---
title: "Articles"
description: "My field notes: methods, lessons and limits observed while delivering business systems and working with agents."
url: "https://mc-stud.io/en/articles"
lang: "en"
updated: "2026-10-12"
---

Articles

# Field notes

Methods, lessons and limits observed while delivering business systems and working with agents.

October 11, 2026 5 min read Adoption AI

## [Joining a team, then upgrading the way it works with agents](https://mc-stud.io/en/articles/joining-a-team-and-installing-agentic-primitives)

How I join an existing team and install, sized to it, agentic work primitives: written context, recorded decisions, skills, workflows with human approval, proof before trust.

- I join a team through its rituals and its code, not through my tools.
- The first primitives are texts: a context file, recorded decisions, a glossary. Humans and agents read the same source.
- A recurring procedure becomes a skill; a long task becomes a graph with human approvals.

October 8, 2026 5 min read Data AI

## [Automating a sensitive process without losing traceability](https://mc-stud.io/en/articles/automating-a-sensitive-process-without-losing-traceability)

Automating a process that touches health data, payroll or invoicing is not about speed. It is about memory: knowing, afterwards, who decided what, under which rules and on which data.

October 1, 2026 5 min read Operational AI AI

## [From idea to pilot: running an AI project you can measure](https://mc-stud.io/en/articles/from-idea-to-pilot-a-measurable-ai-project)

Most AI projects do not die from a bad model. They die from a pilot with no success criterion. Here is how I build a pilot that leads to a decision.

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