Blog
Notes on automation, without the hype.
What I learn from real projects, written so it's useful even if we never work together. About AI, about simple rules, and about when each one is worth it.
AI or plain automation? When to use which.
The question I get most this year isn't "can this be automated?" but "shouldn't we use AI for this?". Most of the time the answer is no. The rule I decide by, with a table and three examples.
ReadWhere AI goes wrong, and how to build around it.
A language model fails differently from a program. It doesn't stall, it doesn't throw an error: it answers nicely, confidently, and sometimes wrongly. The four safety nets I put in every time.
ReadWhat AI actually costs inside an automation.
The good news: the AI part is almost free. The less good news: the AI part isn't what's expensive. Where the money goes, and how I work it out for a client.
ReadAI and your company's data: what leaves the building and what doesn't.
"If I add AI, do my data end up in America?" Good question. The short answer: it depends how you build it, and you get to choose. Three options and five questions for anyone selling you AI.
ReadTen tasks: five without AI, five with.
A short list from real projects, so you can see the difference at a glance. And the pattern that repeats across all ten.
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The no-math-no-money audit.
The process audit costs you nothing. If I can't show you, in plain numbers, where automation saves you real hours — we shake hands and you walk away with a map of your own processes. You risk thirty minutes. That's the whole downside.
AttilaHelloAttila · Odorheiu Secuiesc