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Agents @ Work
An indicative snapshot of what AI agents do across the apps they use.
Where agents actually do their work, by category
Agents are doing more every week
Agent Actions (Weekly)
Agents rarely stay in one app
Top apps agents work in, and the pairs that keep turning up in the same job
Which app categories agents are moving into?
Fastest-growing categories this week, and the biggest by volume
Fastest growing
Biggest (by volume)
Reads per write, by job
What agents actually do with your data
Reads versus creates, updates and deletes - the action mix over the last 7 days
How often agents repeat work they've seen
How much of last week's work repeats something agents have handled before
How hard is agent work?
- Hard
- 82%Multi-step work with cross-app dependencies, pagination, edge cases or error recovery.
- Medium
- 18%A moderate sequence of several connected steps.
- Easy
- 0.3%One straightforward action with a single tool.
The stacks developers build on
The frameworks developers build their agents on
LangChain / LangGraph5.2%
Anthropic SDK<2%What new users start with
Which AI clients new users start with each week
Other AI clients include n8n, Make, Goose, Raycast, Dify and Lindy.
Which apps are taking off this week
The apps agents picked up fastest this week
What triggers an agent run
The events kicking off agent runs - a new email, a form, a webhook
30M+ trigger events last week, around the clock.
The work never stops
Agent actions by hour of day (UTC)
Where agents hit rate limits
How often each app throttles the calls agents send it
How these numbers are measured
What is measured
Real agent actions running through Composio. One action is one request to an app, from a sample of live traffic.
How figures are published
Shares and week-over-week changes are shown as bands, not exact numbers.
What this does not establish
A high rank means agents used that app a lot, not that it's better. An app also has to have been used the week before to rank, so a one-week spike doesn't count.
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