Theme

Font

Size

Text width

Line spacing

Controls accent

0 of 00%
Start / Track 1
TRACK 01

Foundations

Turn a good result into a teachable process.

2modules
12topics
100 minestimated with practice
Practicalprogressive level
0 of 00%
Understand the processPractice the conceptCheck the deliveryConsolidate the skill
Turn a good result into a teachable process.

Track map

1.1~45 min

🧩 Understand what a skill teaches

The recipe becomes a process

1.2~55 min

🧩 Start with the approved result

Define what “done” means

Detailed content

MODULE 1.1

Understand what a skill teaches

Separate instruction, tool, and result before automating.

0 of 00%

What it is

A skill is a reusable procedure that guides an agent through a task. In the video analogy, the result is the pancake, the agent is the cook, and the skill is the recipe. The file records decisions you don’t want to explain again with every request.

Why learn

Without a procedure, the agent has to fill in gaps: size, format, sources, and quality criteria. Recording these choices reduces avoidable variation. This doesn’t make generation infallible: different ingredients and unavailable tools still change the outcome.

Key concepts

  • Input: the received material.
  • Process: the actions and decisions.
  • Output: the delivered artifact.
  • Acceptance: evidence that the delivery is fit for purpose.
Study this topic and do the exercise →

What it is

A prompt asks for something in this interaction. A skill stores a specialized procedure. AGENTS.md records durable project guidance. A tool carries out a concrete capability, like reading a file or querying a service. These pieces complement each other.

Why learn

When everything goes into the global rule, details of one task start influencing unrelated tasks. When everything stays in the prompt, you repeat instructions. Separating roles helps you find the correct place for each correction.

Key concepts

  • Prompt: intention and execution data.
  • Skill: a reusable method.
  • AGENTS.md: project conventions.
  • Tool: capability and access.
Study this topic and do the exercise →

What it is

The best first candidate is a frequent task with a definition of “good” that you can demonstrate. It doesn’t need to be complex. A video description, a text review, or a short report already lets you learn the whole cycle.

Why learn

Starting with “manage my business” mixes planning, writing, accounting, and publishing. You can’t locate the mistake. A smaller task produces an assessable artifact and gives faster feedback before connecting important systems.

Key concepts

  • Frequency: how many times it repeats.
  • Cost of the error: what a failure causes.
  • Observability: how to recognize success.
  • Scope: where the task ends.
Study this topic and do the exercise →

What it is

The contract describes what needs to be delivered, what will be produced, and what happens when information is missing. In our lab, the CSV contains date, channel, and value. The output includes observed period, total, totals by channel, and pending items.

Why learn

Missing data should not turn into silent assumptions. If “value” doesn’t exist, the skill can’t calculate revenue. A useful response identifies the missing field, stops only the dependent step, and preserves the original material.

Key concepts

  • Precondition: minimum required data.
  • Post-condition: required content.
  • Invariant: something that can’t change.
  • Predicted failure: a useful response without making things up.
Study this topic and do the exercise →

What it is

The six steps are the author’s practical proposal: start from the result, define the task, calibrate freedom, verify, compare configurations, and incorporate feedback. “Better than 99%” is the promotional title of the reference, not a measured result in this course.

Why learn

The video shows different outputs across models in a visual task. This is a useful case study, but it doesn’t establish a universal ranking. Observed times from that one run also don’t guarantee duration, price, or quality for your account.

Key concepts

  • A report is not the same as a benchmark.
  • Repeatability requires multiple cases.
  • Tools depend on real access.
  • Self-evaluation requires evidence.
Study this topic and do the exercise →

What it is

You’ll work with synthetic data and local files. Download the kit from the homepage, open the folder in Codex, and keep input, output, and evidence separate. The exercise doesn’t require a paid API or a connected CRM account.

Why learn

Separating folders makes it possible to redo an execution without replacing the original. With each change, you can compare the previous report with the new one and verify whether the fix had any unintended effect.

Key concepts

  • dados/: immutable inputs.
  • saidas/: execution results.
  • evidencias/: tests and observations.
  • SKILL.md: versionable procedure.
Study this topic and do the exercise →
View Complete →
MODULE 1.2

Start with the approved result

Reverse-engineer a delivery and turn preferences into criteria.

0 of 00%

What it is

Reverse engineering starts with an output you consider good and the inputs that produced it. An isolated report shows the appearance, but doesn’t explain filters, formulas, and decisions. Also save the data’s origin.

Why learn

Copying only the format can reproduce an elegant mistake. Before turning the example into a reference, check numbers, dates, and context. A good reference example has known quality, not just approval from general impressions.

Key concepts

  • Approved output: destination.
  • Original input: source.
  • Decisions: the path.
  • Validation: confidence in the example.
Study this topic and do the exercise →

What it is

Ask how the work was done: which sources were used, which records were excluded, how duplicates were handled, and who approved the result. Ask questions that make hidden decisions explicit, rather than asking only for a “professional style”.

Why learn

Someone who has done a task for years takes shortcuts without noticing them. The agent doesn’t know those shortcuts. A short interview recovers tacit knowledge and helps uncover dependencies that must exist before automation.

Key concepts

  • Origin: where each piece of data came from.
  • Transformation: which rule changed the data.
  • Exception: when the rule isn’t enough.
  • Acceptance: who decides and with what evidence.
Study this topic and do the exercise →

What it is

“I want something good” does not allow you to consistently reject an output. Break quality into observable items: the presence of the period, alignment between the data and the table, the summary length, and the clarity of the outstanding points. Separate mandatory requirements from preferences.

Why learn

Up-front criteria prevent changing the bar after seeing which model produced the result. They also help distinguish a serious block, like a made-up number, from an editorial improvement, like a long sentence.

Key concepts

  • Mandatory: failure blocks delivery.
  • Desirable: improves usefulness.
  • Objective: reproducible checking.
  • Editorial: judgment with examples.
Study this topic and do the exercise →

What it is

The template must preserve the necessary information and allow adaptation where it helps. In the report, column names and sum rules are fixed; the wording of comments depends on the content. This separation is the foundation for the level of freedom.

Why learn

Freezing everything produces generic text. Leaving everything open allows important numbers to be omitted. A good recipe combines a stable skeleton with delimited editorial decisions—without trying to predict every sentence.

Key concepts

  • Fixed structure: required sections.
  • Fixed rule: defined calculation.
  • Variation: week summary.
  • Limit: do not infer causes without a source.
Study this topic and do the exercise →

What it is

A reference set brings together inputs, expected outputs, or criteria, and the reason each case exists. Include the common path, a missing data point, and an ambiguous situation. The set represents the task, not just your favorite example.

Why learn

A correction that resolves the original file can break an empty file. Varied cases reveal this effect early. Reserve a few cases for final evaluation, without using them to edit the instruction on every attempt.

Key concepts

  • Normal: demonstrates the main path.
  • Limit: tests the rule’s boundary.
  • Invalid: tests error-handling response.
  • Reserved: reduces overfitting adjustments to the examples.
Study this topic and do the exercise →

What it is

The briefing gathers purpose, inputs, output, steps, limits, and criteria. It doesn’t yet need to be an installed skill. First, check whether someone else can execute the process using only these instructions, without relying on you at every step.

Why learn

This exercise surfaces ambiguities before you blame the model. If even you can’t say when the work ends, automation just speeds up the spread of uncertainty. Use a small, complete briefing as a starting point.

Key concepts

  • Purpose in one sentence.
  • Steps with clear verbs.
  • Output-linked criteria.
  • Exceptions with expected response.
Study this topic and do the exercise →
View Complete →
← All learning tracksNext learning track →