Notes from an AI Conference: What are the AI folks up to these days?

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Notes from an AI Conference: What are the AI folks up to these days?<br>Thoughts and themes from AI Engineering World’s Fair

theahura<br>Jul 10, 2026

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Note: we are hosting our second in person Agentics event (and our first bi-weekly) at The Brass Factory on July 22nd. We’ll have speakers, food, and hopefully some boardgames too. Sign up here: https://luma.com/agentics-qz0j

Do you ever look out at the beautiful Manhattan skyline, bagel in one hand, pizza slice in the other, and wonder “What are those guys who are doing the AI thing in the Bay up to these days?” They’re always saying all sorts of weird and crazy things on the bird app that no one else but the AI people use anymore.1 Probably worth checking in.

hmm…<br>Now, cards on the table, I generally think of myself as one of those people who is doing the AI thing, on account of being the founder of an AI company and having been in ml research for years before this2 and also writing copiously on the subject of AI things. But I mostly avoid the bird app, and I don’t live in SF, so sometimes I do get some FOMO.<br>I’d heard about the AI Engineering conference a few times — a few friends at Google were previous sponsors and told me it was a good place to catch up with other folks who were thinking about coding agents on the cutting edge. Applied to give a talk, got in on the online track, and the organizers very kindly sent over a few free tickets by mistake.

They also very kindly did not respond, so I assumed the extra tickets were fair game.<br>Just got back from the Bay, FOMO eradicated. Here are my thoughts.<br>12 Grams of Carbon is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

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At a high level, the talks were split 85-15. 85% of the people there were enterprise folks who were trying to learn how to AI good. These people were interested in attending and giving talks about how to leverage more AI in their respective organizations. The other 15% of the people there were really on the bleeding edge, people who had plumbed the depths of lights off software factories and came back to tell of Lovecraftian horrors lying beneath (hi Dex!). These guys mostly were looking for less AI. I was expecting way more of camp two than camp one, and was somewhat surprised at the skew in the other direction. Even in this highly selected environment — the ~7000 people most likely to attend an “ai engineering” conference — the vast majority of people don’t really know how to use AI effectively.

Every month the AI world is onto something new. January was takeoff, February was ‘what is a skill’, March was ‘everyone has to use Claude Code all the time’, April was get the ops team on board, May was tokenmaxxing.<br>Apparently, June was the month of skill sprawl. There were a dozen talks that were variants of “how do we manage the 1000 skills that people have created in our organization?” These were inevitably packed to the brim, which should give a sense of where most of the market is. Over at Nori we solved this problem back in December (see: noriskillsets.com, a team wide package manager built on our open source local skills manager client).<br>Many of these ‘skill management’ talks landed flat for me. I think having that many skills is a ‘code smell’. In my experience the agents are very good at figuring things out from first principles. Having a skill that 1) will drift, 2) may not actually add anything new, 3) needs to be managed is more likely to create problems rather than solve them. Bluntly, I think many of the teams who are grappling with hundreds of skill files in their organizations are dealing with an employee base that is happily having the coding agents generate skills for all sorts of things without rigorously figuring out whether they are useful. This gives the veneer of “AI enabled” work without actually being so. I wrote about some of this here:<br>Agentics: Your agent skills are all slop<br>theahura<br>Jan 18

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I was also disappointed at how many talks were about some form of self-learning that involved having agents read through transcripts and automatically create skills, so much so that I wrote about it. Anything that does not have a human in the loop for context management is going to quickly spiral out of control, which is why we end up with so many skills in the first place.<br>In my opinion, you cannot really rely on the agents to write good skills for you. The process needs to be intentional. There’s a particular format that we find works. We like to bundle sets of skills into specific groups instead of just having a big pile of them with a search server on top. Every prompt with an agent is like summoning an entity from the void. The particular skills that are bundled with the agent are a big part of eking out the highest quality results. Trying to slopify the agent...