Crossing the AI Chasm: How OpenAI Turned LLMs into a Mainstream Success





I’ve been a vocal skeptic about the viability of ML developer tooling (broadly categorized as MLOps) as standalone businesses and, with very few exceptions, I’ve been proven right. The lack of a dominant design has led to fragmented “micro-markets” with very little value capture, mostly because of open source alternatives and cloud vendors giving their ML tools away for free (to collect revenue on the infrastructure layer). So what led LLMs to blow right past these problems, receive breakout media attention, and achieve real widespread adoption? And what is going to happen to all of the startups throwing the MLOps playbook at LLMs, rebranding as LLMOps? In this post I’ll use the “diffusion of innovation” theory as well as the concept of “crossing the chasm” in an effort to explain my bullish expectations of LLM providers like OpenAI or Anthropic, and my bearish view on the attempt to resurrect MLOps as LLMOps.According to Everett Rogers’ “Diffusion of Innovations”, innovative products are adopted progressively by different groups of adopters with distinct traits. Innovators, who are willing to take risks and have a high tolerance for failure, are the first to try out a new product. Laggards, who have an aversion to change, are the last. The famous bell-curve shaped graph shows the percentage of adopters in each category, and the corresponding graph of cumulative adoption resembles the familiar “S curve” pattern of an innovation’s market share over time.