AI Food Fights in the Enterprise

Disruption Theory & risk-aversion don’t apply

Incumbents typically cede market space to startups wherever there’s new, unproven technology or a new, unproven market, especially in spaces where they can’t use past data to predict the future. But in AI, they’re rushing to embrace new technology and uncertain markets, spending historic amounts of ... See more

Sobriety source #2: AI as the next platform shift. Every wave of new companies that transforms their respective industries is fueled by a major platform or technology shift. The advent of the web did this. The smartphone and mobile applications did this. And there is no doubt that AI is our next wave. But does every new wave always necessarily favo... See more

Unlike consumers, enterprises want control over how their data is used and shared with companies, including the providers of AI software. Enterprises have spent a lot effort in consolidating data from different sources and bringing them in-house (this article Partner integrations + System of Intelligence: Today’s deepest Moat by fellow Medium autho... See more

The need for better AI or LLM-specific infrastructure, along with the host of problems that come with non-deterministic of LLMs, means that there’s more software work ahead of us, not less. Abstraction layers like LLMs create more possibilities and thus, more work.

Is this a good thing or a bad thing? I’m not sure.

A great example of this is frontend... See more

But just like the internet, someone will show up later and think about something like Uber and cab driving. Someone else showed up and thought, “hey, I wanna check out my friends on Facebook.” Those end up being huge businesses, and it’s not just going to be one model that OpenAI or Databricks or Anthropic or someone builds, and that model will dom... See more