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AGI-ready: Your Work Becomes Managing Agents
Explain the difference between giving step-by-step instructions and delegating to an agent, using the ladder of intention, objective, prompt, skill, context, tools, memory, permissions, and evals.
Area page: eventos.inema.pro/agi-ready/en/ · in the menu: “directing agents”
1AI Has Stopped Waiting for Instructions
What it is
The AGI-ready area opens with the line: “AI has stopped waiting for instructions. Your work becomes managing agents.” The page recalls how, for three years, we tried to put the entire operation into one giant prompt. With agents that work for hours or days, the game changes: you state the destination, and the agent finds the way. An agent here is an AI that takes on a responsibility, plans, executes, monitors, and returns with the result. This area brings together what is changing, the mental model to keep up, and INEMA courses and projects to help you get started today, without programming.
Why learn it
If you keep operating AI only through short commands, you compete with the agent itself. If you learn to delegate, you multiply your own capacity, and you can practice that.
Key concepts
Destination, not route; work for hours or days; delegate; manage agents without programming.
In practice
An analyst used to give AI five separate commands every month to put together the sales report. They started handing over the full responsibility, with an objective and a definition of done, and reviewing only the result.
✓ Do
Write one sentence stating the destination of the work you repeat most often, without describing any steps.
✗ Avoid
Judging the area by its name: read the main idea on the page before deciding if it’s for you.
2A Task Becomes a Responsibility
What it is
The page describes six changes: the first three come from people inside the labs, and the next three are what those changes mean at your desk. At your desk, the first is that a task becomes a responsibility: you stop asking “make this spreadsheet” and start handing over “take care of this month’s reconciliation.” The second is that trust becomes a curve, not a switch: what the agent decides on its own, what it suggests for you to approve, and what it never touches, with an owner for each row. The third is that your value shifts to what AI cannot decide: setting the objective, choosing what matters, stating what must not happen, and judging whether the result is good. The page also cites, as an external source, an English-language video about the article “Alien Minds” by Jakub Pachocki, OpenAI’s chief scientist, who acknowledges that capability is growing faster than control.
Why learn it
Without this shift in how you define the work, you keep writing recipes for a tool that can already take care of the result. Without a trust curve, you either lock everything down or give it too much freedom.
Key concepts
Task × responsibility; trust as a curve; trust matrix; role of an agent manager.
In practice
A finance coordinator tells the agent, “take care of this month’s reconciliation.” It classifies items on its own, suggests adjustments for the coordinator to approve, and never touches payments, with a named owner for each row.
3The End of the Prompt as the Entire Program
What it is
The page warns that talking about the “end of the prompt” is an overstatement: the prompt is not disappearing. What is ending is the prompt as the entire program, with all the operation’s intelligence written in natural language, as people did between 2023 and 2025. Micro-prompting means teaching every step: do A, then B, then C. If one step is missing, the result is wrong. Now the prompt states the objective, what matters, the constraints, the resources, and what counts as a good result. It works alongside the Skill, which is reusable knowledge or a procedure: instructions, reference files, templates, scripts, and guidance on using tools.
Why learn it
Separating the prompt from the Skill keeps you from rewriting the same nine steps every time. The prompt stays short, and quality comes from the operating manual the agent already has.
Key concepts
Prompt = what I want now (the brief); Skill = how our organization usually does it; Prompt → Context → Skill → Agent Engineering → Orchestration.
In practice
You say, “turn this research into a presentation for Brazilian business owners.” The presentation Skill provides the story structure, slide standards, writing rules, and review process. The agent does a much better job with the prompt and the Skill.
Steps to try
- Open the area page beside this lesson.
- Take your longest prompt and split it into two columns: what changes with each request (prompt) and what stays the same (a Skill candidate).
- Write one sentence about what changed in your understanding.
4The Ladder of a Working Agent
What it is
The page lays out the architecture in levels, using one example throughout: increasing course conversions. Intention answers “why?”; objective answers “what?”; the prompt guides this run; the Skill explains how to do the work well, consistently. Next come context (what it needs to know), tools (the agent’s hands, such as a browser, CRM, spreadsheets, APIs, and MCP), memory (accumulated experience), and finally permissions and evals. Evals are tests that show whether the result meets the success criteria. Along with limits, human approval, and logs, they form quality control. As the page puts it, we do not want only a powerful agent; we want an agent we can control.
Why learn it
When an agent fails, the ladder shows which rung has the problem: missing context, a missing Skill, or missing criteria. Without it, every failure leads to a longer prompt.
Key concepts
Intention; objective; prompt; skill; context; tools; memory; permissions and evals; a human sets the destination and judges the result.
In practice
In the page’s example, an agent with five Skills (research, copy, campaign, video, and analytics) gets a short sentence: "launch this course for Brazilian business owners and get 200 enrollments". That sentence triggers a huge amount of work because the how is already in the Skills.
✓ Do
Fill in the nine steps of the ladder for one of your goals, and mark the step that is empty today.
✗ Avoid
Jumping to the tool or course without understanding the problem the area addresses.
5Six moves for this week
What it is
The page turns the change into six tips that fit into your schedule. First: separate tasks from responsibilities in your list of requests to AI. Second: rewrite a prompt as a delegation, with the goal, what matters, what must not happen, resources, and how you will judge the result. Ask for a plan before any action. Third: if you have explained the same procedure three times, turn it into a Skill with a manual, template, checklist, and examples. Fourth: write the trust matrix; fifth: give context before tools; sixth: define what "good" means before you run it.
Why learn it
These are small, verifiable steps, not a months-long project. Each one is the first step toward a skill the page lists: thinking in processes, directing AI, building agents, integrating systems, evaluating and supervising, and understanding the business.
Key concepts
Task × responsibility; delegation in five parts; a Skill for what repeats; trust matrix; context before tools; evaluation before running.
In practice
A consultant realizes she has explained three times what she wants in meeting reports. She puts the template, a checklist, and two examples into a Skill. The fourth time, the request fits in one line.
6Courses, projects, and three doors
What it is
This area brings together courses for people who make decisions but don’t code, and courses for people who want to build. To start: Os Super-Agentes Chegaram (6 lessons), Super-Agentes na prática (8 lessons), and Arquiteto de Trabalho com IA (8 lessons). To work with the tools: Arquitetura de Intenção, Computer Use com o GPT-6 Astra, Subagentes e Superpowers, and the recording Agentes do Zero: Fundamentos (5 days). Projects with code and a guide include OS Coach, os-agentes, Kit do Arquiteto de Agentes, INEMACCBOT, Content2Video, WebMCP Readiness, Fable 5.1 · Prompt de Sistema, and STORM Research. The page ends with three doors into the same ecosystem: INEMA.CLUB (open courses), INEMA.VIP (community), and INEMA.PRO (hands-on platform).
Why learn it
Each project is a working piece of the architecture: INEMACCBOT shows the trust matrix in code, while WebMCP Readiness shows the "tools" side from the website’s perspective. Seeing a finished example helps you make your first delegation sooner.
Key concepts
Start with Os Super-Agentes Chegaram; open courses in Portuguese; projects with code and a guide; INEMA.CLUB, INEMA.VIP, INEMA.PRO.
In practice
A manager with no programming experience first takes Os Super-Agentes Chegaram, writes a delegation brief using the six questions, and only then opens Kit do Arquiteto de Agentes to turn the agent into a one-page specification.
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 First Real Delegation
Keep the area page open: https://eventos.inema.pro/agi-ready/en/. Use an example from your work, without personal or client data.
Prompt: Turn a Request into a Delegation
Paste it into Claude, ChatGPT, or Codex. Replace the words inside < and > with details about your situation.
Read https://eventos.inema.pro/agi-ready/ (the AGI-ready area of INEMA), especially the architecture (intention, objective, prompt, skill, context, tools, memory, permissions, and evals) and the six tips.
My request today, as I usually write it: <paste your step-by-step prompt here>
My area and what already exists: <company, customers, available tools>
Rewrite it as a delegation with five parts: objective, what matters, what must not happen, available resources, and how I will judge the result. Then: 1) point out which parts stay the same and should become a Skill; 2) build the trust matrix (decides on its own | suggests and I approve | never touches); 3) say which rung of the architecture is missing. Ask for a plan before any action, and do not make up information about my company.
Completion criterion
Explain the difference between giving step-by-step instructions and delegating to an agent, using the ladder of intention, objective, prompt, skill, context, tools, memory, permissions, and evals. Keep the worksheet with the main idea, audience, first step, and starting point.
Open the area page ↗Review what you’ve learned
Your request to AI has 30 numbered steps, and the result still comes out wrong if one step is missing. What does the AGI-ready area suggest?
View suggested answer
Move up a level: state the destination (objective, constraints, resources, and success criteria) and put the “how to do it well” into a reusable Skill, instead of teaching every step.
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
- Destination, not route; work for hours or days; delegate; manage agents without programming.
- Task × responsibility; trust as a curve; trust matrix; role of an agent manager.
- Prompt = what I want now (the brief); Skill = how our organization usually does it; Prompt → Context → Skill → Agent Engineering → Orchestration.
- Intention; objective; prompt; skill; context; tools; memory; permissions and evals; a human sets the destination and judges the result.
- Task × responsibility; delegation in five parts; a Skill for what repeats; trust matrix; context before tools; evaluation before running.
- Start with Os Super-Agentes Chegaram; open courses in Portuguese; projects with code and a guide; INEMA.CLUB, INEMA.VIP, INEMA.PRO.
Check the source
Pages read on 28/09/2026. Area content changes; the official page takes precedence over this summary.