X Product Lead Peter Sellis on Working Backwards and Killing Your Cash Cow
X's new Product Lead Peter Sellis proposes using a "working backwards" approach for product planning: reasoning back from the future endgame rather than making linear patches on the existing business. Citing SpaceX's willingness to phase out its most profitable Falcon 9 and bet on Starship, he argues that top-tier companies dare to smash their own cash cows, while most companies would rather count money on a ship that is destined to sink.
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View original postNVIDIA CEO and founder Jensen Huang publicly shared one of his highly counterintuitive daily habits in a CNN interview: He uses AI frantically every day, yet he feels his own brain has actually become sharper. Many people use AI in a way that is essentially performing a massive mental amputation on themselves— for example, having it polish an email, having it ghostwrite a summary, and when they hit a little knot that requires thinking, they casually push the keyboard over to the model and let it make the decision for them. Treating the tool as a crutch for laziness, the result after half a year is that their skills are all ruined, and they have completely degenerated into overgrown infants who cannot think without a chat box. But in the interview, Huang directly tore off this fig leaf. He said he never lets AI think for him; instead, he lets AI be his private tutor, to teach him entirely new fields he knows nothing about, or to gnaw on hard bones that mere personal experience simply cannot crack. Don't use it for things you could already do; use it to push open the high walls of cognition you originally could never cross. Most striking was the real CEO card Huang mentioned when Zakaria pressed him. He said that as the head of a chip empire worth trillions of dollars, 90% of his instructions every day are essentially not giving orders, but frantically asking high-quality questions to his team and to the model. Writing prompts for large models has never been some mechanical chore of typing in a few keywords; asking questions itself is an extremely mentally demanding top-tier cognitive skill. Here is a cruel, counterintuitive truth: AI is widening the wealth gap between two kinds of people at the speed of light. One kind of person outsources thinking to machines, saves half an hour of slacking off every day, and sees their cognition shrink across the board. The other kind of person outsources execution to machines, forces themselves to dig deep into real problems, and uses the world's top computing power every day to complete a brain remodeling. So let's stop asking whether AI will make people stupid. Tools have no moral preference. If you treat it as a wheelchair, you will become paralyzed; if you treat it as a lever, you can move an entire brain trust all by yourself.
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英伟达CEO兼创始人黄仁勋在CNN专访里公开了自己的一个极度反直觉的日常习惯: 他每天都在疯狂用 AI,但他觉得自己的大脑反而越来越聪明了。 很多人用 AI 的方式,本质上是在给自己搞脑力大截肢, 比如写个邮件让它润色,写个总结让它代笔,遇到一点需要动脑的死结,顺手就把键盘推给模型让它替自己下决定。 把工具当成偷懒的拐杖,结果用了半年,手艺全废了,自己彻底退化成了离了对话框就不会思考的巨婴。 但老黄在访谈里直接撕开了这层遮羞布, 他说他从来不让 AI 替自己思考, 他是让 AI 当自己的私教, 去教自己完全不懂的全新领域, 或者去啃那些靠肉身经验根本啃不动的硬骨头。 不要拿它去做你本来就能做的事,而是拿它去推开你原本根本跨不过去的认知高墙。 最狠的是扎卡利亚追问时,黄仁勋提到的那个做 CEO 的真实底牌。 他说作为掌管几万亿美元芯片帝国的掌门人,他每天 90% 的指令,本质上都不是在下命令,而是在疯狂向团队、向模型提出高质量的问题。 给大模型写提示词,从来不是什么输入几个关键词的机械杂活,提问本身就是一项极度消耗脑力的顶级认知技能。 这里有一个残酷的反直觉真相: AI 正在以光速拉开两类人的贫富差距。 一类人把思考外包给机器,每天省下半小时摸鱼,认知全面萎缩, 另一类人把执行外包给机器,逼着自己去深挖真问题,每天借着全球顶级的算力给自己完成一次大脑重塑。 所以咱们别再问 AI 会不会让人变笨了,工具没有任何道德偏好, 你把它当轮椅,你就会变成瘫子,你把它当杠杆,你就能一个人撬动一整个智囊团。
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X's new Head of Product, Peter Sellis, is truly the top product manager of our time—with a single sentence he laid bare the top strategic philosophy of Silicon Valley: once you understand why SpaceX dared to proactively retire its most profitable Falcon 9, you'll understand why the planning at the vast majority of companies is nothing but slow-motion suicide.
Peter has actually laid out for us an extremely brutal product logic: most mediocre companies die at the hands of their competitors, while all top-tier companies die from not daring to shoot themselves.
Many teams doing business planning are essentially engaging in self-deceiving linear extrapolation.
They look at how much money they made this year, look at what resources they have on hand, and then cautiously patch things up on their existing turf, terrified of touching the cake of those with vested interests.
What this forward-inference thinking produces is often just a cheaper, defective product from the old era.
But the backcasting method Sellis talks about flips the timeline directly in reverse.
It is absolutely not about guessing tomorrow from today; rather, it forces you to stand at the future endgame and look backward: if in the next ten years the standard for human-computer interaction is lightweight smart glasses, then no matter how good we make phone screens today, it's meaningless—every line of code now must serve that endgame.
The most ruthless part is that he directly benchmarks this method against SpaceX's crazy, almost suicidal decision back then.
Falcon 9 was clearly the most profitable, highest-success-rate flagship rocket in the history of human commercial spaceflight, with cash flow so good it could coast for twenty years;
yet Musk turned around and decided to retire it completely, betting his entire fortune and life on Starship, which had already exploded several times.
This is like Cortés, after landing, personally burning his retreat ships—leaving himself not the slightest room to scrape by.
Sellis marveled that almost no large company in the world can achieve what SpaceX has.
Because human nature is deeply attached to the comfort zone, preferring to count banknotes on a ship doomed to sink rather than jump into the icy water to build the next nuclear submarine.
In fact, there is an extremely cold, counterintuitive truth here: the most dangerous state in the business world is never when you face a dead end, but when you are holding a highly profitable golden rice bowl.
Daring to smash with your own hands the cash cow that earns you the most money is often the only way to save your entire life when the future wave comes crashing down.