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Creative Developer Daan Rongen explores the agentic systems behind IBM’s GRAMMY Museum interactive table, looking at how FIELD approached content-generation tools for music-led experiences.
Tony Ameji
Founder
Most "state of AI" reports we have seen run on surveys. You ask people how they use AI, they tell you what they hope is true, and you get an optimistic picture of a future that hasn't shown up yet.
We wanted firmer ground, so we did two things a survey doesn't. We measured what teams actually do, from the one place that can't round up: their AI agents' own tool calls. And we interviewed content leaders about why they do it. Quantitative reach, qualitative depth.
Short heading in the description article
An AI agent (like Claude or ChatGPT) acts on its own to complete a task, not just answering a question. To get work done, it makes tool calls: individual requests to a system to do one thing. Query a document. Edit a field. Publish a change.
Every tool call in this report is one such request hitting Sanity's MCP server: a single, logged action an agent took against real content. When we say "agent actions," we mean the same thing. One action, one tool call, one row in the data.
Between September 2025 and April 2026, AI agent tool calls on Sanity's MCP server grew from 7,400 a month to 521,000. Across that window we logged 1.46 million calls, from 12,300 users across 12,500 organizations. What we see has gone past pilots. It's production work, running daily, and still counting.
The full report is at research.sanity.io/ai-content-ops, including a prompt that helps you get started with this in your org. This post goes into what's behind the research.
