Agentic Coding

This content is a GitHub repository documentation page for PM-Skills, a curated library of product management skills and workflows for AI agents like Claude Code and Cursor. While it comprehensively covers agentic coding best practices, agent skills architecture, and enterprise adoption patterns for PM tools, it does not contain news or recent developments related to the user's specific search intents. The user is seeking news about Claude Code PRD workflows, agentic coding context management strategies, and AI coding assistant enterprise adoption. This page is a static library documentation and reference guide—not a news article or development update—so there is no breaking news, product announcements, or recent developments to extract.

# Claude Code PRD Workflow Best Practices & Agentic Coding Context Management This repository presents AAS Core, a local agent-first control plane for AI coding workflows that enables Claude and Codex to inspect projects, search a complete skill catalog, and compose reproducible stacks with validation and immutable planning before any changes are applied. The system prioritizes agent-owned selection over ranking or recommendations, with agents evaluating full project surface (architecture, testing, security, deployment, maintenance) and choosing exact skill IDs from 2,025+ available skills. Key workflow practices include using read-only MCP tools for skill composition, persisting selections as aas-stack.json with evidence artifacts, reviewing stacks in the hosted Workbench, and validating plans through CLI before execution. For enterprise adoption, the platform supports multiple coding agents (Claude Code, Cursor, Codex, Autohand Code, Gemini CLI, Copilot) through specialized plugins, bundles, and direct installers, with optional role-based starter sets for SaaS MVPs, security hardening, and OSS shipping workflows.

The content directly addresses the user's interests in agentic coding best practices, context management strategies, and enterprise adoption patterns for AI coding assistants. CCAR-F certification covers five core domains relevant to advanced Claude Code work: Agentic Architecture & Orchestration (27% weight), Tool Design & MCP Integration (18%), Claude Code Configuration & Workflows (20%), Prompt Engineering & Structured Output (20%), and Context Management & Reliability (15%). The curriculum emphasizes production-ready system design rather than prompting alone, including multi-agent patterns, coordinator/sub-agent relationships, context passing between agents, and orchestration workflows. Claude Code training covers CLAUDE.md configuration, project rules, custom commands, and skills development integrated with CI/CD pipelines. Context management and reliability strategies are explicitly treated as design constraints from the start, covering context window optimization, long conversation management, context preservation, and error handling for enterprise applications. The material is structured around practical architectural decisions: when to use agents versus single model calls, how to scope tool access, how multiple agents should communicate without losing context, and when human review steps are necessary. Preparation involves hands-on building of agentic applications, MCP integrations, and configured Claude Code workflows alongside scenario-based reasoning rather than memorization.