover the visual RAG approach that simplifies web‑scraping.