AI for Work
Plain guides to the ideas behind AI at work, written for people who use these tools rather than build them. No jargon, no hype, and no assumption that you already know what any of it means. Each one takes about ten minutes.
Read them in order if you are starting out. They build up, from how the tools think to what you can hand over to them. Each one also stands on its own.
Models and thinking effort
Two dials, and most people only ever touch one. Which model sets how good an answer can be, and how long it reasons is a separate setting with its own cost.
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What is an AI skill?
A small folder holding the method for one job, along with the examples and templates it needs. Write it once, then call it by name instead of retyping the brief.
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What is an AI project?
A folder that holds your files and your standing instructions, so every chat inside it already knows the background. Set it up once and work from it all year.
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What is vibe coding?
You describe a tool in plain English and the AI builds it. Excellent for proving an idea in ten minutes, and worth knowing exactly where it stops.
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What is a coding agent?
Two assistants with almost the same name and almost nothing in common. Which one you open decides how good the answer is, and most people open the wrong one.
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What is a work agent?
It takes the whole task rather than one question. Point it at a folder, describe the outcome, and come back to finished work instead of managing every step.
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AI interviews and bias
Candidates want an unbiased interview. They just do not believe AI can provide one. Why human interviews go wrong, and what the evidence actually shows.
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Why humans hate AI
People dislike AI output even when it is good. Five reasons, covering income, identity, control, the verification burden and effort as a signal of value.
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AI training as a solution looking for a problem
They start with training when they should start with the work. Eight steps from a vague brief to one workflow that actually got faster.
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