https://blog.chuanxilu.net/en/series/teaching-ai-to-reflect/Recent content in Teaching AI to Reflect on Chuanxilu for Skilled Homo sapiensHugoen-USWed, 15 Jul 2026 07:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/07/testing-coverage-truth-code-review-found-6-bugs/Wed, 15 Jul 2026 07:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/07/testing-coverage-truth-code-review-found-6-bugs/Don't trust all-green tests. After 1,754 tests passed, an independent code review found 6 bugs. A story about how testing and code review cover each other's blind spots.https://blog.chuanxilu.net/en/posts/2026/07/aristotle-v16-cross-language-design/Wed, 08 Jul 2026 07:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/07/aristotle-v16-cross-language-design/Watchdog intercepts in TypeScript. Intervention decides in Python. A subprocess bridge connects them. This wasn't architected. It was constrained into existence. Five constraints forced this shape: runtime environment, existing assets, zero new infrastructure, startup overhead, and fault tolerance. None of these five decisions were optimal. Each was the least bad option under the circumstances.https://blog.chuanxilu.net/en/posts/2026/07/aristotle-v16-watchdog-intervention-bridge/Sat, 04 Jul 2026 07:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/07/aristotle-v16-watchdog-intervention-bridge/The first five articles all answered one question: how to make AI remember its mistakes. But some mistakes cost too much to wait for "next time." Files are being corrupted, commits are being polluted right now. Reflection cannot undo damage already done. v1.6 introduces the Watchdog-Intervention Bridge: stop waiting for post-mortem; intercept violations the moment they occur.https://blog.chuanxilu.net/en/posts/2026/05/six-bug-patterns-and-integration-gaps/Thu, 07 May 2026 10:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/05/six-bug-patterns-and-integration-gaps/Before releasing Aristotle v1.1, I found 18 bugs. Unit tests caught four. The rest lived at the integration layer. After root cause analysis, six patterns emerged: not because the problems got harder, but because AI bypassed the defenses I'd built through years of experience.https://blog.chuanxilu.net/en/posts/2026/05/ai-bug-root-cause-diagnosis/Fri, 01 May 2026 10:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/05/ai-bug-root-cause-diagnosis/Fix #13, and old bugs come back. This isn't a "how I fixed a bug with AI" anecdote. It's a full post-mortem of a 15+ bug battle: four rounds of attribution, regression traps, and how TDD was forced into existence by pain.https://blog.chuanxilu.net/en/posts/2026/04/seven-human-ai-collaboration-patterns-in-aristotle/Thu, 16 Apr 2026 21:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/04/seven-human-ai-collaboration-patterns-in-aristotle/Looking back at the Aristotle project: from initial design to the GEAR protocol; I identified seven distinct collaboration patterns between myself and AI. As AI gets more capable, human judgment doesn't become less important. It becomes more critical.https://blog.chuanxilu.net/en/posts/2026/04/from-markdown-to-mcp-server-gear-protocol/Thu, 16 Apr 2026 19:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/04/from-markdown-to-mcp-server-gear-protocol/Aristotle's reflection rules started as a flat Markdown file: append-only, forgotten, no rollback. When dozens of rules accumulated, I realized the file wasn't enough. This started a design iteration path from append-only to Git-backed MCP Server. That path led to something called GEAR.https://blog.chuanxilu.net/en/posts/2026/04/from-scars-to-armor-harness-engineering-practice/Sat, 11 Apr 2026 01:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/04/from-scars-to-armor-harness-engineering-practice/The first version of Aristotle looked smooth. In practice, it exposed four architectural problems. Fixing them validated the trust model and harness engineering framework from Part 3: every constraint encodes a trust judgment.https://blog.chuanxilu.net/en/posts/2026/04/a-trust-boundary-design-experiment/Mon, 06 Apr 2026 18:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/04/a-trust-boundary-design-experiment/The same reflection mechanism on different platforms, their complexity differing by an order of magnitude, but the complexity itself reveals a deeper question: when to trust AI's judgment, and when to step in?https://blog.chuanxilu.net/en/posts/2026/04/claude-code-reflect-different-soil/Mon, 06 Apr 2026 14:56:00 +0800https://blog.chuanxilu.net/en/posts/2026/04/claude-code-reflect-different-soil/The same reflection mechanism lands on different platform foundations with very different landing postures and paths: from plugin installation to permission pitfalls to API concurrency, documenting the actual development process on Claude Code.https://blog.chuanxilu.net/en/posts/2026/04/aristotle-ai-reflection/Mon, 06 Apr 2026 10:00:00 +0800https://blog.chuanxilu.net/en/posts/2026/04/aristotle-ai-reflection/Installing reflection capability into AI coding assistants: when the model makes a mistake, immediately trigger root cause analysis and transform the correction into persistent rules.