Excerpt from today’s editorial: AI may eventually reduce the need for bulky enterprise software middlemen. But before that happens, Snowflake, Microsoft, Databricks, and others are fighting to become the trusted layer between raw AI capability and real company work.

→ This week was heavy with announcements. I was invited to two conferences at once – Snowflake Summit and Microsoft Build in San Francisco. And I went to both conferences because enterprise AI is where the industry is trying to make AI useful at scale. And the sentiment you read in a room full of analysts, while watching leaders push their agenda, defend their choices, and occasionally look uncomfortable, gives you much more than a machine-gun burst of news.

Let’s see what’s going on.

For two years we watched the AI story through models, benchmarks, chatbots, coding assistants, and consumer adoption. But the harder economic question is now moving inside companies. What happens when AI becomes easy enough for people to use directly? What if we don’t need a bulky and heavy middleman?

These were the questions I had in mind when I went to Snowflake Summit. Snowflake is a data-governance giant from the cloud-warehouse era, and now it has to prove it stays essential in the agentic one. The market liked the story – shares jumped more than 33% after earnings, FY2027 product-revenue guidance went up to $5.84B from $5.66B, the company signed a five-year $6B AWS deal, and market cap sits around $90B – but the strategic pressure is obvious. Databricks pushes from one side (some calls them “a bully in the room”), Microsoft tries to own the agentic interface from another, hyperscalers sit underneath everyone, and OpenAI and Anthropic, partners and customers on paper, are turning into the real competitors.

So I wanted the survival techniques. Does AI hurt enterprise software by making products replaceable, or does it make that software more valuable, because every agent still needs governed data, permissions, identity, memory, and trusted context? The usual debate stops at that binary, but I think that binary is the wrong place to stop.

Microsoft Build made the question larger. Satya Nadella’s message from the stage was that agents are everywhere – inside work, development, the operating system, local devices, cloud, enterprise knowledge. But the most useful thinking line came from a smaller Kevin Scott (Microsoft CTO) talk at a private event around Build:

Yup, I thought, exactly that. But these are symptoms.

Here is what the lag actually creates. Enterprises are full of legacy systems, fragile pipelines, compliance constraints, security reviews, human habits, and workflows that only make sense because someone has been repairing them by hand for years. Agents get more capable by the month; organizations do not move at model speed. So we get a strange interval, where AI threatens intermediaries in the long run while enterprise complexity keeps them useful in the short one. Snowflake, Microsoft, Databricks, Salesforce, ServiceNow are all fighting inside it, and from what I heard in the hallways, there is real uncertainty in there, almost panic, and a lot of running in too many directions at once. I also feel hey might be brittle because of their own internal complexity. Agents might need different organisation.

The comforting reading of that interval – agents threaten us later, complexity protects us now – treats the moat as a function of time. I think it's a function of cost. As per-token cost falls, the raw work middleware used to charge for, querying and generating and connecting and transforming, drifts toward free. What stays expensive is trust: knowing an agent acted on the right data, with the right permissions, on behalf of the right person, with a record of why. When everything cheap gets cheaper, the scarce thing is governed proximity to intent.

Which means the middleman doesn't disappear in the direct-use world; it changes shape. It stops being an application – capability packaged into rigid software and sold back through layers of interface – and becomes a substrate, the trust and permission layer that sits at the moment a stated intention turns into a permitted action. The agent era doesn't need less governance. It needs more, located somewhere new.

But it’s a different type of governance.

This is the test Snowflake should be judged by. Not whether it governs data – it does, and that was the moat of the last era – but how it governs it, and whether it moves up to the intent layer or stays a managed warehouse with AI bolted on top; whether it reduces the distance between what a person wants and useful work getting done, or adds one more governed layer between the user and the outcome.

And tokenmaxxing might be even dangerous here. Independently from each other, Sridhar Ramaswamy, Snowflake's gentle CEO, and Kevin Scott were making the same point: activity, or tokenmaxxing, is not value, and more agents, more context, more tokens, more integrations, more automation can all produce motion without progress. I think this is the dilemma we will be sorting through this year, both at the behemoth and startup levels.

The middleman doesn't die in this story. It moves – closer to where intention becomes work, and further from the warehouse.

If any of those thoughts resonate with you – share them across your social networks. Let’s keep the conversation going.

Topic 2: Also, NVIDIA made tons of announcements in Taipei (see News from the Usual Suspects below). We played with and covered one of the most interesting: Cosmos 3, its omnimodal world model family.

Trends we see looking at every paper related to AI and ML published last week:

AI research agents and deep research

Agent operating systems: harnesses, skills, and coordination

Memory, context, retrieval, and persistence

Training for reasoning, diversity, and test-time search

Architectures, world models, and physical AI

Verifiable environments for computer-use agents

That’s all for today. Thank you for reading! Please send this newsletter to colleagues if it can help them enhance their understanding of AI and stay ahead of the curve.