Such a good example of this I encountered recently: I was on a fishing trip. I asked the charter if he’d want to check out a free app I work on ( https://oceanconnect.ca ) in case it might be useful for his work. I don’t know how people on the ocean use ocean data. I don’t really know what they want to know, or why. I wasn’t totally prepared for the incredible onslaught of questions and information pertaining to how people use the data or what we can do with the data, and it was so cool and exciting to get that perspective. It was a good reminder that models are not the same as the systems they abstract, and knowledge to develop them has almost nothing to do with using them. This guy was a wealth of knowledge about how they use weather data on the water. In a sense, he knows more about the data than I do (even if he doesn’t realize it, or doesn’t understand it in its digital representation), and would be far better equipped to make a useful application for people like him if he could program. I found myself thinking people like him could actually do amazing stuff with LLMs if they sat down and got their ideas out on a screen. I’d really like to interview people on the water daily some day to refine the product if we ever have the funding. That domain knowledge is highly, highly specialized and people know things you’d never guess after living in a complex domain for decades.
痛点为 AI 基于上游原始证据的初步提炼;未包含额外中国市场检索。
这篇文章和讨论指向的痛点不是缺乏编程工具,而是领域专家在将自身知识转化为软件时存在根本性障碍。原始场景是:领域专家(如渔民、税务专家)拥有高度专业化的隐性知识,但缺乏编程能力,无法独立构建能解决自己问题的软件。现有流程中,他们要么依赖软件工程师来理解并实现其需求,但沟通成本极高,且工程师往往缺乏领域深度,导致产品偏离实际需求;要么放弃软件化,继续使用低效的手工或模拟方式。这种摩擦造成的结果是:大量有价值的领域知识无法被有效编码和复用,专家被迫在“学会编程”和“忍受低效工具”之间二选一,而软件工程师则因缺乏领域洞察而产出质量不稳定的产品。评论中渔民与软件开发者交流时产生的信息洪流,以及作者强调“理解领域比写代码更难”,都印证了这种知识传递的断裂是核心痛点。
External article summary
Personal website for Aaron Brethorst - Seattleite, technology leader, photographer, transit enthusiast, erstwhile non-runner.
External article source
- Article title
- Domain Expertise Has Always Been the Real Moat | Aaron Brethorst
- Host
- www.brethorsting.com
Selected HN comments
The software generalist described in this post has domain expertise as well. In software. If you’re a great generalist software engineer today, you aren’t jumping to some random domain to escape AI. Software is your domain. You’re sticking with it as it expands and transforms.
Not just domain expertise. The hard part has always been marketing, distribution, risk appetite, motivation, grit, and patience. There are plenty of things which are "trivial" to produce with no moat and yet are still million dollar businesses. Kebab stands. Water bottles. Barber shops. Movers.
This is such a sane take. It is THE reality we have been always ignoring. Writing software has never been difficult. It is the domain that has been the issue. Always.
Good post! Also, in my opinion, domain expertise is actually more interesting than pure coding ability. Coding, for me, has always been a means to an end. I'm equally happy with a spreadsheet if it solves my problem, and in fact I hate most apps.
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