Agentic Coding

This comprehensive GitHub repository on Claude Code agentic workflows directly addresses your interests in advanced AI coding techniques, PRD-driven development, and best practices for solo entrepreneurs. The guide covers efficient agent architecture with 48 visual diagrams explaining context flow, tool orchestration, and multi-agent patterns. For PRD and documentation best practices, it includes detailed sections on methodologies (TDD, SDD, BDD), CLAUDE.md configuration, and decision frameworks for when to use agents versus skills versus commands. The repository provides 181 production templates including custom agents, skills, and hooks with explanatory comments—examples like code-reviewer, security-auditor, and refactoring-specialist agents demonstrate advanced "vibe coding" patterns. You'll find practical workflows for specification-driven development, step-by-step guides for context management and memory hierarchy, and production hardening approaches. The 271-question knowledge validation quiz tests understanding across setup, agents, MCP servers, and advanced patterns. For security and compliance in SaaS applications, the guide uniquely tracks 28 CVEs and 655 malicious skill patterns with MCP vetting workflows and threat databases—critical for production deployment.

This guide provides a comprehensive structured learning path for mastering Claude Code's advanced features. It covers 10 modules progressing from beginner to advanced, including slash commands, memory systems, skills, subagents, MCP protocol integration, hooks, plugins, checkpoints, and advanced features like planning mode. The guide includes production-ready templates for workflows like automated code reviews (combining slash commands, subagents, memory, and MCP), copy-paste configurations organized by feature, and Mermaid diagrams explaining how features work internally. It emphasizes combining multiple features into automated pipelines—for example, using memory with CLAUDE.md files for team standards, delegating tasks to specialized subagents, configuring hooks for event-driven automation, and integrating external tools via MCP. The learning path takes 11-13 hours total with self-assessment quizzes to identify knowledge gaps, immediate value available in 15 minutes by copying a slash command template, and all configurations versioned on GitHub with active maintenance synced to Claude Code releases (currently v2.1.160).

This article directly addresses all three of your search intents. Vibe coding is the practice of describing software intent in plain English while Claude writes, runs, and debugs the code autonomously—you own the output and can deploy anywhere. Key advanced techniques include writing specifications first in plain English before implementation (spec-driven development), using CLAUDE.md files to encode tech stack and conventions, treating prompts as structured work orders with scope and verification criteria rather than casual messages, and leveraging effort levels with Claude Opus 4.7 at "high" or "xhigh" for complex tasks. Claude Code is the core agentic tool, operating in the terminal with full codebase access via a 1M token context window, autonomous execution of tests and Git workflows, and checkpoints for rollback. For best practices: keep CLAUDE.md concise to avoid drowning important rules, always verify outputs with tests or screenshots before shipping, plan two to three iterations per feature, use test-driven development by writing failing tests first, and avoid over-exploration by scoping tasks tightly. Practical workflows include installing Claude Code (npm install -g @anthropic-ai/claude-code), starting with GitHub's Spec Kit for specification tooling, and deploying via Vercel or Netlify. As of May 2026, Claude Opus 4.7 scores 87.6% on SWE-bench Verified; Sonnet 4.6 is the recommended daily driver at lower cost, with Haiku 4.5 for high-volume routine work.

The user is interested in advanced Claude Code workflows, agentic coding PRD documentation best practices, and vibe coding tutorials for AI pair programming. The website content includes multiple podcast episodes about AI coding, Claude Code usage, and development workflows. Here's what's relevant to their interests: Several episodes directly address their interests: episodes on Claude Code advanced techniques, AI agent workflows, agentic coding patterns, PRD documentation approaches, and vibe coding methodologies. Episodes featuring Brian from Notion on prototype playgrounds and code-based prototyping, Intercom's engineering velocity with Claude Code, Stripe's AI coding agents, and various advanced Claude Code tutorials are highly relevant. The content covers practical workflows for efficient AI-assisted development, custom agent architectures (like agent loops and goal-based patterns), design system integration with code, and best practices for high-quality AI-generated code. The content is in English. Advanced Claude Code techniques are featured prominently, including context loading with mermaid diagrams, custom hooks for automated code quality checks, and command-line tool optimization. Multiple episodes demonstrate PRD-driven development workflows, agent loop design patterns (heartbeat, cron, hook, and goal loops), and practical vibe coding approaches. Brian Lovin's episode on Notion's prototype playground shows how code-based prototyping transforms design workflows. Stripe's minions episode demonstrates agent architectures at scale with 1,300 PRs weekly. The Intercom episode reveals how to structure custom skills and use telemetry to measure AI adoption. Episodes cover everything from setting up efficient development environments to multi-agent orchestration patterns, with emphasis on practical implementation over theory.