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Context Engineering for Claude Code
Design patterns, best practices and caveats for engineering context in AI coding agents with Claude Code.
Read MoreLangChain Deep Agents
Comprehensive reference for building long-running, multi-step AI agents using LangChain’s Deep Agents SDK — covering planning, file systems, subagents, memory, skills, sandboxes, backends, context management, human-in-the-loop, and deployment.
Read MoreClaude Agent SDK
Reference for building production AI agents with the Claude Agent SDK, the agent loop, sessions, tools, MCP, hooks, subagents, permissions, context management, structured output, streaming and deployment.
Read MoreClaude Code Plugins
Claude Code plugins let you extend Claude Code with custom skills, agents, hooks, MCP servers, LSP servers, background monitors, output styles, and themes — and share them across projects and teams via marketplaces.
Read MoreGitHub Copilot Notes.
GitHub Copilot and customization instructions together unlocks a structured, repeatable way to guide AI assistance across your codebase—covering custom instructions, reusable prompt files, agent mode and extensible skills for end-to-end AI-driven workflows.
Read MoreLangchain Gen-AI Patterns
Reusable design patterns and best practices for building robust, efficient and scalable LLM applications, covering retrieval, memory, agents, RAG and orchestration.
Read MoreAgent2Agent Protocol (A2A)
Agent to Agent Protocol (A2A) is an open standard protocol to enable seamless communication and collaboration between AI agents.
Read MoreSOAP-Based Web Services Notes
SOAP-based web services remain a foundational pillar of enterprise integration—covering the messaging envelope, WSDL contracts, binding styles, security via WS-Security, and how to reason about SOAP versus REST when designing distributed systems.
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