Transcript
tools, the employee or the company? Lyncomp has been through enough technology transitions to know when an industry is running faster than it can think. And right now she says that's what's happening. I see a lot of fear and confusion right now because I've been through a number of tech transitions and this one is happening faster and being marketed more and there's more hype around it than I've seen in other tech transitions like dot com, the mobile phone rollout or the internet. And so I think really the amount of stress that people are having over what is artificial intelligence? How is it going to affect me? Should I be using it? How should I be using it? Is probably the undercurrent of the entire tech industry right now. AI trust and safety. Yeah. AI governance, security. I actually had an IT person at a company that openly admitted when they saw open claw, like what fresh hell is about to become shadow IT? There's a lot that is really starting to pop. It's exciting because nobody really loves to have to do all of the grind themselves. They'd really like to have a personal assistant. But when something needs your user ID credentials, admin privileges, your credit cards, your calendar, you're taking a really interesting risk. I had somebody tell me today, oh, well, my information's all there on the dark net. But you need to really think about it when you have something making autonomous decisions that is non-deterministic. So lots of great experiments, lots of excitement, but lots for us to really keep an eye on and try and figure out what does it mean to have admin privileges or the right privileges for a staff of agents like they're humans? Is it really a user ID that you give them or is it something else? What do you do when an employee leaves the company? Do they take their agents with them? Probably not. So who manages the agents? So many things that we have not thought about. I had a blog post recently about how essentially, actually it was an MIT journal article that between December 2025 and January 2026, it's the same experience for IT that new parents have when their baby that was crawling starts walking. Because the whole idea of keeping them safe, it's a new ballgame. You're making me think, if you have all these agents everywhere, is it even possible to have sovereign AI? There's a whole question. AI governance used to be, let's have policies, let's look at safety, let's see how the model interacts with humans. Unfortunately, now AI governance has to be code. And you have to be ahead of questions around if someone has built an AI agent that has made them significantly more productive, is that the intellectual property of the company? Because if it is, then what do employees do when they've built and invested in this thing? It just by definition invites shadow IT. So there's just some things that we don't have worked out yet. I was talking with someone today at a lunch table about the fact that in the US, attorney client privilege and doctor patient privilege do not count when you're asking questions to chatbots. There is no copyright protection when you're using AI tools. So if you're trying to self-publish on Amazon, please don't use an AI image generator, unless you actually can do a lot of work on the image to prove that it was yours. Because those three examples right there, it just says our policies, our laws, our governance, we are gonna have to rethink things as dramatically as we did when people started getting connected with the internet. It feels like we are moving also towards people are doing more AI on their own. Right. Can you talk about where we're going with that? Yeah. I used this analogy earlier today. And if you remember, or you look on the internet, depending on if you're Gen Z or Gen X, when mobile phones and mobile telephony first came out, the systems that you were carrying were the size of a box. They were suitcases. If you go to Mobile World Congress, when they're announcing the new wireless technology, and they've just got it up and running, the motherboards are not phone size. They're, you know, rack size, because they're still working out the kinks, and they're still programming and tweaking the configurations for the wireless technology. With AI, we're in that kind of situation. So you got these big systems for it to proliferate, and for it to really be everywhere, the way that mobile telephony is, essentially, it's going to have to go through optimization, you're going to have a bunch of heterogeneous types of solutions, you're going to have to go from programmable to ASICs, in some cases, which is hardened logic, it only does one set of things. So what a phone call used to look like, on something that was programmable is now a hardened set of logic that only does that wireless technology. So you're going to see something similar in terms of wireless, that evolution with AI, and the proliferation of the different solution types. It goes back to what you said at the very beginning about fear. How are people getting through this time? You know, what Intel IT has done that I think is really, really smart. They are, they've always been an eat your own dog food type of IT department. And they publish a lot about what they've implemented. So they've done everything from taking natural language processing, to read tool logs in manufacturing facilities. Because as it turns out, when the technicians start getting really tense in their language on logging using the tool, that's because the system needs maintenance. And it's about to go down. So now, when they sense that the technicians are getting really pissed off, they know, oh, we should probably do proactive maintenance. So that's one use case. But they also do things where they have a common interface. And underneath it, you can swap models out. So as they find different models that are either more economical or better for a task, you don't get stuck on one model. And then they have also had a trial of things like, you know, some of the chaining, the agent chaining technologies, there's a few out there. And they watch how people are building with it, who they know are trustworthy and developers that are going to do it right, so that they know what they can replicate, and they know what's going to be a popular popular use case. Transcribed by https://otter.ai
