Practical coverage of AI for developers: coding agents and how to keep them under control, new models and what they cost, local LLM projects, and the policy news that affects anyone building on AI APIs.
Google's Gemini 4 Argon is now in the Gemini API, at an introductory price that doubles in December. What it costs, how long decode and thinking levels work, and the code changes needed when moving from Gemini 3.
The MCP 2026-07-28 revision dropped sessions and the initialize handshake, and the TypeScript SDK moved to a new v2 line. A step-by-step guide to building, serving and testing a small MCP server with the current packages, plus what to change when migrating from v1.
A working, step-by-step setup that turns a folder of personal notes into a searchable knowledge graph on your own laptop, using Ollama for embeddings and entity extraction, FAISS for semantic search and Neo4j for relationships. Full Python code included.
A practical guide to open-source terminal coding agents: what they do, how to install Gemini CLI, Codex CLI, Aider and Goose, how to choose between them, running local models, and safety habits for letting an agent touch your repo.
CRAB tests AI agents on tasks that span a desktop and a phone, with graph-based checkpoints and efficiency metrics. What it measures, what its 2024 results showed, how to run it, and how it compares with OSWorld and AndroidWorld.
You don't need to start machine learning with equations. A guided path through free interactive tools (TensorFlow Playground, Teachable Machine, CNN Explainer, Transformer Explainer and Netron) with specific exercises that build real intuition before you write code.
"Agentic AI" is everywhere in 2026, and Gartner expects over 40% of agentic projects to be cancelled by 2027. A practical guide to what agents really are, the patterns that work in production, a minimal agent loop in code, and how to avoid the common failure modes.
Since March 2026, Claude Opus 4.6 and Sonnet 4.6 support a 1M-token context window at normal per-token prices. Real cost maths, when caching makes sense, and when you still shouldn't dump everything into the prompt.
Agent Safehouse wraps AI coding agents like Claude Code in a deny-first macOS sandbox so they can work on your project without reading your SSH keys or wandering through your home folder. How it works, how to install it, and where its protection stops.
WebMCP lets a website expose structured tools that in-browser AI agents can call, instead of making them guess from screenshots. How the declarative and imperative APIs work, with code, how to join Chrome's early preview, and the security questions to think about.
