INEMA.CLUBPRORSI v6.2 enter the course

Recursive self-improvement · RSI v6.2

Understand the AI that helps improve AI.

From concepts to your first supervised cycle. Compare evidence, recognize limits, and test improvements in support, education, and documents.

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18 lessons · 6 modules · about 232 minutes · free · phone and computer

The manager and the educator compare documents and results from an improvement experience at a work table.

What you start doing

Understand the mechanismDistinguish response review, system improvement, and recursion.
Judge the evidenceExamine real cases and organize a verifiable comparison.
Run a pilotRecord criteria, results, costs, and the decision.

Who it’s for

It’s for you if

  • You work in management or education and want to evaluate and improve routines with AI.
  • You have little time and no technical background.
  • You prefer learning by doing.

It’s not for you if

  • You already master the subject and are looking for something technical.
  • You want a traditional video lesson.

Six modules, one practice per lesson

Module 1 · Basics: recognize what changed

Distinguish RSI, response reviews, and claims without evidence.
3 lessons · 39 min

Module 2 · How it works: draw a cycle

Goals, roles, evaluation, memory, and adopting improvements.
3 lessons · 39 min

Module 3 · Research: read real cases

AlphaEvolve, DGM, and the pieces of automated research.
3 lessons · 39 min

Module 4 · Assessment: check before trusting

Held-out cases, manipulation of measurements and generated data.
3 lessons · 39 min

Module 5 · Applications: use at work

Customer service, education, and document summaries with references.
3 lessons · 37 min

Module 6 · Final project: decide with evidence

Choose an implementation, plan a pilot, and report its limits.
3 lessons · 39 min

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Research with source and context

AlphaEvolve, Darwin Gödel Machine, AI Scientist, DSec and evaluation studies. Original sources included with each lesson, consulted on 25/09/2026.

Marina and Ícaro are fictional characters. The screens illustrate comparisons; they do not show measured results from tools.

The practices teach supervised improvement. They don’t promise to create an autonomous AI or to train a new model.

Read the research and editorial decisions (Portuguese) · Download the experiment worksheet · Download practice cases · Download the approved knowledge worksheet