Zero-Shot Prompting
Zero-shot prompting asks the model to complete a task directly without examples. It relies on the model's pretrained knowledge and works best when the task is simple, clear, and familiar.
A structured technical guide for AI application developers, prompt engineers, and technical leads covering techniques, patterns, model differences, evaluation, and production rollout.
Zero-shot prompting asks the model to complete a task directly without examples. It relies on the model's pretrained knowledge and works best when the task is simple, clear, and familiar.
Few-shot prompting teaches the model a pattern by showing a few input-output examples before the target task. It is one of the most reliable ways to improve format and style consistency.
Chain-of-thought prompting asks the model to reason step by step before giving an answer. It is useful for multi-step reasoning, calculations, and transparent decision workflows.
Tree-of-thought extends step-by-step reasoning by exploring multiple candidate paths, scoring them, and selecting the strongest solution.
System prompt design defines the assistant's role, responsibilities, boundaries, and output behavior. It is the behavior contract for an AI application.
Role-playing prompting gives the model a professional identity, perspective, and communication style so it can respond with domain-specific framing.
GPT-4o prompts should be adapted to its context window, instruction-following behavior, tool-use support, and safety profile. Test with your own workload before choosing it for production.
Claude Opus prompts should be adapted to its context window, instruction-following behavior, tool-use support, and safety profile. Test with your own workload before choosing it for production.
Gemini Pro prompts should be adapted to its context window, instruction-following behavior, tool-use support, and safety profile. Test with your own workload before choosing it for production.
Expert Persona Pattern is a reusable prompt design pattern for structuring model behavior, constraints, and output in production-oriented workflows.
Step-by-Step Pattern is a reusable prompt design pattern for structuring model behavior, constraints, and output in production-oriented workflows.
Constraint-First Pattern is a reusable prompt design pattern for structuring model behavior, constraints, and output in production-oriented workflows.
A staged learning path for Prompt Engineering, from basic prompting to advanced patterns and production operations.
The ten most common Prompt Engineering mistakes developers make, plus practical fixes.
A systematic way to choose an LLM based on task type, quality requirements, latency, budget, context length, deployment, and compliance.
Every technique page includes use cases, examples, recommendations, and failure modes.
The site covers evaluation, versioning, cost, latency, safety boundaries, and operations.
Compare context windows, output behavior, tool use conventions, and adaptation strategies.