Working with AI
Practical AI for everyone, not just ML engineers - prompting, agents, CLIs, MCP, skills and plugins, context and loop engineering, and getting real work done with AI. The hype-free user's manual.
Foundations 4
What an AI Assistant Really Is Demystify the thing behind the chat box: a model that predicts text, wrapped in tools and a loop. Once you see the three parts, agents stop being magic.
Prompting That Actually Works Stop guessing at magic words. Clear instructions, the right context, and a few reliable patterns get better results than any secret prompt.
When to Trust AI AI sounds equally confident when it is right and when it is making things up. Learn why, and the habits that catch the difference before it costs you.
AI Privacy and What Not to Paste Before you paste that document into a chatbot, know where it goes and what could come back to bite you. A practical privacy guide for everyday AI use.
Agents & Tools 7
AI Agents, Explained An agent is a chatbot that can act: it plans, uses tools, looks at the result, and tries again. Here is the loop, the power, and where to keep it on a leash.
AI in the Terminal (CLIs) Coding agents that live in your terminal can read files, run commands, and edit code on your say-so. The workflow, the habits, and how the main CLIs compare.
AI in Your Editor From autocomplete to a chat that knows your codebase: how editor AI like Copilot and Cursor actually helps, and the one discipline that keeps it from hurting.
What Is MCP (Model Context Protocol) MCP is the standard plug that lets an AI assistant talk to your tools and data, the same way USB-C connects any device. What it is, how it is shaped, and how to add one safely.
Skills and Plugins Two ways to extend an AI assistant: skills teach it reusable know-how, plugins give it new powers. What each is, how they differ, and how to add or write your own.
Context Engineering The model only knows what is in front of it. Context engineering is the craft of controlling that window: what to include, what to cut, and what to pull in on demand.
Loop Engineering The newest piece of the agent puzzle: designing the act-check-repeat loop so the AI corrects itself instead of confidently finishing wrong. A practical look at a term still settling.
Build With It 4
Vibe Coding Building software by describing what you want and letting AI write it. What vibe coding is, where it genuinely shines, and where it quietly bites.
RAG in Plain English Retrieval-augmented generation is how you get an AI to answer from your documents instead of its memory. The idea, the moving parts, and why it goes wrong.
Running AI Locally (Ollama) Run a capable model on your own machine: private, free per use, and offline. What Ollama does, how to start, and the honest tradeoffs versus the big cloud models.
Automate Your Work with No-Code and AI The crossover that makes both worlds click: a no-code automation that calls an AI step. Triage, summarize, and draft on autopilot, with guardrails so it does not run wild.