What Is Prompt Engineering?
Learn what prompt engineering is, how effective prompts are structured, which techniques improve results, and how to test and maintain prompts for reliable AI workflows.
Explore prompt engineering in depth, including prompt structure, context design, examples, constraints, reasoning strategies, structured output, evaluation, security, reusable templates, and reliable AI workflow design.
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Learn what prompt engineering is, how effective prompts are structured, which techniques improve results, and how to test and maintain prompts for reliable AI workflows.
Learn what context engineering is, how it differs from prompt engineering, and how to select, structure, retrieve, limit, and maintain the information an AI model receives.
Learn how system prompts, application instructions, user prompts, retrieved content, and tool results work together, where conflicts arise, and how to design reliable instruction layers in Feluda.
Learn how to design prompts for tool-using AI agents, including tool descriptions, selection, arguments, stopping conditions, retries, approvals, validation, and reliable Feluda workflows.
Learn how to design summarisation prompts for different audiences, lengths, source types, long documents, factual faithfulness, omissions, references, and reliable Feluda workflows.
Learn how to write prompts for Small Language Models using focused tasks, concise instructions, explicit formats, limited context, examples, validation, and reliable Feluda workflows.
Learn how to design prompts for rewriting and editing while preserving meaning, facts, tone, brand voice, terminology, localisation, and reviewable changes in Feluda workflows.
Learn how to design prompts for retrieval-augmented generation, including query rewriting, source boundaries, citations, conflicting evidence, missing information, context selection, and Feluda workflows.
Learn how to design information-extraction prompts for names, dates, amounts, identifiers, nested records, missing values, source fidelity, validation, and reliable Feluda workflows.
Learn how to design classification prompts with clear labels, category boundaries, uncertainty handling, examples, validation, evaluation metrics, and reliable routing in Feluda workflows.
Learn how to write effective AI prompts by defining the task, adding relevant context, setting clear constraints, specifying output formats, and testing prompts against real inputs.
Learn how to prompt AI for structured output using fixed headings, labels, tables, JSON, schemas, allowed values, validation, repair strategies, and reliable Feluda workflows.