Alex Strick van Linschoten

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@strickvl

ML/AI Engineer @zenml_io, researcher (& author of a few books + PhD 👨‍🎓). feedback welcome admonymous.co/strickvl 🙏

Delft, The Netherlands alexstrick.com Joined January 2011

747 Following 3.3K Followers 3.6K Posts

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Alex Strick van Linschoten @strickvl Oct 14

Finally got round to adding in a way to subscribe to my blog / site via email. (Always supported RSS, but seems that's gone out of fashion a bit 🤷 )

Also added in a way to browse some of the blog series I've written over the years instead of just scrolling through a huge long list of posts.

Please do subscribe if you want to get an email whenever I write new posts!

alexstrick.com/subscribe.html
alexstrick.com/series.html

alexstrick.com Subscribe – Alex Strick van Linschoten Personal and technical writings from Alex Strick van Linschoten

Alex Strick van Linschoten @strickvl 2h

Watch me walk you through our new shiny voice onboarding agent :)

Hamza Tahir Verified account @htahir111 2h

One of the 🐐 's retweeting our launch video yesterday <3

Promised you guys a cool onboarding. Check out how it works.

x.com/CompleteSkepti…

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Alex Strick van Linschoten @strickvl Nov 1

And this one is maybe most useful, but I think a lot about these views as sort of MCP Apps that an agent (or team of agents, more likely) would propose to surface some behaviour to you. You'd get some sort of representation like this with the problematic / interesting parts colour-coded and then you can actually 'look at the data' in that way.

I mean probably even @HamelHusain would admit it's going to be hard to look at the full swarm's data past a certain scale...

Alex Strick van Linschoten Verified account @strickvl Oct 31

This stack view, my personal favourite I think, gives you the same swarm data as a 3D stack. Teams are represented on the floor, and time is represented by moving up through the stack vertically (i.e. each slice).

Failures that many teams carry out at once show up as a layer. You can click a slice or even a specific agent at a moment in time and see what the agent was doing, what messages it was sending and so on.

It's pretty easy to navigate through the swarm in this way with your trackpad or mouse.

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Alex Strick van Linschoten @strickvl Nov 1

This view of a swarm is probably my second favourite, and it's only useful if swarm activity is collocated / i.e. happens at similar times.

Alex Strick van Linschoten Verified account @strickvl Oct 31

Or skip the menus and a 3D view and pinch to zoom into the agent traces without being confronted by a wall of text..

Here you go from swarm to team to agent rows even all the way down to a message that was sent or a file that was edited. Clicking anywhere within the UI at this point takes you the specific detail that you care about.

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Alex Strick van Linschoten @strickvl Oct 31

Seeing more and more people writing about swarm observability so thought I'd post some of the work I'd been doing to think this through.

I built some tools to help AI engineers work with agent swarm traces and other signals. Specifically:

- a collector that tracks everything the agents in a swarm are doing, from filesystem writes and reads to inter-agent messages to traditional traces that you're probably familiar with
- a viewer with a bunch of different modes (see the rest of the 🧵 below for some glimpses of these) to help someone trying to understand how a swarm behaved either during or post-run
- a simple agent ('hodhod') that comes with some deterministic tools to help quickly try to slide and dice the huge volume of data recorded by the collector, which can try to help understand how things worked (or where they failed)

Today I'll focus more on the viewer component as it's easiest to understand...

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