
Claude Code Hooks: Making AI Gen Deterministic
Learn how deterministic hooks transform AI systems from probabilistic helpers into reliable tools with guaranteed actions by embedding commands that run automatically at certain checkpoints.
News, tutorials, and insights about AI agent skills and the future of AI-assisted development.

Learn how deterministic hooks transform AI systems from probabilistic helpers into reliable tools with guaranteed actions by embedding commands that run automatically at certain checkpoints.

Explore OpenCode as an alternative to Claude Code for building self-healing documentation pipelines with JSON manifests, validation gates, and parallel processing capabilities.

OAuth 2.1, JWT validation, and TLS encryption for LiteLLM's unified client library

Learn how to implement OAuth 2.1, JWT validation, and TLS encryption for DSPy's programmatic architecture when connecting to MCP servers. Complete guide with code examples.

Learn how to implement OAuth 2.1, JWT validation, and TLS encryption for LangChain's agent-based architecture when integrating with MCP servers. Comprehensive security patterns for autonomous AI agents.

Explore how to integrate Claude with the Model Context Protocol (MCP), revealing the unique patterns and considerations that make Anthropic's content-based implementation powerful and elegant.

Learn how to transform OpenAI's standard API integration into an enterprise-grade secure system using OAuth 2.1, JWT validation, and TLS encryption for MCP servers.

Learn how LiteLLM's universal gateway integrates with MCP to create truly portable AI tool integrations across OpenAI, Anthropic, AWS Bedrock, and local models.

Learn how to integrate DSPy with the Model Context Protocol (MCP) to create self-optimizing AI systems that transform fragile prompt engineering into robust, tool-enabled applications.
Learn how to integrate Model Context Protocol (MCP) with OpenAI using the Agents SDK and native API approaches for building powerful, tool-enabled AI applications.

Learn how to build a production-ready MCP server using FastMCP, the Pythonic framework that makes Model Context Protocol development accessible to any Python developer.

Learn how MCP enables AI applications to communicate seamlessly with external data sources. Build an MCP server, create tools for searching academic papers, and connect to a chatbot.