Ideas Weave Every Narrative with AI.
WPS Office, a productivity giant with over 600 million users, recently faced massive backlash over C-drive clutter and convoluted premium fees. But the real crisis isn’t technical—it’s a profound trust deficit. As the company attempts to pivot to AI-driven services, its legacy of opaque freemium tactics is coming back to bite them.
After eight years building AI across Baidu, fintech, and ByteDance, one truth is clear: we are building AI wrong. From treating token costs like premium features to forcing users into endless chat loops, the industry is missing the point. The real future of AI isn’t human-to-machine conversation—it’s autonomous agents trading services behind the scenes. Here are the five brutal truths every product manager needs to hear.
Most AI agent demos fail in production not because the model is dumb, but because the framework made too many irreversible decisions for you. Pi Agent challenges the feature-stacking status quo with a minimalist architecture that hands control back to developers. Discover why the platform, not the model, is your real moat.
Most AI products don’t die from competition; they get eaten by the next model update. This article reveals how AI product managers must shift from chasing tools to defining responsibility boundaries, embedding AI so deeply into workflows that removing it breaks the business. It’s a manifesto for surviving the AI value compression.
OpenAI’s real move isn’t a smarter model—it’s turning ChatGPT into a unified task-execution platform by absorbing Codex. The new competitive metric is cost-to-deliver for end-to-end workflows, not benchmark scores. AI product managers who still think they’re building chatbots are already obsolete.
AI recording cards aren’t about hardware profit. They’re a strategic mechanism to capture your conversations — turning ephemeral office chat into permanent, searchable corporate data. This article reveals why office giants are racing to digitize your voice, and why the real product isn’t the card, but the data monopoly it enables.
90 days of real-world use reveals the AI recorder’s hidden tax: time saved on typing is spent on correcting speaker labels and transcription errors. The real competitor isn’t other devices—it’s your smartphone. Survival depends on escaping the recording paradigm and embedding into enterprise data silos where phones can’t reach.
Alibaba just banned Claude and GPT internally, forcing 100,000 employees onto their own AI models. This isn’t a compliance move — it’s a brutal but brilliant product strategy. Dogfooding creates a high-density, zero-delay feedback loop that turns employee frustration into the most valuable product data. The short-term morale hit is the down payment on long-term market dominance.
Defaulting to the strongest AI model is a profit-killing habit. GPT-5.6’s tiered pricing forces product managers to build task routing maps—matching model cost to task value. The real competitive moat isn’t model access, but the ability to control costs and deliver quality. Stop building expensive demos. Start building sustainable products.