AI Decode Wire explains how everyday AI tools actually behave, and how to check them, in plain language with the sources linked. Pick the line that matches what you are trying to do.
Understand why AI behaves the way it does
These don’t go stale quickly, and most of the how-to guides assume them.
- Why AI makes things up: why inventing and recalling are the same operation, and the habits that catch it.
- Why AI gives different answers to the same question: answers are drawn by weighted chance, and you can use the variation as a check.
- Why AI forgets mid-conversation: what a context window is and why answers slip long before it is full.
- AI agents explained: the loop that lets a model take actions, and where the failures come from.
- Reasoning models explained: what the visible “thinking” is, what it costs, and when the wait is worth it.
- Multimodal AI explained: what happens to the photo you upload.
Get better answers from the tools you already use
- A practical guide to prompting: the techniques that reliably change output quality, and the ones you can ignore.
- Nine prompts for work that check their own answers: copy-and-adapt prompts for summaries, emails, policies, tables and meeting notes.
- How to fact-check AI output in five minutes: a routine, with a worked example of a summary that misread a court order.
- How to summarise a long document without losing the point: five prompts, each with a one-minute check.
- How to use AI on a spreadsheet and still trust the numbers: make it calculate, not read, then check one number you already trust.
Choose and pay for AI tools
- What “free” actually gets you on ChatGPT, Claude and Gemini: what each free plan includes and where to see your own limit.
- Tokens, pricing and why your AI bill looks like that: one chat worked through at current prices.
- Why “open source” AI usually isn’t: the three-part test, and the licence clauses that matter.
Connect AI to your own documents and systems
- What “upload your documents” actually does (RAG): why the model never reads the whole file, and when to skip retrieval.
- Fine-tuning vs RAG vs prompting: a symptom-to-fix table for “I want an AI that knows my business”.
- What an MCP connector is: the difference between a remote connector and a local server, and what to check before you connect.
If you run a business
- The three questions that decide what AI should touch first: a screen for where AI genuinely helps, and where a script does better.
- Run a restaurant? Alongside the publication, I redesign restaurant websites so the menu, hours and ordering work on a phone. See the before-and-after work.
For the sceptics
- Six AI myths that refuse to die: beliefs the vendors’ own documentation contradicts.
How this site works
Every article says what it is based on and links its sources; nothing is presented as tested unless it was. Read the editorial policy and the AI-assisted content policy, and tell us if you spot an error. Corrections are made in the open (corrections policy).