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The latest AI guides, comparisons and news
Models compared, agents and MCP built step by step, automation, AI coding, local LLMs and the tools worth your time.
AI Models
GPT, Claude, Gemini, Llama, DeepSeek, Qwen, Mistral and the open-weight models: what each is good at, what it costs and how they compare.
AI ModelsGemini 4 Argon: What It Is, What's New and How to Use ItGemini 4 Argon is Google's new flagship reasoning model. What's new, where to use it (app, AI Studio, API, Vertex), pricing as published and the limits. · 6 min read
AI ModelsGPT-6 Sol vs Luna: Differences, Pricing and Which to UseGPT-6 Sol is OpenAI's mid-tier model for coding and agents; Luna is the cheap, high-volume one. Specs, prices, ChatGPT access and which to pick, compared. · 5 min read
AI ModelsMuse Spark Open: Meta's Open-Weight Model, Licence and How to Run ItMuse Spark Open is Meta's 816B open-weight MoE model. What it is, how it relates to Muse Wonder, the licence terms, hardware needs and how to run or access it. · 5 min read
AI Agents
Agentic AI explained and built: frameworks, tools, memory, skills, multi-agent systems, evals and keeping agent costs under control.
AI AgentsAgentic AI vs Generative AI: The Difference ExplainedGenerative AI creates content when prompted; agentic AI uses the same model to plan and take actions toward a goal. Differences, a table, examples and costs. · 8 min read
AI AgentsAI Agent Frameworks Compared (2026): LangGraph, CrewAI, OpenAI, Claude, ADK and MoreAI agent frameworks compared for 2026: LangGraph, CrewAI, Microsoft Agent Framework, OpenAI and Claude SDKs, Google ADK, LlamaIndex, Pydantic AI and n8n. · 8 min read
AI AgentsAI Agent Security: Risks, Recent Rogue-Agent Incidents and a Practical ChecklistAI agent security in 2026: prompt injection, excessive permissions, data theft and rogue actions, the latest real incidents, OWASP guidance and a checklist. · 9 min read
MCP and Integrations
The Model Context Protocol, MCP servers, function calling and connecting AI to the systems a business already runs.
MCP and IntegrationsThe Best MCP Servers in 2026, by Job (and How to Install Them)The most useful MCP servers by job, each checked against its official repo, with install steps for Claude Desktop, Claude Code, Cursor and VS Code. · 7 min read
MCP and IntegrationsMCP vs API: What's the Difference and When to Use EachAn API is a service's own interface; MCP is one protocol AI apps use to discover and call tools. Side-by-side table, examples and when to use each. · 7 min read
MCP and IntegrationsMCP vs RAG: Different Jobs, and How They Work TogetherRAG grounds answers in retrieved text; MCP connects AI apps to tools and live data. A clear comparison table, when to use each and how to combine them. · 7 min read
AI Coding
Claude Code, Codex, Cursor, GitHub Copilot and the practice of building software with AI.
AI CodingBest AI Coding Assistant in 2026: Picks by Use CaseThe best AI coding assistants in October 2026 by use case: free options, VS Code, terminal agents, open source and enterprise, with current prices and caveats. · 8 min read
AI CodingClaude Code vs Codex vs Cursor (and GitHub Copilot): Which AI Coding Tool in 2026?Claude Code vs Codex vs Cursor vs GitHub Copilot in October 2026: what each tool is, where it runs, current prices, default models and who should pick which. · 8 min read
AI CodingWhat Is Vibe Coding? Meaning, Origin, Risks and When It WorksVibe coding means building software by prompting an AI and accepting its code unread. Where the term came from, how it works, the risks and when to use it. · 5 min read
Local and Private AI
Running models on your own hardware: Ollama, LM Studio, vLLM, llama.cpp, GPUs and Macs for LLMs.
Local and Private AIBest Local LLM for Coding in 2026 (Picked by Your Hardware)The best local coding models for 16, 24-32 and 64 GB+ machines, with sizes, licenses and vendor benchmarks, plus how to plug them into Claude Code or your IDE. · 7 min read
Local and Private AILocal LLM Hardware Guide: How Much VRAM and RAM You Really NeedWork out the memory any local LLM needs: weights by quantization, KV cache for context, a sizing table from 3B to 120B, and how GPUs and Macs compare. · 8 min read
Local and Private AIOllama vs LM Studio: Which Local LLM Tool Should You Use?Ollama is the open-source, CLI-first runner for developers; LM Studio is the polished desktop app. Compare engines, APIs, platforms and licensing, and pick one. · 7 min read
AI Fundamentals
How AI actually works, in plain English: LLMs, transformers, tokens, embeddings, RAG, fine-tuning and the terms behind the headlines.
AI FundamentalsRAG vs Fine-Tuning: When to Use Each (and When to Use Neither)RAG gives a model knowledge; fine-tuning changes its behaviour. A decision table, costs as of October 2026, what vendors still allow and how to combine both. · 9 min read
AI FundamentalsWhat is llms.txt? The format, who uses it and whether AI actually reads itllms.txt is a proposed Markdown file that gives LLMs a map of your site. Here is the format, who publishes one, and what Google and AI tools really do with it. · 6 min read
AI Tools
Honest reviews, comparisons and the best AI tools for each job.
Prompt and Context Engineering
Getting reliable results from models: prompt patterns, system prompts and context engineering.
Prompt and Context EngineeringWhat Is Context Engineering? Techniques for Reliable AI AgentsContext engineering is curating everything an LLM sees, not just the prompt. Where the term came from, why context rots, and techniques for reliable agents. · 9 min read
Prompt and Context EngineeringContext Engineering vs Prompt Engineering: What's the Difference?Prompt engineering shapes the instructions; context engineering manages everything the model sees. Side-by-side table, worked example and when each matters. · 7 min read
AI for Business
Use cases, adoption, ROI and AI strategy for teams and companies of every size.
AI News
What changed in AI and why it matters: new models, releases and the weekly roundup.
