Interactive Explainer Maps Claude Code Agent Loop Designs, from Single Calls to Self-Mutating Prompts

An interactive explainer at agent-loop.app.teenyapp.com breaks down how Claude Code handles its agent loops, memory management, and reasoning. Built with Opus 4.7, the site presents eleven actual agent loop designs that are in production, ranging from a single call to advanced agents that rewrite their own prompts.
What's Inside
The site is designed as a 30–60 minute learning resource for developers who want to understand Claude Code's thinking process. Each loop design is a real pattern gathered from research papers, leaks, and community sources. The explainer includes:
- Eleven loop patterns — from simple call loops to meta-agents that mutate their own instruction sets.
- SVG animations — visual walkthroughs of how each loop processes context, manages memory, and decides next steps.
- Interactive controls — you can watch each pattern execute step by step.
Loop Designs Covered
The eleven patterns include (but are not limited to):
- Single request-response (no loop)
- Basic loop with fixed context window
- Sliding window memory
- Hierarchical summarization loop
- Self-critique loops
- Prompt rewriting agents that modify their own system prompts
- Multi-agent loops where sub-agents report to a coordinator
Each pattern is annotated with when to use it, trade-offs in latency and accuracy, and real-world examples.
Why It Matters
Understanding these loops directly impacts your effectiveness with Claude Code. Choosing the right loop design can reduce token waste, improve response quality, and prevent context overflow. The interactive format lets you compare patterns side-by-side without running experiments yourself.
📖 Read the full source: r/ClaudeAI
👀 See Also

Migrating OpenClaw agents to Claude Code after third-party harness deprecation
A developer migrated 17 OpenClaw agents to Claude Code in one afternoon after Anthropic ended third-party harness support. The process involved creating CLAUDE.md entry points, bash wrappers, and cron jobs while preserving existing agent logic.

Using Claude to analyze writing patterns for better custom instructions
A Reddit user describes a method for creating more effective custom instructions by having Claude analyze 10 writing samples to identify concrete patterns like punctuation avoidance and analogy sources, rather than relying on subjective tone descriptions.

Short Leash AI Coding Method: Beat Fable by Keeping Control
Greg Slepak's short leash method for AI coding agents: plan, review every diff, deny bad changes, commit after subtasks. Beats Fable quality by keeping the developer in the loop.

OpenClaw Docker users: Pin to commit 0c926a2c5 to fix broken Discord and channel extensions
After updating OpenClaw via Docker, channel extensions like Discord, Signal, and WhatsApp fail with module import errors. The issue stems from commit d9c285e93 and a second Docker-specific bug. Pin to commit 0c926a2c5 for a stable workaround.