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TRACK 04

The secret and the project

People management under a different name, code agents, and your agent in production.

2modules
12topics
110 minestimated with practice
Practicalprogressive level
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People managementCode agentsYour sheetAgent in production
People management under a different name, code agents, and your agent in production.

Track map

4.1~50 min

🧭 The secret: you already know this

It’s not a new discipline

4.2~60 min

🧭 Final project: your agent in production

From the sheet to the routine

Detailed content

MODULE 4.1

The secret: you already know this

Discover that the 7 principles are written people management for people who don’t guess anything.

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What it is

Replace the word “agent” with “new employee” and reread the 7 principles: nothing feels strange to someone who has already led others. Intention describes the role; context is onboarding; data is the official system; criteria are goals; autonomy is the scope of authority; observation is the report; supervision is the 1:1 meeting. The report on “the new era of AI” gave a new name to old practices.

Why learn

People who think managing agents means learning everything from scratch get stuck before they even start. Realizing you already know a good part of the method removes fear and speeds up your first delegation. And it gives you a simple test: if you wouldn’t delegate like that to a person, don’t delegate like that to an AI.

Key concepts

  • Role: intention—why the position exists.
  • Onboarding: context—what you teach on day 1.
  • Scope of authority: autonomy—“up to R$ 500 you decide.”
  • 1:1: supervision—review, correct, promote or not.
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What it is

A new employee infers a lot: they observe coworkers, notice the company tone, and ask in the hallway. The agent doesn’t do any of that; it works only with what’s written in the instructions and the data it has access to. Everything a person would infer has to become text: the tone, the source that counts, what to do when information is missing, and when to stop.

Why learn

Most agent mistakes come from what “seemed obvious” to the person who delegated. With a person, lack of clarity costs a lot by going slowly; with an agent, it costs immediately and at scale. Listing the implicit is the cheapest way to avoid this mistake.

Key concepts

  • Tone: how you talk to a customer—formal or friendly.
  • Source: which spreadsheet or system is the one that counts—and which one isn’t.
  • If something is missing: what to do when the data doesn’t exist.
  • Stop: what situation makes it call you.
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What it is

Code agents, like Claude Code and Codex, are AI programs that work inside a repository—the folder of a project with all its history. Anyone who uses these agents practices the 7 principles every day: the plan mode (the agent proposes before changing anything), the CLAUDE.md or AGENTS.md (a file with the project rules), the repository as the source, tests (automated checks), permissions, failure log, and review.

Why learn

This shows the method isn’t stage theory: it already works in production, in the hands of thousands of people. Even those who don’t program benefit by copying these practices into other areas. And programmers gain a vocabulary to explain their own routine to managers.

Key concepts

  • Plan mode: intention—combine before executing.
  • CLAUDE.md: context—the house rules in a file.
  • Tests: the readiness criterion—“done” is whatever passes the verification.
  • Review: supervision—humans approve the irreversible.
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What it is

In Claude Code, permission mode defines what the agent can do without asking. In plan, it only reads and proposes; in default, it asks for approval for every edit or command; in acceptEdits, it edits files on its own, but commands still ask; in bypassPermissions, it allows everything. It’s the same N0 to N4 autonomy ladder—just with a button instead of a conversation.

Why learn

Choosing the “on the fly” mode is the most common mistake people make when they start with code agents. With the ladder, the choice becomes rule-based: the level comes from the action and the risks, not from urgency. And it becomes clear what has to happen in order to move up a rung.

Key concepts

  • N0 and N1: plan—only reads and proposes.
  • N2: default—approves every edit and command.
  • N3: acceptEdits—edits on its own; commands ask.
  • N4: only with hooks and isolated environment.
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What it is

Three pieces turn the principles into real configuration. The instruction file (CLAUDE.md for the Claude Code, AGENTS.md for Codex and others) sits at the root of the project and is read in every session. Tests are commands that automatically verify whether the work is correct. Hooks are triggers that run before an action and can block it; the allow and deny rules in the configuration grant or prohibit actions.

Why learn

Writing “don’t deploy” in the conversation isn’t enough: the conversation ends and the rule disappears. In the instruction file, it applies every time; as a deny rule or hook, it applies even if the agent forgets. It’s the difference between asking and guaranteeing.

Key concepts

  • CLAUDE.md: house rules read in every session.
  • Tests: a readiness criterion that doesn’t depend on opinion.
  • Deny: an action prohibited by permissions.
  • Hook: a lock that blocks the irreversible before it happens.
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What it is

The 7 questions are the same ones a good manager always asked. Without intention, the agent efficiently does the wrong task; without a source of truth, it picks the information on its own and picks badly; without criteria, it says “done” and you only find out later that it wasn’t. And the design of the principles is a circle: supervision feeds back into intention, each mistake becomes a rule, and each clean week becomes a rung of autonomy.

Why learn

Blaming “the AI” prevents you from fixing what’s within your reach: delegation. When you treat each error as a missing rule, the agent improves week after week without switching tools. The circle turns the Agent Sheet into a living process, not a form you fill out once.

Key concepts

  • Without intention: it does the wrong task well.
  • Without a source: it picks bad information.
  • Without criteria: a “done” that isn’t actually done.
  • Circle: the observed error becomes a new rule.
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MODULE 4.2

Final project: your agent in production

Take a real task from your choices through the first supervised week, and then through multiple agents.

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What it is

The first agent in production should handle a frequent task, with visible output and cheap errors. Frequent, so you learn fast; visible, so you can check the result with your own eyes; cheap, so an error only costs a correction—not a customer. One task per sheet: if you came up with three, start with the one with the lowest risk.

Why learn

Starting with the most important process sounds ambitious, but it mixes risks and hides where the mistake was born. A small task gives, in a few days, real data to adjust the sheet. The confidence you earn from it is what unlocks the bigger tasks afterward.

Key concepts

  • Frequent: it happens every week or every day.
  • Visible: you check the result with your eyes.
  • Cheap error: a failure costs only a correction.
  • One at a time: one task per sheet.
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What it is

The agent sheet brings together the 7 answers, the calculated autonomy level, the ready-to-use instruction, 3 tests, and the supervision checklist. There are two paths. The web Sheet (inematds.github.io/7pa) works in the browser, with presets for 10 areas such as clinic, store, and real estate. The skill /ficha-agente is for people using Claude Code in the terminal (the text command screen). It asks the same interview questions and saves everything into a file AGENTE.md.

Why learn

The sheet forces you to answer the questions that usually get left for later, such as what to do if data is missing and when the agent stops. The level is not a guess: it comes from a fixed rule that only goes down. And the result already includes an instruction to paste and tests to run.

Key concepts

  • Web sheet: in the browser, with presets for 10 areas.
  • Skill: /ficha-agente in the Claude Code terminal.
  • Preset: your area’s ready sheet to adjust.
  • AGENTE.md: file with sheet, instruction, and tests.
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What it is

Every sheet comes with 3 tests before you trust it: missing or contradictory information from the source, a forbidden request, and an alert situation. You run each one and compare it with the expected behavior. If it fails, adjust one rule at a time and run again—so you know which change fixed it.

Why learn

An agent that passes the easy case can still make up data in the difficult one. The tests simulate exactly the moments when the error becomes costly. Changing one rule at a time prevents the “fix one thing, break another without noticing” effect.

Key concepts

  • Test 1: if data is missing, it doesn’t invent.
  • Test 2: forbidden request; it refuses and calls you.
  • Test 3: alert; it stops and calls you.
  • Adjust: one rule at a time, then repeat.
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What it is

Auditing means evaluating an instruction that already exists (a saved prompt, a CLAUDE.md, a AGENTS.md, or a custom GPT) against the 7 principles. Each principle gets a score of 0 (missing), 1 (vague), or 2 (clear), with the excerpt that proves it. Then you apply the level rule and check whether the current autonomy is above what the rule allows.

Why learn

A lot of people already have agents running without ever checking what they can do. Auditing finds, within minutes, the most common risk: autonomy greater than the task justifies. And it comes with ready-to-paste corrections, without needing to redo everything.

Key concepts

  • Score: 0 missing, 1 vague, 2 clear, with evidence.
  • Level: the rule applied to what the text allows.
  • Main finding: autonomy above the rule.
  • Corrections: at most 5, starting with the riskiest one.
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What it is

Turning on the agent isn’t the end—it’s the start of the trial period. During the first week, you check every day for 2 minutes, log each failure in one line, and at the end of the week adjust a rule. The failure log has dates, what broke, the smallest correction, and the changed sheet rule.

Why learn

The most expensive mistakes show up in the first few days, when the instruction encounters real cases you didn’t predict. Short, daily supervision catches these errors early. And the log becomes the proof for leveling up afterward, rather than leveling up based on impression.

Key concepts

  • Daily: 2 minutes checking the report.
  • Log: one line per failure.
  • Weekly: adjust only one rule.
  • Promotion: only with clean weeks recorded.
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What it is

With the first agent running, more show up. Then the organization has three parts: people, processes, and agents. An agent map lists each one with its task, level, source of truth, human owner, and who it delivers to. Each agent keeps its own sheet; the map shows how they fit together.

Why learn

Without a map, agents overlap, read different sources for the same data, and no one knows who’s responsible for them. With a map, each agent has an owner and each delivery has a destination. It’s the same logic as the org chart, now including who isn’t a person.

Key concepts

  • People: owners who approve and respond.
  • Processes: the path the work takes.
  • Agents: each one has its own sheet and level.
  • Map: who does what, with which source and owner.
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