The article explains how AI product managers have shifted from creating prototype diagrams to designing continuous evaluation “exams”, using real‑world examples, data‑driven testing, cross‑team collaboration, and iterative error analysis to deliver truly useful AI products.
The article explains how scaling AI agents reveals fragmented, inconsistent internal documentation, and argues that high‑quality production knowledge bases require a company‑wide, role‑based process, concrete writing rules, continuous inspection, and cross‑department ownership to ensure AI answers remain accurate and user‑focused.
By mapping information gaps, building a cross‑functional support system, and automating key workflows, a smart‑hardware operation reduced remote communication costs to zero, cut labor by 50%, lowered expenses by 95%, lifted efficiency by 50%, and generated roughly $1.68 billion GMV within a year.
In the AI era, product managers shift from routine execution to strategic decision‑making as AI tools automate data analysis, PRD drafting, and market research, while their core value expands through deeper business insight, cross‑domain coordination, and critical risk‑aware thinking.
This article shares practical insights from frontline managers on scaling teams, evolving decision processes, fostering cross‑functional collaboration, choosing market models, and optimizing pricing, helping founders and leaders navigate the typical challenges of growing a startup.
In the AI era, developers must shift from merely writing code to mastering soft skills such as problem definition, cross‑functional collaboration, and critical thinking, using AI tools as assistants while maintaining rigorous quality checks and clear communication to create real business value.
This guide explains why designers must oversee product experience, outlines a systematic four‑step framework (define, find, solve, push), details planning elements, project phases, problem‑gathering methods, classification of issues, value assessment, alignment practices, and how to establish a lasting experience‑optimization mechanism.
A technical leader at NetEase Yanxuan, with a PhD in applied mathematics, describes building a supply‑chain algorithm team from scratch, categorizing projects as mature, challenging, or innovative, assigning staff by risk, overseeing work through high‑level guidance, engaging with business units to uncover pain points, mobilizing resources for deadlines, and pursuing initiatives while emphasizing resilience, business focus, and a trust‑based workplace culture.
This article outlines how designers can contribute strategic value during the fast‑paced, resource‑constrained early phase of a consumer loan product, covering role adjustment, business analysis, goal setting, process optimization, and low‑cost design implementation to secure business buy‑in.
This article shares seven actionable insights—from demand management and platform design to verification, collaboration, branding, and growth challenges—drawn from Ant Group’s experience building AI‑driven platforms, illustrating how product managers can turn abstract methods into concrete, user‑centric solutions.
The article argues that involving developers, designers, and operations from the start of product planning improves communication, catches design flaws early, and prevents costly delays, while urging product managers to question every feature, maintain logical rigor, and lead by example to earn engineers' respect.
