Reselling inference is a zero-margin commodity. The margin question comes down to cost-plus versus value-based pricing : one anchors to the inference line, the other decouples from it.
Databricks runs at $6.9b ARR growing 80%, widening the gap over Snowflake to $1.6b. Its AI products sit on the token path, where companies grow explosively even at scale.
The fastest growing companies in AI & software all share one property. They are either selling AI directly, or they are reselling inference. At worst, the first derivative of inference.
State-of-the-art AI email costs $22-130/month, but smaller models & local inference can cut costs by 100x. The next 12-24 months will be defined by matching models to workloads.
The new sales motion asks three questions : software budget, labor budget, & what ratio you want in three years.
Omni raises $90M at $1.5B to power intelligence about the business, not just dashboards.
The SaaS era rewarded unbundling & specialization. AI companies are rebundling into platforms because rapid model changes create cognitive burden for buyers assembling best-of-breed stacks.
Agent pricing reveals whether you're solving scarcity or creating disruption - and the market rewards these very differently.
Databricks has overtaken Snowflake in revenue. AI turned unstructured data from liability to asset, flipping the data warehouse market.
AI skills are programs written in English that give agents capabilities instantly. Like Trinity downloading a pilot program, skills encode institutional knowledge in executable form.
