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PRACTICAL TRAINING · AI AGENT MANAGEMENT · INEMA V2

It’s not enough to create agents.
You also need to manage them.

Learn how to delegate work to the AI with a clear goal, the right limits, and supervision that fits your week.

From the 7 principles to the sheet for your first agent: visual explanations, cases from 10 areas, copy-ready examples, and a final project.

THE 7 PRINCIPLES

A cycle, not a list.

01Intentionwhat and why
02Contextthe minimum needed to get it right
03Reliable datathe source of truth
04Success criteriawhat’s considered ready
05Autonomy with limitsfrom N0 to N4
06Observationreport and failures
07Human supervisionthe cycle that evolves
intenção → contexto → dados → critério
→ autonomia → observação → supervisão ↺
4progressive learning tracks
8complete modules
48topics with hands-on practice
6–8 hestimate with exercises
YOUR JOURNEY

From turning point to an agent in production.

Follow in order to reach the final project with your agent sheet ready. Already use agents? Enter the path that solves your next challenge.

Intention and contextData and success criteriaAutonomy withlimitsObservation andsupervision
The 7 principles form a cycle: what you observe during supervision feeds back to adjust the agent’s intention and rules.
YOU WILL BUILD

Your first agent sheet, tested and supervised.

The final project turns a real task from your work into a well-managed agent: mission, house rules, source of truth, definition of done, calculated autonomy level, report, triggers, and a review ritual. Cases from 10 areas follow your journey, from a clinic to a marketing agency.

  1. Choose a frequent task, with a visible output and cheap errors.
  2. Answer the 7 questions and calculate the autonomy level.
  3. Run the 3 tests before trusting—and adjust one rule at a time.
  4. Supervise the first week with a failure log.
READY-TO-PRACTICE TOOLS

Open, fill in, use.

All free, no login, running in the browser. The skill is optional for those using Claude Code in the terminal.

Study with your own trail.

Mark topics as read, flag questions, and select excerpts from the explanations to highlight or take notes. In My learning journey, collect your notes, export a backup, and pick up from the last topic.

Progress measures topics marked as read; it is not a certification of mastery. Do the exercises before opening the answers. Your notes stay in the browser and are not sent to a server.

Prerequisites: none technical knowledge required. Just have used ChatGPT, Claude, or Gemini at least once. Every new term is explained the first time it appears.

Sources and editorial criteria

The course starts from three project 7PA texts: a report on the new work logic with AI agents, a critical analysis that separates the promotional layer from what is technically relevant, and a synthesis of the 7 principles. The originals are in github.com/inematds/7pa/conteudo. Examples, exercises, diagrams, and cases were developed for this course.

The autonomy level calculation rule (N0 to N4) and the criteria for leveling up are an educational proposal from the 7PA project, designed to start safely. They are not a technical standard or a market benchmark. Adapt to your context, always in the direction of more control when in doubt.

Mentions of programming agents (Claude Code, Codex, CLAUDE.md, AGENTS.md, permission modes) describe capabilities available in September 2026. Names and options may change depending on the version and the account. Duration estimates include hands-on practice; they are not measurements of students.

Project tools: Agent Sheet, sheet gallery, guide to the 7 principles and The Secret of the 7 Principles.