AI Browser Agents in 2026: 6 Tools That Actually Click, Type and Buy

AI browser agents compared for 2026 — Claude Computer Use, ChatGPT Agent, Browser Use and more, plus where they still fail.

AI browser agents compared for 2026 — Claude Computer Use, ChatGPT Agent, Browser Use and more, plus where they still fail.

The best embedding models for RAG in 2026 — 8 compared by MTEB score, language coverage and self-hosting, plus how to actually choose.

Prompt injection explained for 2026 — nine attack patterns, what actually works as defence, and the lethal trifecta to design around.

LLM inference server comparison for 2026 — vLLM, Ollama, llama.cpp and LM Studio, and the one question that decides which you need.

Fine-tuning vs RAG in 2026: six questions that settle it, when each genuinely wins, and the third option most comparisons skip.

LLM evaluation tools compared for 2026 — RAGAS, DeepEval, LangSmith and more, plus how to build your first eval set in an afternoon.

Context engineering in 2026: why bigger windows made things worse, the four ways context fails, and eight proven techniques that fix it.

Compare the best AI coding assistants in 2026 — Claude Code, Cursor, Copilot and Windsurf — with real pricing, honest trade-offs and who each one fits.

The agent loop is fifteen lines. Everything that makes an agent worth deploying is in the other 185. A working AI agent from scratch, in plain Python.

A local AI agent runs the same loop as a cloud one. The model is the only thing that changes, and that one change decides how you write everything else.