Скачать или смотреть 10- AI Engineering Architecture and User Feedback

Building a robust AI application requires a structured evolutionary architecture that prioritizes safety, efficiency, and continuous improvement through five key stages of development. The process begins by enhancing context and implementing input and output guardrails to prevent data leaks and hallucinations, eventually moving toward sophisticated model routing and caching to manage costs and latency. Central to this lifecycle is the transition from simple sequential logic to agentic patterns and write actions, which necessitates advanced observability and tracing to debug the resulting system complexity. Finally, the text highlights the value of integrating user feedback, both explicit and implicit, to create a data flywheel that refines model performance while warning against the risks of biased feedback loops.