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ai-engineering-hub vs CodexGuide

36k-star hub of runnable AI engineering tutorials — LLMs, RAG and agent apps as self-contained projects, including build-code-harness: a Claude-Code-style coding harness rebuilt on CrewAI + E2B. — versus — Community-maintained Chinese practice guide to OpenAI Codex — learning paths, CLI/App/Cloud/IDE setup, AGENTS.md templates, sandbox/approval safety and team playbooks, published at codexguide.ai.

The curated verdict

Both are learning material rather than tools: ai-engineering-hub ships runnable tutorials for building LLM and agent apps, codexguide is a Chinese-first practice guide for operating one harness — setup, AGENTS.md rules, approval boundaries, team playbooks.

ai-engineering-hubCodexGuide
Stars37k3.3k
Forks6.1k311
LanguageJupyter NotebookPowerShell
LicenseMITMIT
Last activity28 days ago4 days ago
Topicscodingcoding
Curated connections32

ai-engineering-hub — the curator's take

A tutorial hub, not a tool — each folder is a complete, runnable project with real dependencies. The standout is build-code-harness: it rebuilds a coding-agent harness (planning, memory, checkpoints, sandbox, human gate) one layer at a time on CrewAI + E2B, the best way to understand what harnesses like Claude Code actually do. Content repo caveat: quality varies by folder, and there's a newsletter funnel attached.

CodexGuide — the curator's take

Use it to onboard people — especially Chinese-speaking teams — onto Codex without the trial-and-error phase: real task flows (PPT, Obsidian, CI fixes, Feishu/Notion), AGENTS.md rule templates, sandbox and approval boundaries, and a team playbook for turning one successful run into reusable process. NOT a tool: nothing to install, it's a VuePress knowledge base. Content is Chinese-first (an English README mirror exists), the README carries a heavy sponsor block, and anything time-sensitive (pricing, availability) should be re-checked against OpenAI's own docs — the guide itself says so.