Engenharia de Prompt

Avaliação e Otimização de Prompts

2-4 hours 4 Modules

Overview

Main Topic: Prompt Evaluation

Duration: 2 - 4 Hours

Level: Advanced

Target Audience: Quality Managers (QA), Developers, Technical Leaders, and AI Auditors

ABOUT THE TRAINING

How to know if your prompt is really effective or if it just "looks" good? This training teaches how to measure the quality of results objectively, eliminating empiricism and assumptions. The focus is on implementing a continuous improvement cycle through performance metrics, cost control (tokens), and response speed, ensuring a constant standard of excellence.

Objective

Empower professionals to act as a "Prompt Quality Manager", using structured testing methodologies and auditing to reduce rework and ensure maximum accuracy in AI deliverables.

TRAINING MODULES

A/B Testing Methodology

Development of experiences to compare different versions of a prompt (e.g.: a more detailed version vs. a more direct one). Learning how to measure which variant delivers the best return and greatest accuracy for the specific use case.

Self-Consistency

Implementation of the multiple reasoning pathways technique. Professionals learn to configure AI to generate various outputs for the same problem and select the most frequent and coherent response, drastically increasing reliability in complex tasks.

Quality Metrics and Hallucination Score

Implementation of quantitative evaluation scales and criteria for clarity, utility, and veracity. Techniques to use the AI itself as an impartial auditor, assigning scores and grounded technical justifications to the generated responses.

Audit and Continuous Optimization Lab

Practical exercise in logical refinement: analysis of interaction logs to identify pattern failures. The challenge is to optimize an unstable prompt until reaching a confidence index above 95%, focusing on reducing token consumption and eliminating ambiguities without the need for third-party tools.

Materiais complementares

Prompt Enviado:

"Atue como um auditor de qualidade. Avalie a resposta da IA abaixo em uma escala de 1 a 5 para o critério 'Clareza', onde 1 é confuso e 5 é perfeitamente compreensível. Justifique sua nota."

Nesse treinamento, também mostramos a técnica Self-Consistency. Técnicas para fazer a IA verificar o próprio trabalho e corrigir erros antes de mostrar o resultado.