The LinkMap
98 terms and the lines between them.
Understand the system
behind the headline.
Fresh from the desk.
What happens to what you type into an AI chatbot? A plain guide to AI and your privacy in 2026
When you type into ChatGPT, Gemini, or Claude, your words leave your device and reach a company''s servers — where they may be stored, reviewed by a person, or used to train future models. Here is what actually happens in plain terms, and the simple settings that put you back in control.
That phone call in your loved one's voice might be AI: a plain guide to voice-cloning scams (and the one habit that protects you)
AI can now copy a familiar voice from a few seconds of audio, so a real-sounding phone call is no longer proof of who is calling. Here is what that means in plain terms, and a simple habit to keep you safe.
AI agents that act for you: a plain guide to the new “do it for me” assistants (and how to stay in control)
A new wave of AI “agents” does more than answer questions; it takes actions for you across your apps. Here is what that means in plain terms, and a simple checklist to stay in control.
Why AI chatbots sound so sure when they're wrong (and a 5-minute habit to check)
AI chatbots state false things in the same confident voice they use for true ones. Here is why that happens and a simple five-minute habit to catch it before you act.
The AI Infrastructure Cost Dashboard Small Teams Need in 2026: Tokens, RAG, Cloud, and Review Gates
A decision-oriented 2026 guide to the AI infrastructure cost dashboard a small team actually needs. Maps the four cost lines worth one page — LLM tokens, RAG / vector database, cloud compute and storage, and governance review gates — onto a concrete unit metric for each and a clear place to put a review gate, grounded in Anthropic, OpenAI, Pinecone, AWS, and FinOps Foundation documentation.
AI Workflow Automation for Non-Engineering Teams in 2026: What to Automate, What to Keep Manual, and Where It Breaks
A decision-oriented 2026 guide to AI workflow automation for non-engineering teams. Maps what Zapier, Microsoft Power Automate, Make, and Google Apps Script actually do onto a concrete playbook for what to automate fully, what to gate behind a human approval step, and where automation predictably breaks — with a one-page checklist by situation.
A glossary you navigate, not memorize.
Terms are learned by their distance from one another. We render the glossary as a network — click a node to open the term, every term links back into the map.
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