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Advice for Building in AI

Advice for Building in AI

Separating the signal from the noise

Jan 25, 2023 · 5 min readUpdated Sep 22, 2026

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The past three months since we launched Lex have been wild. I’ve been heads down doing all the mundane (and fun!) things you need to do to transform an app from an exciting toy into an essential tool—talking to users, fixing bugs, tweaking the funnel, and building features. Meanwhile, the hype around AI has kept growing. There are tens of thousands of smart builders who want to launch startups in AI, and an even greater number of engineers and product leaders at incumbent technology companies that are integrating AI into their existing products.

Because this is all so new, it’s hard to understand clearly, and I see a lot of misconceptions and misunderstandings. This week on Divinations is my attempt to clear them up and offer some practical advice.

Resist broad generalizations

AI is like steel or electricity—a broadly useful underlying technology that is becoming a part of almost everything we use. It’s being integrated into free consumer apps, SMB SaaS, enterprise software, and everything in between.

Be wary of any one-size-fits-all advice about AI companies. One line I’ve heard is that “distribution is everything, because everyone has access to the same models.” That might be true, but when you’re trying to engineer viral distribution for a consumer app, the work looks very different from if you’re selling $100-per-month software to small businesses. And scaling up distribution for a bad product that fails to retain users is just lighting money on fire.

Ultimately the AI is a new raw ingredient to help you solve some customer problems that weren’t solvable before. The same old fundamental dynamics of whatever type of business you’re in still apply.

AI technology isn’t anyone’s moat—but that doesn’t mean moats will not be built

The conventional wisdom seems to be that AI companies building at the application layer will struggle because they’re reliant on fundamental models built by companies like OpenAI. Building A fundamental model is considered more attractive and defensible. I’m not so sure about that.

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