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Practical guides to AI automation: what agents really cost, what to log, and how to turn a niche dataset into a workflow that runs itself.
By Théo P. and Noah Schmidt8 min readNiche data: when a small dataset beats a big one
Owning data is not a moat. Keeping it current is closer to one. How to tell a niche dataset worth building from an expensive one, in five questions.
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By Sophie M. and Emma R.6 min readNo-code AI automation: from one sentence to a working workflow
Describe the job in plain language and get a workflow you can see, run and change. No nodes to wire by hand, and no black box to trust blindly.
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By Camille R. and Noah Schmidt7 min readHow to turn a dataset into a workflow that runs itself
Six steps from a file you check by hand to a price watch that refreshes, decides and asks before it acts. Plus the four traps that fail silently.
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By Théo P. and Nora A.8 min readAI workflow vs AI agent: what each one really costs
On a support ticket, one agent runs about 19 cents and a split-up workflow about 2. Why the gap exists, when it shrinks, and when the agent is the right call.
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By Théo P. and Inès L.8 min readHow to stop an AI agent from overspending
An alert is not a limit, and most provider spend caps only send a notification. What a real ceiling looks like, and how to prove yours would refuse a call.
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By Inès L. and Nora A.7 min readHow much should you budget for one AI agent?
What a step actually costs, how much margin to add, and why capping loops is a poor way to cap money. A practical way to get to a number you can defend.
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By Inès L. and Noah Schmidt8 min readWhat to log for every AI agent run
Your dashboard is not an audit trail, and standard AI tracing stores no prompts by default. What to record per run and per step so you can answer for it later.
Read moreBy Inès L. and Nora A.7 min readHow long should you keep AI agent logs?
Keep the small skeleton for years and the bulky content for months. What the EU AI Act really requires, and why most agents are out of scope entirely.
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