An AI‑era product manager is no longer just a process designer; they must manage uncertainty, handle ambiguous user intent, design graceful failure, and set clear boundaries for model behavior, acting more like a trainer of a living system than a traditional static workflow architect.
The article recounts a failed AI‑powered feature launch, explains why users care about concrete problem‑solving rather than flashy AI, defines a rigorous scenario formula, outlines a five‑step traditional scenario‑analysis SOP, adds five AI‑specific dimensions, and provides a one‑page canvas to help product managers turn AI hype into real user value.
This article explores the philosophy and practical techniques of failure‑oriented design, covering why anticipating failures is crucial for developers, the organizational and process changes needed, core design principles, and concrete implementations such as multi‑level Redis distributed locks with code examples.
This article examines why failure is inevitable in software systems, proposes a mindset of failure‑oriented design, outlines organizational roles and processes to mitigate incidents, and presents concrete technical techniques such as distributed locking and traffic shaping to build resilient, high‑availability services.
This article explains the concept of failure‑oriented design, why it matters for large‑scale streaming services, and details concrete architectural patterns—such as layered services, database fallback, cache redundancy, consistency checks, and dynamic traffic switching—used by a production playback control platform.
The article explains how anticipating and engineering for diverse failure scenarios—from hardware faults and software bugs to traffic spikes and external attacks—can dramatically improve system reliability, reduce downtime, and protect business continuity in modern distributed and cloud environments.
