Ideas Weave Every Narrative with AI.
You’ve probably noticed that every conversation about AI safety eventually spirals into the same tired sci-fi clichés. We conjure up images of red-eyed Terminators, Skynet, or the Paperclip Maximizer turning the universe into office supplies.But the recent 'rise and fall'…
Read More →/feed/json/wp-json/wp/v2/posts/sitemap.xml/feed/When AI makes implementation cheap, the product manager’s job shifts from managing resources to making high-quality judgments: what to build, when, and to what degree. Forget learning to code—become a judgment architect. This article breaks down 7 strategies from OpenAI’s Codex lead on how to thrive when building is abundant and taste is the only moat.
The most valuable output of a project isn’t the deliverable—it’s the conditional judgment of why it worked. Most teams ask if they should ‘productize’ a feature, but the real question is ‘under what conditions did this work?’ Misplaced knowledge does more harm than no retention at all.
Building an AI product isn’t just about prompt engineering. After developing Read-Box, an AI reading assistant with three collaborating Agents, I discovered that 30% of development time was swallowed by invisible, non-functional costs. Product managers must understand that architectural decisions—like choosing shared storage over event buses, or abstracting the LLM layer—directly dictate a product’s iteration speed, scope, and risk.
Laojun Mountain’s $60,000 ‘dream job’ posting wasn’t a hiring event; it was a zero-cost growth engine. By designing a two-phase user-generated content system, they turned a fixed salary into leverage, generating 9 days of viral spread and 30 days of continuous content. Discover how any business can stop buying traffic and start designing rules to attract it.
If your product is crushing it on one platform but flopping on another, stop doubting your team. The real enemy isn’t a bad product or a bad channel—it’s a systemic mismatch. From user mindset to algorithmic overfitting, here is why your expansion strategy is failing.
Selling AI features is a race to the bottom. Selling AI judgment is a fortress. Beisen, China’s HR SaaS giant, spent four years learning this hard truth. Their path from 40% losses to 5% profits reveals a blueprint for any SaaS company facing the AI dilemma: focus on outcomes, not technology. The real moat isn’t the model—it’s two decades of human expertise.
K12 tutoring is not a knowledge business — it’s an anxiety insurance racket. Parents pay for the feeling of having tried hard enough, not for actual learning. The real competitive moat isn’t technology or teachers; it’s the ability to translate invisible student progress into visible reassurance. AI can solve content delivery but not the core problem: motivation and trust. This insider analysis reveals why the industry’s only sustainable strategy is emotional, not educational.
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.
Plura is dismissed by analysts as a niche app for open relationships, but it’s actually a systems-level critique of modern dating. By flipping the sequence to ‘meet at an event, then match online,’ Plura achieves a 10x higher success rate, proving that algorithms destroy the context needed for real human connection.