Closing: The Discipline Is the Leverage

You started this course thinking vibecoding meant 'using AI more.' You leave knowing it is the opposite: using AI more deliberately. The pattern that runs through every lesson: the model is fast and confident. Your job is to be slow and skeptical at the right moments. The discipline is non-negotiable: brief well, read every line, force enumeration when debugging, stop when AI is the wrong tool. The weXare thesis applies cleanly here. Vibecoding is the canonical human + AI workflow. You direct. AI drafts. You decide. None of the three roles is optional. None can be skipped without breaking the system. Five takeaways to keep: 1. Context is everything. The model knows nothing except what you show it. Point at files, name symbols, set constraints. 2. Examples beat descriptions. Constraints beat vibes. Acceptance criteria beat 'make it work.' 3. Read every diff. Including the parts you did not ask to be changed. Especially the test files. 4. Force the model to enumerate when debugging. 'List 3 possible causes' beats 'fix it.' 5. The 30/70 split: about 30 percent of code is AI-drafted on healthy teams, 70 percent is still human-written or heavily edited. Be deliberate about which 30 percent. What is next: If you want to design AI-powered products beyond your own code, take [Building AI Products Responsibly](/en/learn/building-ai-products-responsibly). If you want to ship AI features at scale, take [LLMs in Production](/en/learn/llms-in-production). If you want to build autonomous agents, take [Building with Agents](/en/learn/building-with-agents). Now go ship code that you wrote with AI and would still defend in a code review.