Recently, I came across a hilarious discussion on social media. A netizen complained that while LLM hallucinations are decreasing, their boss's hallucinations are growing. The comments section was buzzing, with many reflecting that since the big fire of crayfish earlier this year, their bosses' imagination about AI has become increasingly wild, believing AI is omnipotent. These "crayfish-brained" bosses keep making outlandish demands, treating AI like a silicon-based deity that answers all prayers and saves them from suffering.
At the same time, in a widely discussed article titled "The layoffs will continue till we learn to use AI," author Arnav Gupta faces potential layoffs on May 20. He analyzes that although AI has significantly boosted code output and token consumption, corporate revenue hasn't grown in tandem, leading to a disconnect between "input-output-outcome." In the article, he laments a phenomenon where AI rapidly inflates demand, as AI amplifies the impulse to "just do it first." CEOs and product managers are churning out more and more bizarre demands, but rarely mention any concrete results, instead relying on layoffs to boost stock prices.
Actually, this kind of discussion isn't new. Over the past year or so, similar complaints have been endless. There used to be a joking saying that the real money-makers after AI were education and self-media. Recently, OpenAI and Anthropic have both released ARR data, leading the industry to hype token monetization again. But so-called token monetization largely comes from these demand-inflated companies, burning tokens wildly to keep up with the "trend," while AI remains decoupled from their revenue.
What baffles me most in these discussions and complaints is why product managers, as demand managers, have become accomplices in the disorderly expansion of business?
From a product manager's perspective, many so-called "demands" don't even qualify as such; at best, they are "requests."
The difference between the two is significant.
"Demand" means a real problem exists and is worth solving. "Request" is merely the anxiety, KPIs, power, and sense of existence of organizational members—an overflow of self-worth. This issue is very common in demand management; many people confuse the problems they need to solve with the things they want to do.
Before AI, these "requests" were intercepted by the high "transaction costs" within the organization. From proposal to PRD, scheduling, development, testing, and launch, a feature consumed significant communication, collaboration, and resources. Many immature ideas would naturally die off in this process.
After AI, these unworthy "requests," due to their cheap implementation costs, are packaged as "product strategy," "long-tail opportunities," "AI transformation," and other high-sounding terms, piling up into everyone's workload. The ultimate question they point to is: Am I keeping up with the AI trend?
Strangely, product managers, who are supposed to manage all this, haven't played a role in the business flow; instead, they've become producers of these unreasonable "requests." This shows that for a long time, the role of "product manager" has been distorted into a mere node for demand transmission within the company.
We generally believe that product managers are primarily responsible for demand management—they define problems, constrain demands, and make value judgments, occasionally handling project management tasks. But in many companies, they've become cogs in project management, constantly receiving requests, running processes, drawing prototypes, writing documents, and passing messages up and down.
If product managers spend their days doing these menial tasks and no longer act as a firewall against the company's disorderly expansion, nor advocate for user value, it's no wonder they become a notorious source of demand pollution.
Once they lose the core value of "demand managers," in the post-AI era, they will inevitably struggle to find their place within the organization. In the foreseeable future, organizational collaboration will inevitably settle into the context of agents, and product managers with only transactional attributes will be worthless.
As Arnav said in his article, the layoffs in these "AI transformation" companies stem from the inherent redundancy of human resources within large companies, not because AI has actually reduced costs and increased efficiency. These product managers skilled at menial tasks are part of that redundancy, and to survive, they have to churn out "demands" at full throttle.
For a long time, self-media has loved to hype "AI replaces XX jobs," and the "product manager" role, often cursed by programmers, naturally made the list. If you ask me whether AI still needs product managers, I'd say we don't need so many people to "unclog toilets."
But if you ask me whether AI still needs people to manage demands, I'd say it's needed more than ever and is increasingly important. Whether that person is the boss, CEO, or product manager doesn't really matter. The easier it is to create an illusion of "omnipotence," the more we need someone to pull the reins and align the "hallucinations" within the organization.
We need product managers because we need someone who, when the boss is driven by a "crayfish brain" and burning tokens wildly, can calmly point at all those PPTs and say: "This is just a 'request,' not a 'demand,' because it doesn't solve any real problem."
In a sense, product managers are returning from "producers of features" to "gatekeepers of value."
No user cares whether you use AI; users only care whether you can help them solve their problems. This is the most fundamental product value and the only consensus worth upholding in the AI bubble.