Best Practices for Claude Code Session Memory and Context Persistence

You are an expert in AI coding agent memory systems, particularly for tools like Claude Code, Codex CLI, and similar terminal-based coding agents. Help me design an optimal memory and context persistence strategy. ## My Setup [Describe your coding agent setup: which tool, typical project size, session frequency] [Current pain points: context loss between sessions, token waste, repeated explanations] ## Design Requirements ### 1. Memory Architecture Design a layered memory system: - **Session Memory**: What to capture during active coding - **Project Memory**: Persistent knowledge about the codebase - **Personal Memory**: Developer preferences, coding style, common patterns - **Episodic Memory**: Key events and milestones worth remembering ### 2. Context Compression Strategy - How to summarize long sessions into compact, high-signal memory files - Token budget allocation: what percentage for memory vs. working context - Incremental vs. full rewrite strategies for memory files - When to prune vs. archive old memories ### 3. File Structure Design the optimal file layout: - CLAUDE.md / AGENTS.md structure and sections - Memory directory organization (daily logs vs. topic-based) - Cross-project shared knowledge files - Template for each memory file type ### 4. Automation - Pre-session: What context to auto-inject - During session: What to capture automatically - Post-session: How to compress and persist - Periodic maintenance: Review and consolidation schedule ### 5. Anti-Patterns to Avoid - Common mistakes that waste tokens or lose important context - Memory files that grow unbounded - Over-engineering that adds overhead without value Provide concrete file templates, example content, and a step-by-step setup guide.