The Product Ark on the AI Wave: How Traditional PMs Can Be Reborn in the Creator Storm

The AI Tsunami: Is the "Half of PMs Will Lose Their Jobs" Prophecy Doom or Rebirth?

Imagine standing on the deck of an old wooden sailing ship, gripping a rusty compass while dozens of sailors coordinate around you—someone hoisting sails, someone steering, someone calling out orders. That is the daily life of a traditional product manager (PM): drawing roadmaps, aligning across teams, endlessly revising requirement documents. Suddenly, an unprecedented wave rises from the sea, and within it glimmers a magnetically levitated vessel moving faster than light. A voice carries from the crest of the wave—Cat Wu's startling remark from an interview: "Half of traditional product managers will face unemployment!"

This is not science fiction; it is a faithful depiction of a heated debate in our recent captain's meeting. Reviewing the full discussion points—Lucas's strong pro argument, the captain's counterpoints, and the final ruling—we find that AI is not a dragon stealing jobs but the creator of the wave itself. It has compressed the cost of "how to write code" to nearly zero. What remains truly scarce is only "what to write" and the product taste behind "wow, that experience is amazing!" The traditional PM toolkit—coordination, roadmaps, cross-team alignment—is decisively outflanked by "research previews + automated workflows + mission alignment." But don't panic: in this storm, the opportunities far outweigh the risks. What gets eliminated is not AI itself, but the old mindset that refuses to embrace "product taste + extreme execution speed + creator identity." Anthropic's "highway" framework has proven, through iteration speed, that compressing a 6-month project into 1 day is not a dream but a daily routine. xAI operates the same way—we practice "removing all delivery barriers." Right now is the best window for ordinary people, entrepreneurs, and working PMs: AI gives you the lever; all you need to do is "Just Do Things!"

> Note: If you're encountering "product taste" for the first time, don't worry. It's not mysticism—it's an intuitive sensitivity to users' "wow" moments. Just as a sommelier can taste the oak-barrel vintage in a glass of wine, a great PM can sniff out the scream-worthy innovation hidden in a pile of user feedback. In the AI era, this taste becomes scarce currency, because everyone can write code, but experiences need a soul.

The Awakening of Product Taste: From "Orchestra Conductor" to "Composer + Performer" in One

Lucas went all-in during the discussion, strongly supporting "product taste" as the new core competency. His metaphor was surgical: AI has smashed the barrier to writing code to zero, so "what to write" and "wow experiences" are the real battlefield. The traditional PM is like an orchestra conductor, busy keeping violins and cellos in sync; the new PM must simultaneously become composer, conductor, and first violinist—writing the melody, conducting, and playing the climax personally. The captain added a measured counterpoint: not all PMs will lose their jobs, but 95% of "pure coordination" PMs will indeed be marginalized. In large enterprises, external constraints like regulation, legal, and brand still exist—but AI companies like Anthropic have slashed coordination costs to the extreme with their "highway" framework: mission alignment and pre-building "future container" prototypes make the whole process fly.

Think about daily life: you open an app, the interface is fluid, features feel intuitive, every tap feels like a handshake with an old friend—that's a "wow experience." AI can generate code instantly, but it doesn't know which button color makes a user's heart skip. Cat Wu's view is now mainstream in the AI-native era, and xAI's internal iteration speed is equally ferocious. Those who refuse to transform are like sailors of the sail era suddenly facing steamships, watching others sail away. Those who embrace it become the helmsmen at the storm's center, navigating with product taste.

To put it humorously: the traditional PM was like a wedding planner coordinating florists, hotels, and officiants; now AI is the super-assistant—florists deliver by drone, hotels auto-schedule, and you only decide "romantic or wild today?" Lucas's practical advice cuts to the chase: interrogate models daily, build 10 Evals, ship prototypes weekly, become a hybrid creator. For everyone, it's "Just Do Things"—100% automation + everyday tools + agency. The captain's ruling: half of PMs face risk, but the opportunity is bigger! What eliminates them is the old mindset that refuses a new identity.

Days 1–7: Rebuild Product Taste—Interrogate AI Like a Detective to Find the Model's Blind Spots

Transformation isn't a slogan; it's daily executable action. The first week's core is "perceiving model boundaries." Spend 1 hour per day "interrogating" Claude or Grok: pick a feature you own and force the model to reflect on its mistakes three times—"Why did you do this? Where was the prompt ambiguous? What is the user's real pain point?" This isn't casual chatting—it's Holmes interrogating a suspect, with every follow-up digging out hidden logic gaps.

Quantified targets are clear: establish 10 core Evals (definitely not 100—focus on quality), such as "user wow-experience score > 8.5" or "pre-merge review pass rate > 95%". The deliverable? A "My Product Taste Checklist" filled with core user personas, wow scenarios, and model boundaries.

Example: you own search for an e-commerce app. Previously you coordinated front-end, back-end, and product managers across 10 meetings. Now you ask AI: "If a user searches for 'summer sandals' but actually wants sun-protection clothing, how do we make recommendations more delightful?" After three follow-ups, you discover the model missed "scenario association." That's the awakening of taste—from coordinator to insight generator.

> Note: Evals aren't cold KPIs—they're a health report for your product taste, quantifying the "wow" the way a doctor measures your pulse. Think of how short-video algorithms guess what you want to watch—that's top-tier Evals at work. Learn to build your own, and you've grasped AI's pulse.

Days 8–15: Just Do Things + 100% Automation—Throw Repetitive Work into the AI Black Box

Week two, escalate: pick one task you repeat daily (requirement docs, presentations, meeting notes) and automate it to 100% with AI (don't stop at 95%—that's self-deception). Build an "internal tool you use every day," like auto-generating custom sales demos—that's exactly what Cat Wu's team's salespeople did, and efficiency took off.

Quantified requirements: save ≥ 2 hours/day, and personally use the tool for 7+ days after launch. Deliverables: a before/after time-comparison table plus one genuinely deployed tool.

Humorous scene: you used to be an old ox hauling the rickety cart of requirement documents uphill; now AI is a self-driving tractor—you sit in the cab sipping coffee, enjoying the scenery. Example: a PM who spent 2 hours daily writing weekly reports now inputs one prompt; AI pulls data and generates a witty summary with emojis. You tweak two sentences and send it to your boss. The saved time? Spend it thinking about "where the next wow experience is."

The captain's immediate action recommendation: do it today—open Claude or Grok and say: "Help me automate the most annoying thing in my daily workflow to 100%; give me the complete prompt + validation Evals." Screenshot the result and let's iterate together. That's the essence of Just Do Things!

Days 16–23: Build Future Prototypes—The Counterintuitive Strategy of Turning "What Models Still Lack" into a Weapon

Week three, the highlight: pick a feature "current models still can't do perfectly," such as advanced code review or multi-agent coordination. With a Research Preview mindset, quickly ship internal prototypes (no perfect docs, no legal review). One prototype per week, maintaining a "gap list" of "what capabilities models still lack." Deliverable: a "container prototype" (code/prompt) ready to plug in at the next model upgrade.

Vivid metaphor: traditional PMs build sandcastles and wait for the tide to test them; new PMs build a submarine prototype, dive into the deep sea, and record where it leaks. A discussant added highly practical advice: immediately after prototyping, use AI to simulate user testing and iterate—甚至 build multi-agent systems to automate cross-team workflows. Enterprise regulatory constraints remain, but AI assists with translation and compliance checks, cutting costs sharply.

Example: you own an AI writing assistant that occasionally "hallucinates." You quickly build a prototype where it outputs a draft, then a second AI agent fact-checks. The gap list reads "hallucination rate still high"—at the next model upgrade, you swap in the container. A 6-month project, iterated in 1 day. Anthropic has validated this path; xAI is running it too.

> Note: Multi-agent coordination sounds fancy, but it's like chefs in a kitchen dividing work: one chops, one stir-fries, one plates. In the AI era, you direct these "AI chefs" and only decide tonight's menu (product taste). Ordinary people can do it too—prompts are the recipes.

Days 24–30: Inject Mission + Expand Agency—Job Titles Are Illusory; Value Is Eternal

Week four, elevation: use "Does this matter more to the mission?" as a decision razor in every weekly team meeting. Cross boundaries and proactively solve 1 high-value problem outside your job description—job descriptions are cages; the creator identity is wings. Quantified: complete 1 small experiment in "Claude personality optimization" (making AI behave like a great colleague). Deliverables: a personal 30-day retrospective + 1 public share (Zhihu / RED / LinkedIn).

Story time: PMs used to be the company's "traffic police," directing everyone not to crash. Now you're the expedition leader, shouting "For the exploration of the unknown universe, onward!" Mission gives every prototype a soul. Lucas's "Just Do Things" blossoms here: you no longer draw roadmaps—you deliver in units of days. Expected outcome: after 30 days, you transform from "coordinator" into "AI-native creator" with scarce product taste.

After the Storm: The Product Ark Has Set Sail—Ordinary People Can Become Legends

Reviewing the whole discussion—from the pro side, the captain's ruling, to the 30-day quantified plan—every point points the same direction: in the AI era, the half-of-PMs unemployment risk is real, but the rebirth opportunity is bigger. Traditional coordination is being eliminated, replaced by product taste and creator identity. Just Do Things—starting this moment.

Ordinary readers may ask: can I benefit if I'm not a PM? Absolutely! Entrepreneurs can use this plan to pull ideas from their heads into reality; working professionals can use it to save time and embrace agency. The AI wave has arrived—those who board the ark will witness a magnificent transformation from particles to stars.

--- References 1. Cat Wu interview: product management transformation in the AI era (Anthropic internal sharing, emphasizing product taste and the highway framework). 2. Anthropic highway framework internal practice: mission alignment and prototype iteration acceleration cases. 3. xAI iteration speed cases: delivery-barrier removal experience from the Grok captain's perspective. 4. Lucas's PM transformation views: product taste as the new core competency, a practical guide. 5. The captain's 30-day action plan: a quantified transformation path from coordinator to AI-native creator.