MODULE 1.1 / 1 OF 9

AI Management: 2027, the year of managing agents

Explain why companies with agents need management, not just technology, using the 8 competencies and LOOP-R.

Area page: eventos.inema.pro/gestao-ia/en/ · in the menu: “2027: managing agents”

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01 / GESTAO-IAThe thesis: manage what you’ve created02 / GESTAO-IAThe third object of management03 / GESTAO-IAManage agents like people04 / GESTAO-IAThe 8 AI manager competencies05 / GESTAO-IAProcesses aren’t sacred: LOOP-R06 / GESTAO-IA2027 Training and Where to Start
The 6 topics in this module. At the end, you’ll fill out the area worksheet.
6 topics
~20 min reading and practice
1 area worksheet
1 ready-to-use prompt

1The thesis: manage what you’ve created

What it is

The INEMA.events.inema.pro AI Management area opens with a statement: "In 2026, we taught you to build agents. 2027 is the year to learn how to manage them." An agent is an AI that takes on a responsibility and does work with tools instead of just answering a question. Managing an agent means giving it a role, goal, context, tools, authority limits, and evaluation, as you have always done with people. The page also makes a tougher point: don’t put agents to work running old processes faster. Redesign the company for the speed of agents. The area brings together the thesis, the 8 AI manager competencies, LOOP-R, the 2027 AI Management Training, and the INEMA courses and projects that already cover most of the path.

Why learn it

Building an agent is no longer the bottleneck. What holds a company back is what comes next: who is responsible for it, what it can do on its own, how it is measured, and how much it costs. Understanding the thesis changes the question from "which tool?" to "how do I manage this?"

Key concepts

People management + process management + agent management; management, not just technology; redesign before accelerating.

In practice

An administrative manager already has three agents built by her team, each by a different person. No one knows who approves what they produce or how much they cost each month. Her problem isn’t building a fourth agent; it’s managing the three she already has.

✓ Do

List the AI agents or automations your team already uses, and write the name of the person responsible for the outcome next to each one.

✗ Avoid

Judging the area by its name: read the main idea on the page before deciding if it’s for you.

2The third object of management

What it is

The page shows the eras of management, each shaped by what companies needed to coordinate. From 1980 to 2000: people management—roles, responsibilities, tools, limits, and evaluation. From 2000 to 2020: process management—design, document, train, and execute. From 2020 to 2025: digital transformation—design, automate, and monitor. From 2025 to 2026: agent building, with prompts, skills, context, tools, and memory. In 2027, management coordinates people, agents, models, processes, and computing budgets at the same time. This area is for companies that already have agents and need to manage them; building the agents themselves is covered in the AGI-ready area.

Why learn it

Treating an agent as an IT project leaves out the part that determines the outcome: responsibility, limits, and measurement. Seeing the agent as the third object of management puts it on the agenda for the people who run the business.

Key concepts

Three shifts: building got easy, managing didn’t; the old process doesn’t deserve to be sped up; processes are no longer frozen.

In practice

An office assigns an agent to follow the same review process that three people used to handle on paper. The agent is fast, but it repeats steps that existed only because there used to be no other way. The right question would have been whether that process should still exist.

People1980–2000Processes2000–2020Digital2020–2025Building2025–2026Agent management2027
Each management era brought a new object to coordinate; in 2027, agents join people and processes without replacing them.

3Manage agents like people

What it is

The page’s central thesis is that managing agents is a lot like traditional people management, but with more measurement. The words change, not the logic: employee, position, responsibility, tools, limits, and evaluation become agent, role, goal, context, tools, autonomy, and evaluation. Two elements are added that people didn’t have: explicit context and graduated autonomy. Graduated autonomy means the agent doesn’t get "all or nothing" authority. It gets a defined scope—a limit on what it can decide on its own. And you can measure almost everything an agent does.

Why learn it

Many rules companies already know still apply, which shortens the path. Separation of duties, authority limits, and human review don’t need to be invented for agents; they need to be applied to them.

Key concepts

Accounting: the person who enters items doesn’t approve them; legal: the agent prepares, the lawyer decides and signs; healthcare: some decisions are outside the agent’s authority.

In practice

At an accounting firm, the agent enters and classifies the month’s documents, but another person still approves them. As the page puts it, the agent goes as far as the signature line, never beyond it.

Steps to try

  1. Open the area page beside this lesson.
  2. Take a job description for someone on your team and rewrite it for an agent, adding explicit context and authority limits.
  3. Write one sentence about what changed in your understanding.

4The 8 AI manager competencies

What it is

The page lists eight competencies in the order a manager uses them. Strategy asks what outcome we want; work architecture asks whether the process should still exist; delegation asks exactly what to give the agent; orchestration asks whether to use one agent or several, in sequence or in parallel. Governance decides what it does on its own, confirms first, or never executes; economics asks how much it costs to produce the outcome; evaluation asks whether it’s good and what it’s compared with; evolution asks what we learned from this run. The first four determine what the agent will do; the last four determine whether it keeps doing it. The 2027 manager oversees nine objects, from people and agents to computing budgets, and tracks metrics such as cost per outcome, rework, and autonomy rate.

Why learn it

The competencies work as a checklist: if one has no answer, that’s where the agent will fail. They also show you where to study, because the page points to the course that currently teaches each competency.

Key concepts

Strategy; architecture; delegation; orchestration; governance; economics; evaluation; evolution; cost per completed task.

In practice

A team chooses the cheapest model per token for a customer service agent. It makes mistakes and needs two tries per case. The page sums up the math: a cheap agent that makes mistakes and needs two tries costs twice as much as the price list suggests.

✓ Do

Score each of the 8 competencies for your main agent from 0 to 2, then circle the lowest score.

✗ Avoid

Jumping to the tool or course without understanding the problem the area addresses.

StrategyArchitectureDelegationOrchestrationGovernanceEconomicsEvaluationEvolution
The first four capabilities decide what the agent will do; the last four decide whether it keeps doing it.

5Processes aren’t sacred: LOOP-R

What it is

The page compares four generations of processes. Traditional processes were designed, documented, taught, and executed. Automated processes were designed, automated, and monitored. Agentic processes start with a goal; the agent executes and measures, then a person or agent evaluates. LOOP-R closes the cycle: execute, observe, critique, propose, experiment, validate, promote, and repeat. The process becomes a living system with versions, like software. There are three rules: don’t automate a bad process; people direct, agents execute; promoting and reverting are steps, not accidents.

Why learn it

Without the cycle, a company only asks "is the task done?" and learns nothing from each run. With it, each run suggests the next improvement, and a change that made the result worse can be rolled back without drama.

Key concepts

Four generations; LOOP-R; versioned process; promote and roll back; take it apart before automating.

In practice

A customer support team tests a new standard response suggested by the agent for two weeks. Since rework went down, they promote the change and make it the new version of the process. If things had gotten worse, they would have gone back to the previous version.

ExecuteObserveCritique and proposeExperimentValidatePromote
In LOOP-R, the execution itself proposes the next improvement: validated changes are promoted, and the cycle repeats.

62027 Training and Where to Start

What it is

The 2027 AI Management Training has ten modules and a final project, with the Gestão de IA course as its backbone. The modules cover the agentic company, process is not sacred, delegation and autonomy, agent economics and governance, and finally the company that learns through LOOP-R. The final project is Gestoria, a simulator for managing an agentic company in fourteen steps. The page is honest: the training packages a thesis; it is not a new course published today, and 75% to 80% of its foundation already exists in open courses and projects. This area brings together the Gestão de IA, Os Super-Agentes Chegaram, Super-Agentes na prática, Arquiteto de Trabalho com IA, LOOP-R, and Copilot + Agentes courses, as well as the Gestoria, LOOP-R, Arquiteto de Execução, Agentic OS, Kit do Arquiteto de Agentes, and Kit Copilot + Agentes projects.

Why learn it

Knowing what is already available keeps you from waiting for a course that has yet to be packaged. The suggested path is to start with the existing courses, following the module order.

Key concepts

Ten modules; Gestoria as the final project; 75% to 80% of the foundation already exists; the best first module is a process from your company.

In practice

A clinic owner wants to get started but does not know which course to take. They look at the appointment scheduling process, realize their question is about what the agent can do on its own, and start with the delegation and autonomy module, using Super-Agentes as a guide.

AI ManagementbackboneSuper-AgentesdelegationWork ArchitectureredesignLOOP-RevolutionGestoriafinal project
The training builds on what is already published: each column is a course or project that covers part of the thesis.

Criteria for reviewing your worksheet

Use this rubric after the lab. Each row asks for evidence; marking a topic as read doesn’t mean the worksheet is complete.

Criterion Expected evidence If it doesn’t meet the criterion
Main idea You can describe the area in one sentence that reflects the page. Reread the top of the page and topic 1.
Audience You can say who the area is for and who it isn’t for. Return to topic 2 and write an example from your work.
Core elements You can name the area’s core elements. Use the module diagram as a guide.
First step You chose a small, concrete step. Copy the first step recommended on the page itself.
Starting point You know which course, kit, or project to open first. Check topic 6 and the page’s access section.
Source Every statement in the worksheet comes from the page. Replace your assumptions with what the page says.

HANDS-ON / ~10 MIN

Your agent management worksheet

Keep the area page open: https://eventos.inema.pro/gestao-ia/en/. Use an example from your work, without personal or client data.

Prompt: agent management assessment

Paste it into Claude, ChatGPT, or Codex. Replace the words inside < and > with details about your situation.

Read https://eventos.inema.pro/gestao-ia/ (INEMA’s AI Management area). Use the page’s 8 competencies (strategy, work architecture, delegation, orchestration, governance, economics, evaluation, evolution) to assess the agent below.

My process: <describe the process and who handles each step today>
The agent: <what it does, which tools it uses, who approves>

Provide: 1) a table with competency | current state | what’s missing; 2) a list of what the agent does on its own, confirms first, and never executes; 3) three metrics to measure the agent (use the page’s list of metrics); 4) which module in the 2027 AI Management Training I should study first and why. Don’t make up details about my process. Ask questions where information is missing.

Completion criterion

Explain why companies with agents need management, not just technology, using the 8 competencies and LOOP-R. Keep the worksheet with the main idea, audience, first step, and starting point.

Open the area page ↗

Review what you’ve learned

A team built an agent in an afternoon, and now it runs the 2010 approval process, just faster. What would the AI Management area say?

View suggested answer

It delivers the error faster: before automating, the process needs to be taken apart and redesigned, and the agent needs an owner, authority limits, metrics, and a cost per outcome.

If your answer was different, return to the relevant topic and describe the difference in one sentence. This check won’t block your progress.

Module summary

  • People management + process management + agent management; management, not just technology; redesign before accelerating.
  • Three shifts: building got easy, managing didn’t; the old process doesn’t deserve to be sped up; processes are no longer frozen.
  • Accounting: the person who enters items doesn’t approve them; legal: the agent prepares, the lawyer decides and signs; healthcare: some decisions are outside the agent’s authority.
  • Strategy; architecture; delegation; orchestration; governance; economics; evaluation; evolution; cost per completed task.
  • Four generations; LOOP-R; versioned process; promote and roll back; take it apart before automating.
  • Ten modules; Gestoria as the final project; 75% to 80% of the foundation already exists; the best first module is a process from your company.

Check the source

Pages read on 28/09/2026. Area content changes; the official page takes precedence over this summary.

Module complete