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Ready-to-use prompts and guides for getting more from AI. Learn prompt engineering, context, tokens, memory, testing, and techniques for improving response quality.

Robô diante de um notebook entre três cartões organizados de exemplos à esquerda e muitos cartões dispersos e marcados em vermelho à direita.

Prompt Engineering26/09/2026

Prompts with examples: when few-shot helps and when it only adds noise

Learn when examples genuinely improve a prompt, when they only add unnecessary context, and how to compare zero-shot and few-shot with a representative test set.

Ilustração dividida entre zero-shot e few-shot, com cartões de instruções e exemplos, respostas simuladas e medidores de uso da janela de contexto.

Prompt Engineering22/09/2026

Zero-shot vs. few-shot: when examples improve a prompt and when they waste context

Compare instructions without examples and prompts with demonstrations on the same test cases to measure format, accuracy, and token cost.

Duas versões de planilha lado a lado, ampliadas por uma lupa, com células divergentes destacadas e um caderno de relatório de divergências sobre a mesa.

Ready-to-Use Prompts02/09/2026

Prompt to compare two spreadsheet versions and explain every difference without changing the data

A prompt template for comparing File A and File B in read-only mode, finding differences in structure, values, formulas, and formatting, and producing a traceable report.

Notebook com planilha do Excel aberta, painel do Copilot usando Python e materiais de análise auditável sobre a mesa.

Ready-to-Use Prompts01/09/2026

Copilot in Excel with Python: 9 prompts to clean data, test hypotheses, and build auditable analyses

Ready-to-use prompts for Python through Copilot in Excel with explicit inputs, checkpoints, validation, and an audit trail.

Notebook com grade de planilha abstrata, lupa ampliando células, escudo com marca de verificação e gráficos que simbolizam análise e validação de dados.

Ready-to-Use Prompts31/08/2026

Prompt to analyze a spreadsheet in ChatGPT without changing data blindly: diagnosis, validation, and a reproducible report

A reusable prompt for analyzing Excel or CSV files with schema inventory, data-quality diagnosis, a plan before edits, calculation traceability, and sanity checks.

Painel de laboratório de segurança com agente de IA central ligado a e-mail, documentos PDF, base RAG e ferramentas, enquanto entradas hostis são bloqueadas e casos de teste são avaliados.

Agents and Automation30/08/2026

How to test prompt injection in AI agents before connecting email, PDF, RAG, and tools

A reproducible method to prove whether untrusted content can divert an agent, trigger tools, leak data, or persist instructions before production.

Painel futurista horizontal com três interfaces de modelos de IA, controles de temperature, top_p e top_k e linhas ramificadas que representam a variabilidade das respostas.

AI Performance30/08/2026

Temperature, top_p, and top_k in 2026: what still works in OpenAI, Claude, and Gemini

In 2026, classic sampling controls are no longer universal. See where they still work, where they cause errors, and which settings control variability now.

Ilustração dividida entre memória padrão e somente do projeto no ChatGPT, com laptop ao centro, fluxos de chats e arquivos, setas de contexto e isolamento e anotações de decisão.

Context, Tokens and Memory26/08/2026

Project Memory in ChatGPT: default vs. project-only and what enters context in 2026

Understand how ChatGPT Project memory modes affect instructions, files, chats, and outside context, including plan differences and tests for isolation.

Infográfico tecnológico em fundo escuro compara OpenAI, Claude e Gemini em três colunas, com camadas de instrução e setas indicando prioridades entre regras e pedidos.

Prompt Engineering24/08/2026

System prompt, developer message, and user prompt: how instruction hierarchy changes across OpenAI, Claude, and Gemini

OpenAI, Claude, and Gemini separate high-level instructions from the user's request, but their APIs use different roles, fields, and precedence rules.

Mesa de estudos com notebook exibindo uma sessão interativa baseada em material enviado, PDF impresso, caderno de revisão e anotações sobre active recall.

Ready-to-Use Prompts21/08/2026

Prompt to study with ChatGPT using PDF: active recall, correction and answers based on the material

Use a modular prompt to turn PDFs, slides, and notes into an active recall session, one question at a time, proofreading material, and reviewing weaknesses.

Banner tecnológico em fundo azul-escuro compara OpenAI, Claude e Gemini em três colunas, com exemplos de JSON livre e JSON com schema, ícones de erro e validação e um fluxo da instrução ao consumo pelo código.

Prompt Engineering17/08/2026

Structured Outputs or “respond in JSON”? When to use JSON Schema in OpenAI, Claude and Gemini

Requesting JSON, enabling an output mode and imposing a schema solve different problems. See when each approach is sufficient and where it is still necessary to validate content.

Ilustração dividida entre um grande bloco de prompt monolítico à esquerda e uma sequência de etapas conectadas com checkpoints à direita, com um ponto de decisão ao centro.

Prompt Engineering17/08/2026

Mega-prompt or prompt chaining? When to split a task into steps and when to keep it to a single call

A practical guide to deciding between a single call and a staged flow, comparing dependencies, validation, failures, state, latency, cost, and testing.

Dois robôs diante de painéis que comparam uma escolha errada e uma escolha correta de ferramenta, com nomes, descrições e schemas de tool calling.

Agents and Automation17/08/2026

Does your agent call the wrong tool? How names, descriptions and schemas improve tool calling

Tool calling errors are rarely resolved with more prompting. See how to reduce ambiguity with specific names, usage descriptions, restricted schemas, enums, and confusion tests.

Capa em estilo tecnológico com pessoa pensando, cérebro digital e comparação visual entre OpenAI, Claude e Gemini sobre como promptar modelos de raciocínio em 2026.

AI Models and Tools17/08/2026

Is it still worth asking “think step by step”? How to prompt reasoning models in 2026

In current reasoning models, the old “think step by step” has lost space to goal-oriented prompts, criteria and effort controls.

Capa tecnológica com diagrama separando contexto estático e variável, indicador de cache hit, notebook e caderno com fatores que mantêm ou invalidam o cache.

Context, Tokens and Memory17/08/2026

Prompt caching in practice: how to separate static and variable context without breaking the cache

Prompt caching reduces cost and latency when calls reuse the same prefix. See how to separate static and variable content and measure cache hits without relying on guesswork.

Infográfico tecnológico com pilha de documentos para contexto longo, base de conhecimento com busca para RAG e um fluxo híbrido convergindo para um núcleo de IA.

Context, Tokens and Memory17/08/2026

RAG or long context: when to send all documents, when to use retrieval, and when to combine the two

A practical matrix to choose between long context, RAG and hybrid architecture considering corpus, update, question type, citations, cost, latency and maintenance.

Infográfico em fundo escuro compara function calling à esquerda e MCP à direita, com um agente orquestrador no centro e um fluxo híbrido unindo as duas abordagens.

Agents and Automation16/08/2026

MCP vs. function calling: what each layer does, when to use it and why they can work together

Function calling decides and structures a tool call; MCP standardizes how applications discover and access tools and context. Understand where each layer comes in and when to combi...

Estação de trabalho com painéis comparando um modelo anterior e um novo modelo, gráfico de regressão e etapas de diagnóstico de prompt, schema, ferramentas, contexto e parâmetros.

AI Performance16/08/2026

Did your prompt get worse after switching models? How to diagnose regression before rewriting everything

If a workflow changed after a model change, preserve the prompt as a baseline, isolate variables and test format, tools, context and parameters before rewriting.

Homem diante de um notebook observa um cérebro digital cercado por blocos de tokens, balões sobre janela de contexto, context rot e memória e uma árvore de diagnóstico à direita.

Context, Tokens and Memory16/08/2026

Why does AI forget instructions in long conversations? Context window, context rot and clutter-free memory

When an AI starts to ignore old rules, the problem may be context limits, degradation within the window itself, conflicting instructions or misunderstood memory.

Mesa de trabalho com notebook exibindo um fluxo de avaliação de prompts, rubrica impressa, casos de teste e anotações sobre comparação A/B e regressão.

AI Performance16/08/2026

How to know if a prompt really improved: test cases, rubric and regression without evaluating on feeling

A practical method for comparing prompt versions with representative cases, rubric defined before responses, blind A/B testing, and recording regressions.