A notebook on AI, automation, finance & learning
Practical, tested, no hype. Real examples, explained step by step, so you can try them yourself.
Give every agent a clear role, let a main agent coordinate the work, keep irreversible decisions with you, and bring in the whole team only when the task is worth the extra tokens.
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Choose a model that can do the job, tune its thinking effort, and compare the cost of the completed task. A lower token price is only part of the bill.
Keep the rules, the unfinished work and the reasons behind your decisions in your project folder. Then start a new AI chat with a clear place to pick up.
Prompt, context window, token, RAG, API, MCP and Markdown. Each one explained in a sentence, with an everyday picture and what it means when you use AI.
The code button in ChatGPT and Claude lets the AI work with a folder on your computer, and you don't write a single line. We ran the same request in both apps: same folder, same €1,026 quote, and both asked before sending.
We typed 11 words and the agent used 150,194 tokens. About 99% went to re-reading, and the answer itself was the small part. Here is why, and the habits that keep it lean.
Eleven words, and the quote was made, checked and ready to send. The clever part wasn't the prompt. It was a folder with four files. Here is the whole setup, step by step.
Who's behind the corner
He works where finance, processes and technology meet: financial foundations for growing companies, an ERP connected to the business, and AI with human judgement. The rigour comes from seven years in a family office.
The Thinking Corner is where he tests things in the open and writes down what works.
psst Short reels on Instagram, longer notes here.