Ai development

Learn how to build tool functions in Claude to give AI access to real-time information and actions. Master best practices for validation, error handling, and function design.

Learn how to systematically improve your AI prompts through a five-step evaluation workflow. This guide covers drafting prompts, creating eval datasets, generating responses, grading outputs, and iterating for better performance—transforming prompt engineering from guesswork into data-driven optimization.

Learn how to use XML tags to add structure and clarity to Claude prompts. Improve prompt parsing with clear boundaries for code, documentation, and data.

Master one-shot and multi-shot prompting techniques in Claude. Learn how to use examples to handle edge cases, define output formats, and improve response quality.

Learn how to improve Claude's output quality by being specific in your prompts. Master output quality guidelines and process steps to get consistent, high-quality results.

Master the temperature parameter in Claude to control response creativity and predictability. Learn how to choose the right temperature for different tasks with practical Python examples.

Learn how to use Claude's built-in web search tool to access current information. Understand schema setup, domain restrictions, response structure, and citation rendering.

Master the art of writing clear and direct prompts that get better AI results. Learn why the first line matters most, how to use action verbs effectively, avoid common mistakes like vague questions, and see real examples showing 69% improvement from this single technique.

Learn how to use system prompts to customize Claude's responses for specific use cases. Build a math tutor chatbot and create flexible chat functions with role-appropriate interactions.

Learn how to use the Claude Code SDK to run Claude programmatically from your applications and scripts. Available for TypeScript, Python, and CLI with practical examples and use cases.