243 items indexed · AI tools, prompts, hooks & techniques
This entry outlines a structured workflow for using the Claude Code AI assistant to build software projects more efficiently. By defining project context upfront in a CLAUDE.md file and using custom commands, development teams can reduce errors, manage API costs, and accelerate the entire coding process from planning to commit.
This document outlines a structured workflow that uses the Claude Code AI assistant to manage large software development tasks from start to finish. By breaking down work into planned steps with human approval checkpoints, developers can automate up to 90% of the coding, resulting in significant productivity gains while maintaining quality control.
This guide details a structured, 7-step process for using the Claude Code AI assistant to handle complex software development tasks in a professional setting. By defining clear review points and using project-specific documentation, development teams can increase productivity by up to 40% while maintaining code quality and control.
This resource provides a professional blueprint for building robust AI agent systems that can handle real-world business demands. It outlines the seven essential layers—from security and data management to performance monitoring—ensuring your AI agents are reliable, scalable, and safe for production use.
This is a curated index of professional-grade tools for building and managing AI agentic systems. It provides a directory of open-source libraries that help developers deploy, monitor, secure, and scale their AI applications for production environments.
This is a comprehensive guide for building professional AI agents that are ready for real-world use. It provides code-based tutorials to take an AI application from a simple prototype to a scalable, secure, and observable product.
This guide provides developers with concrete examples of how to build AI agents that are reliable enough for production use. It highlights specific open-source projects that focus on testing and handling unexpected scenarios, or 'edge cases', to ensure the AI doesn't break when faced with unusual user requests or data.
This guide shows developers how to use Claude Code as an orchestrated agent system rather than a simple chatbot, using a structured CLAUDE.md config file, planning modes, and specialized sub-agents to reduce bugs and speed up delivery. It covers practical cost controls like context compacting schedules and checkpoint patterns to prevent runaway API costs. Business owners get a blueprint for integrating AI into real development pipelines with measurable productivity gains.