一位产品人谈"我经常犯错":在 AI 时代做产品,犯错是迭代的一部分

Hacker News 热门(buzzing.cc 中文翻译)·2026-09-21 06:48·5小时前·bcherny
AI 导读

一位产品负责人分享自己处理几乎所有问题都遵循的六步框架:理解已有信息、补齐缺失信息、定义问题、定义清晰简单的解法、定义目标、带着紧迫感行动,并在获得新信息后反复回到第 3-5 步。他认为最常见的失败模式是没能清晰定义问题、没能给出清晰简单的解法,并称"我喜欢犯错",因为犯错能帮助更快明确问题、找到正确解法。

Hacker News 热门(buzzing.cc 中文翻译)
30AI 编辑部评分,满分 100

一位产品人谈"我经常犯错":在 AI 时代做产品,犯错是迭代的一部分

2026-09-21 06:48· 5小时前· bcherny
AI 导读

一位产品负责人分享自己处理几乎所有问题都遵循的六步框架:理解已有信息、补齐缺失信息、定义问题、定义清晰简单的解法、定义目标、带着紧迫感行动,并在获得新信息后反复回到第 3-5 步。他认为最常见的失败模式是没能清晰定义问题、没能给出清晰简单的解法,并称"我喜欢犯错",因为犯错能帮助更快明确问题、找到正确解法。

I am often wrong

September 19, 2026

[I shared this note with my team earlier this week, and am posting it here as well. I hope it is interesting or helpful for others working on building product in the age of AI.]

Something that people learn quickly when they work with me is that my approach to pretty much every problem is:

  1. Understand the available information
  2. Gather missing information
  3. Define the problem
  4. Define a clear and simple approach to solve the problem
  5. Define a goal
  6. Act with urgency to achieve the goal

Along the way, I will often learn new information. That means going back and redefining #3-5, and repeating. This process is iterative and for complicated problems, it can take many tries to get right. This can feel thrashy, but if you are aware that it’s all part of the process, and that the only way to really solve a problem is to adjust when there is new data, then the churn is healthy. When there’s new data, you have to update your priors.

I apply something like these six steps for pretty much every problem, and pretty much every product (a product solves a problem for users). I apply this rough framework many times on most days.

Sometimes I will give feedback to people when they are missing steps in the framework, or are poorly executing some of the steps. I expect the same feedback in return. I try hard to give the feedback in real time, so the person/team can learn more quickly. Most often, the failure mode I see is (3) failure to clearly define the problem, and (4) failure to define an approach that is clear and simple. When one of these is missing, it leads to complex plans and unclear success criteria. For complicated problems, lack of clarity can be hard to spot if you’re the one making the plan, making it even more important to get feedback from people.

If part of this meta-process is meta-wrong, I am open to changing it.

All this to say, I love being wrong. It is my favorite, because it helps me more clearly define the problem, find the right solution, learn more quickly, and solve the problem.

来源:Hacker News 热门(buzzing.cc 中文翻译)· borischerny.com