Who engages with AI agent platforms on LinkedIn?
We pulled the crowd around eight AI agent platforms in the UK on 20 August 2026. Over 90 days, 4,449 people reacted to or commented on those platforms' public posts.
Then we split them by title. 79 people whose title suggests they sign for software. 1,523 builders and practitioners. Every platform skews the same direction, and the size of the skew is the table below.
This edition's table is a ratio, not reactions per post.
The count: eight platforms, 4,449 reactors, 90 days
Pulled 20 August 2026 in the UK. Eight anchor platforms, a 90 day window, 4,449 raw reactors.
Before filtering, 4,449 accounts touched these posts. After the title filter two groups came out of it: 79 people whose title suggests they sign, and 1,523 people whose title says they build the thing or run it day to day. The remainder either carried no readable title or did not fit the category.
27 people appear around two or more platforms. This records observed cross-platform engagement, not exclusive audience membership.
The ratio table: builders and practitioners per service owner or lead
Sample: 4,449 raw reactors across 8 anchor platforms, UK, 90 days to 20 August 2026. Read each row as the number of builders and practitioners for every one person whose title suggests they sign.
| Platform | Builders and practitioners per service owner or lead |
|---|---|
| Botpress | 11:1 |
| MindStudio | 12.7:1 |
| Relevance | 13.6:1 |
| n8n | 14.8:1 |
| Voiceflow | 15.8:1 |
| StackAI | 31.5:1 |
| Lindy | 55:1 |
| Gumloop | 87.7:1 |
Botpress has the most balanced crowd in the set, and it is still 11 builders for every service owner or lead. Gumloop's crowd runs 87.7 to 1.
The three at the top of the list sit close together, from 11:1 to 13.6:1. The bottom two are a different category of number. Nothing here inverts.
How to use the role ratios
The ratios help describe who publicly engaged with the selected accounts. On n8n's posts, the recorded ratio was 14.8 builders or practitioners per service owner or lead. On Gumloop's, it was 87.7 to one.
Use that composition to decide which roles to investigate and whom to ask for feedback on content. Builders can influence tool selection and may hold budget in smaller companies. A leadership title does not establish purchasing responsibility.
The ratios do not measure who saw a post or prove a platform's adoption model. They cannot predict whether a post aimed at a particular role will succeed.
The rooms: what this pull did not count
This pull ranked nothing beyond the composition of the crowd. No voices table. No events. No reactions per post.
That is a limitation and printing it is part of the method. For revenue tooling and for ecommerce customer-service AI we ranked the accounts each market follows and looked for the rooms it gathers in. For AI agent platforms at this stage we have who is in the crowd and what their titles say.
What we counted: reactions and comments on eight platforms' public posts in the UK over 90 days, the titles attached to those accounts, and how many people show up around more than one platform.
What we did not count: impressions, follower counts, private profiles, and attendance at anything.
Method: how these ratios were produced
Full method, including where it is weak: /data/method
Questions
Because the useful question for this category is who is in the room rather than which vendor holds attention. Reactions per post compares vendors against each other. A ratio describes the composition of the crowd each vendor has gathered, which is what determines whether content aimed at a lead has anywhere to land.
Because a title is a proxy. Somebody whose title suggests they sign may hold no budget for this category, and somebody with a builder title may be the person who decides in a 30 person company. People whose title suggests they sign is the claim the data supports, so that is the claim we print.
No. Builders may evaluate tools, influence purchases or hold budget. The ratio describes the titles in the observed engagement sample; it does not establish adoption patterns or campaign performance.
Botpress, MindStudio, Relevance, n8n, Voiceflow, StackAI, Lindy and Gumloop. They were chosen as the category's most visible publishers in the UK during the window. Every one of them showed the same skew, which is the finding.
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