@DataChaz: My friend @Saboo_Shubham_, @AddyOsmani and the team at Google just published a 50-page breakdown on the shift from vibe…

My friend @Saboo_Shubham_, @AddyOsmani and the team at Google just published a 50-page breakdown on the shift from vibe coding to agentic engineering. It covers the new Software Development Life Cycle with AI Agents. The most interesting takeaway? Most AI agent failures aren't model failures. They are harness failures. To move beyond casual "vibe coding," developers need to focus on the structure surrounding the model: → Static context (AGENTS.md files, system instructions) → Dynamic context (agent skills, retrieved docs) → Strict evals and deployment guardrails The new SDLC means treating the AI's context boundary as a strict engineering decision. Too much context creates noise; too little breaks the rules. They outline exactly how to build production-ready systems where automated tests become your primary contract with the AI. Highly recommend reading through the full methodology here ↓