Eric Porres, Chief AI Officer at Logitech, returns to Beyond the Prompt to share what’s changed after another year of putting AI into practice. AI use has spread across the company, but the bigger shift is where it shows up: inside the workflows, meetings, tools, and habits that shape how people actually work.
A year ago, Logitech had people experimenting with AI. Today, Eric says he can’t think of a single part of the company that isn’t building, exploring, or creating something with it.
Eric shares what helped make that happen. There’s a Build Advisor that helps employees figure out what to build and connects them with people who may have already worked on something similar. AI in Action moments are now part of company and leadership meetings. And before leadership presents to the board, there’s an expectation that their work goes through an AI Board Advisor first.
Henrik, Jeremy, and Eric also get into what comes next: how to measure whether all this AI activity actually creates value, why Eric built AI systems to manage his own information overload and sleep, and why creating something new should come with another question: what old report, process, or way of working can now disappear?
Key Takeaways
Eric's website: porres.com/
Eric's LinkedIn: linkedin.com/eporres/
Logitech: www.logitech.com/
00:00 Embedding AI Into the Workflow
00:52 Meet Eric Porres
01:15 The Cambrian Explosion of AI
06:20 Measuring the Value of AI
11:16 The Build Advisor
16:12 Keeping Up With AI
19:43 Making AI Part of the Culture
21:37 The AI Board Advisor
25:51 Building an AI Champions Network
29:15 Eric’s Personal AI Stack
32:17 The AI Vampire Problem
40:59 Building a Deep Memory
46:49 What Can AI Help You Delete?
55:19 The Debrief
📜 Read the transcript for this episode: Here!
[00:00:00] Eric Porres: Now the leadership team members, before there's a board meeting, they send their information first to the board advisor for the unbridled feedback.
[00:00:10] Jeremy Utley: Mm-hmm.
[00:00:10] Eric Porres: And, and I, and I think part of this, it speaks to a change in workflow, which is when you embed AI into the workflow of an organization or of a process, then everything follows. If you add it on at the end, then it's not as necessarily as powerful and impactful.
Hi, I'm Eric Porres, the Chief AI Officer at Logitech. I'm super excited to be back with these two gentlemen, because we were here a year ago, and a few things have changed. Models have changed, harnesses have changed, AI has changed, uh, but the work hasn't. And so I'm delighted to talk about, you know, how, how we fuse humans and AI together to build great products and, and do great work at Logitech.
[00:00:52] Jeremy Utley: Welcome back to the show, Eric Porres. You are one of our most listened to, most favorite episodes. We're so delighted to have you here. Here's the first question: What's changed?
Since our last conversation, you've been on the ground, you've been driving the transformation, you instrumented everything out the wazoo, which is the technical term.
[00:01:11] Eric Porres: Yes.
[00:01:11] Jeremy Utley: What's changed from 18 months ago, last time we had you on the show?
[00:01:15] Eric Porres: Yeah, so great question, Jeremy, and th- thanks for having me, and Heinrich, of course.
Um, what I would say is that the, um- I'm a victim of my own success- Please say more ... in, in the s- in the sense that, uh- You poor,
[00:01:30] Jeremy Utley: you poor thing. You poor
[00:01:31] Eric Porres: thing ... yeah, poor thing. No, and, and I, as I, I'm trying to figure out, like, what's the best way to say this, and it's the only, like, the tiny little path I put on myself is that we have now this Cambrian explosion of citizen-based AI initiatives that are happening across the company.
And I think that's what happens when you get to a place in which you can go from, uh, AI curiosity to competency and fluency. So I, I could not give you, uh, an organiz- whereas a year ago, I could say, "Yeah, dabbling, experiments, a little bit here, a little bit there." Uh, I can't think of a single organization within the organization now that is not building, exploring, creating something with AI as a, not just as a thinking partner, but also as a doing partner.
[00:02:23] Henrik Werdelin: Anything you know now that you would have, you know, seen kind of like a thing that happened over the last 18 months that you would've done differently? Or is it just excitement that people are now using it?
[00:02:34] Eric Porres: Uh, sure. So I probably would have done we would've done more work on, um, on token calculations, of course, you know, of, of everyone.
Like, and, and this is not to say that, that the nice thing that we've done as a company is nobody does token maxing. Like I, I, I don't know why that even existed as, as a thing. Like it was such a weird epoch and it only t- um, whenever this gets published, like in the last, you know, first, first half of 2026, um, you know, no one was actively out there to be like, "I'm gonna do as many tokens as I can."
No. I'm gonna come up with thoughtful ways in which I can apply AI to my work to reimagine workflows, to reimagine software development, to reimagine knowledge work
Uh, in, in that way. So, but having said that, Heinrich, you know, it's with, with great power comes great responsibility. And like all of us, I think we could have done, again, you can't do it, you know, a priori. Well, h- how can I
[00:03:28] Jeremy Utley: predict- Yeah, I was gonna say, would you start with that? It feels like starting with a compliance policy.
It's just like, mm- Well, no, no, no. Look, the, not- ... not really the most inspiring thing.
[00:03:34] Eric Porres: Exactly. So not, not a budget, but just a, a, a formulation of, of an expectation. Look, we, we knew numbers were going, right, it was what, Pete Steinberger who said, uh, I think he said, um, like the growth of OpenClaw was, or in his TED Talk he said it was, uh, a stripper pole.
So no, wasn't a stripper pole, but certainly a hockey stick. Right. Not just,
[00:03:53] Jeremy Utley: and for, for people who don't understand, not a hockey stick, right? Right. Not like typical exponential. His basically went nothing, nothing, nothing, nothing, everyone in the world.
[00:04:01] Eric Porres: Yeah. Right. Everyone in the world. Um, maybe except me.
But where the hockey stick growth, we, we saw the hockey stick growth coming out of 2025 in terms of growth everywhere. So adoption, usage, tokens, uh, projects, uh, et cetera. So I, again, I think we all could have been maybe, yeah, just slightly more mindful about thinking about, well, what does this actually mean?
At what point on the curve are we? And I think collectively as a, as a society Even though I feel like we've done an amazing job as a company getting people into this state of AI flow, if you will, to harken back to my old professor, uh, Mihaly Csikszentmihalyi, um, we're still only scratching the surface.
And so when I think about, therefore, on a macro market basis, when I think about what, you know, Erik Brynjolfsson has said, you know, Aaron Levie has said, and others, Jensen Huang has said, we are only, like, the demand will continue to grow exponentially.
[00:05:00] Jeremy Utley: Well, pau- pause there, Eric. What have they said?
Because I wanna make sure for folks who aren't as dialed in, I know we're all listening to the same podcast, but just for somebody to go- Oh, sure, yeah ... "Wait, wait, hang on. What did Jensen say?" You know, what did Eric say, right? What, just give, give folks, like, the quick summary of what the latest thinking from those, say, three people is.
[00:05:18] Eric Porres: Well, the, the, the quick summary is that, you know, in, in Brynjolfsson's case, we're, we're only starting to see the net positive effects of, you know, AI in terms of, uh, labor and productivity, uh, on a macroeconomic basis. Jensen Huang will say, you know, "We should dare to do more," meaning that, you know, AI is not a great eliminator of work, but it's actually a great enabler of work and of, of exploration and, and ideation.
And we have said this, you know, Haneke said this over a year ago, you know, AI will only cease to be useful to us if we run out of ideas, right? So that's like, it's, it's inherently, it's itself challenging in that way. It's like, well, are you in the idea business or are you in the, you know, widget business?
If you're in the widget business, then yeah, maybe it won't be helpful for you. And then, and then Aaron Levie and others, who I think have a pretty sharp, you know, take on the, the state of the industry, is that we're still very, very early. And so, and look, we see this in, you know, TSMC and chip manufacturing or the, NVIDIA's blowout quarter demand Greatly exceeds supply
[00:06:20] Henrik Werdelin: Here's a question for you on that.
Um- Yep ... we talked to Charlie, uh, Charles O'Reilly the other day, a fellow Stanford professor, about incubation. And one of the things- Mm-hmm ... we talked about was one of the i- issues with incubation in big companies is that, you know, when they get to, they get the projects off the ground, but then when they kind of need the, basically the A round, when they need to kind of go f- to scale it, then in many organizations there's not an infrastructure.
Amazon famously have one, but a lot of organizations don't have infrastructure. Question on, like, the use of AI. I sense that there's a little bit of a comparison there, because you see people kind of say they use AI a lot, then they say they've saved, like, endless amount of hours. And then now that the cost equation comes in, where suddenly, like, the bill to Anthropic or OpenAI is going high, then the CFO's office will go like, "Okay, but where do we have, like, the proof points?
Do we see it in our top line? Do we see it in our EBIT? Uh, what is it?" Mm-hmm,
[00:07:17] Eric Porres: mm-hmm.
[00:07:17] Henrik Werdelin: So there could potentially be this kind of risk that we're now seeing kind of like the cost go up, and we haven't really found a way of defining the successes, like, in the metric that kind of covers the cost. Sure. How do you think about all that and how do you navigate that internally?
[00:07:34] Eric Porres: Well, right, what is, wasn't it, um, wasn't it Warren Buffett who said, you know, price is what you pay but value is what you get? So, um, you know, I, I can't necessarily give you an exact value of, you know, me generally wearing black shirts every day. Um, I know it makes it easier for me in the terms of decision science in, in the morning to put, to put, to put a shirt on as, as Heinrich-
[00:07:55] Henrik Werdelin: And, and you make it an honorary Danish person.
[00:07:57] Eric Porres: Exactly, correct. And so your point is a good question, which is how do we measure, like, does it matter? Did, did it, did it make a difference? And one thing that we did early on a year ago, uh, was that... And I, yeah, actually I don't even know if we talked about it at the time. We have a project check-in tracker, simple, simple document, right?
Simple app script that I built. People can enter their information. Information is, so is, is your project, no matter how big or how small, we just wanna know about it. And, and there's a reason why we wanna know about it How big or how small is it? Does it ladder up to 2031 strategy? So one of the things that we did in late summer is we said, "Hey, now that we have this, now that we have 2031 strategy more or less in place, one slide summary, let's turn that into a markdown file so that anybody who's working with a thought partner can, you know, have in the back of their mind, 'Okay, like again, is this, is this tiny little project that I'm doing...'
Maybe you don't necessarily need to measure whether it connects to 2031 strategy. But if you're building something that more than a few of you can use in some way, create some utility for yourself that you didn't have before, then maybe you want to understand if that's connected to strategy. Great. So the intake form has its secondary connector, which is the outtake, which is to say, hey, now that you, now that we've checked in 100 and N number of projects, 200 projects, take your pick, what was the output?
Did it in fact reduce time, save costs, create value, uh, give more time ultimately back to, in a, in a sales and marketing organization, right? Like, like our, our most precious commodity, the time we're spending together right now, we will never get it back. So let's make the most of the time that we have. We all have 24 hours in a day.
Some of us sleep less to get more of that time, right? You know, Sam Altman talks about, you know, polyphasic sleep so that... Because there's just so much opportunity in AI, and I believe it, right? Like I, I built a, and we could talk about that, I built a- Oh, we'll get there. We'll, we'll, we'll get there ... a hoop MCP connected to my work to try and mitigate and mediate the, the amount of time I spend, you know, getting vampires into my, into my jugular.
Anyway, the point is that- You have to start with the end in mind. And I, and I think that's one thing that's new for many people is if you're working at a larger organization, you're working at a large organization, you don't necessarily come from, you know, Heinrich your background, Jeremy your background, even my background in a, from an entrepreneurial perspective, which is say, okay, how do I go from like a V0 artifact is great, but then how do I scale that V0 artifact and what's the impact that it's going to have on others?
And so that's why we instrumented this outtake
[00:10:33] Jeremy Utley: process which gives you- And by outtake all you mean there, Eric, is you're closing the loop. You're saying, "Hey innovator." To, to, to go back to Heinrich's question about kind of explore, exploit broadly. He, he's asking how are you cultivating exploratory capacity?
And what you're saying- Mm-hmm ... is we're having folks not only tell us about the new stuff they're doing, but then we're proactively, call it reaching back out to close the loop with them and say, "Did you validate your hypothesis? What did you learn? What was the impact?" Is that a basic summary of what, what you're getting
[00:11:03] Eric Porres: at there?
Yeah, that's a great... That, Jeremy, you, you, you alwa- you always say it better, more succinctly than, than I do, which is, um, which, wh- which is in fact that, right? So scientific method at its, at its purest form is, okay, here's a hypothesis, validate the hypothesis, what can we learn from that? Now, what we did, what we've subsequently done or what we've done in that work in that timeframe is we built...
So we're a Google Workspace company and we don't just exclusively use Google, but Google Workspace is pretty helpful because we created a gem which is what others would know as a custom GPT if they're in, if you're in the, in the, in the ChatGPT world And that Gem is a build advisor. And the build advisor says, "What are all the surfaces that you can build safely and securely, uh, within Logitech?"
So whether that be a Workspace Studio flow, whether that be an Apps Script, whether that be something, an actual agent in Gemini Enterprise, whether that be something you can do in LogiQ. But one of the parts of the knowledge of the Gem goes back to the project intake and outtake form, such that Jeremy, if you're starting something that's net new to you, what might be new to you may not be new to Heinrich.
And so now I'm already giving you a head start because now another citizen, a Heinrich, can come to... Or you can say, "Oh, you know what?" Or the Gem will say, "Hey, Heinrich, sounds like the project that you're thinking about," right? So that it does an interview, first principles interview, help me understand what you're trying to build, what you're trying to accomplish, what are your goals, objectives, et cetera.
"Hey, you know what?" Mm. "That sounds a lot like Heinrich's project."
[00:12:35] Jeremy Utley: Yeah. "
[00:12:35] Eric Porres: Maybe there's something you can learn from Heinrich. Please talk to Heinrich."
[00:12:39] Jeremy Utley: Uh, and so- So you're saying that the Gem, which I love, the build advisor, I think there's two levels there that are worth calling out. I just wanna, you know, codify that- Mm-hmm
or bookmark it. Sure. One is it's been instructed what are kind of the toolkits, uh, in the sandbox-
[00:12:52] Eric Porres: What's the, what are the ingredients? ... that someone's allowed to play with. Yeah. What, what are the ingredients that you have? You're a chef, you're going in to work with the master chef, master AI chef.
[00:12:59] Jeremy Utley: Mm.
[00:12:59] Eric Porres: What are the ingredients you have that you can work with- Cool
safely and confidently across, across the universe, across the 7,000
[00:13:06] Jeremy Utley: people across the world? It's almost like what are the ingredients and then what is in the fridge already, to use like another metaphor, right? Like, "Hey, Heinrich, Heinrich's actually made this dish." Yeah.
[00:13:13] Eric Porres: Yeah. What are some of the recipes that have been tried- That's cool
across the organization to solve maybe this particular problem that you, that you've identified yourself? But look, because you're in working in a 7,000-person organization, different regions, different business groups, different countries, different social folkways, mores, et cetera, um, how do you... You, you won't, you won't know- What all 6,999
[00:13:36] Jeremy Utley: other people are doing Can you, can you talk about what is the impact of that?
Like, uh, just of the Build Advisor, and it could be anecdotal, but what are you hearing from folks who go to the Build Advisor for understanding of tooling available and kind of prior art? How does that then impact their go forward?
[00:13:50] Eric Porres: Oh my God, it's been phenomenal. So again, again, victim of my own success, quote unquote, is, or victim of our collective success is now that we have...
It's, it's the cold start problem, right? Yeah. So y- and you've talked, both of you have talked about this m- many times on this show and in other places. Staring at the blank page, how do I... Oh, I wanna get there. Okay, yes, I can work with AI, but now, oh my goodness, not only can I work with AI, but I can also work with a human-
[00:14:17] Henrik Werdelin: Mm
[00:14:18] Eric Porres: who has tried to solve this problem a- as well. So it's almost like if we think about, and, and, and Bryce has talked about this before, and it's, it's Bryce Jalamel, um, there are more chess masters today than ever before because they have now worked with computers, uh, and such that it's like it's the combination of the two of them are more, are more impactful than one or the other working on its own.
I would say the same thing applies here, and this is one of the, I think, key takeaways is, right, like the cold start problem is no longer, "Oh, let me just th- work with my thought partner." Well, that's, that's great, but where's the human in that other than yourself?
[00:14:53] Henrik Werdelin: Yeah.
[00:14:54] Eric Porres: Um, so like- So cool ... the, the, the, the democratization of AI truly means it's more than just, it's more than just technology.
It's also people and process that that can support it, and I think that's very, very powerful because right now In large respect, right? There is a fear of, well, I'm just giving my work away, or I'm, I'm working with a machine. Where is the human? And this also closes the loop on, I think, on the human experience-
[00:15:21] Jeremy Utley: Hmm
[00:15:22] Eric Porres: uh, as well. And so what I am seeing is n-number one, um, that gem is the most used gem in the company, 'cause we have company, we have shared, shared company gems. Uh, number two, the projects that then get started start from a place of confidence because, hey, I... now I know what the ingredients are versus what they're not.
Now, there will always be exceptions, right? There will always be people who have, uh, either certain roles or certain experience where they wanna build, like above and beyond and then like, you know, pray, pray, "Hey, this project will get enough, uh, um, energy around it that, hey, we can deploy it in this way that's kinda non-standard."
And look, there will always be non-standard projects. There's a bell curve of projects, right? Solving for the bell curve, though, gives the bell curve a much higher slope, and I think that's where we are right now as, uh, as a company.
[00:16:12] Henrik Werdelin: Now, I was curious a little bit on if you... Do you think that there is kinda like these plateaus that you hit where humans have to kind of catch up?
Or do you think that the experiential curve that we see in the AI world, kind of outside the organizations that we work in is kind of, yeah, yeah, that we'll see the same curve internally? Or like, what, what... If you look at the next six to 12 months, is it just more?
[00:16:41] Eric Porres: Well, so yeah, so, so I th- I think if you were to zoom in, and it was funny w- as, as you were saying that, Heinrich, because I was thinking about that before, which is if you zoom in on the curve, what you actually probably see are these little-
[00:16:53] Jeremy Utley: Mm-hmm
[00:16:53] Eric Porres: these little plateaus. Now, ordinarily, in, in, in the, like, a technology timeline, you would see those over a longer period of time, right? So whether that be the Gartner hype cycle, you know, peak effect, you know, trough of disillusionment, and then, and then moving on. I don't think we're necessarily in the, I don't think we're in the trough of disillusionment phase anymore.
But I do think there are these slow and steady peak, plateau, peak, plateau, peak, plateau. So what do I mean by that? What does that mean in practical terms? It means that either the next generation of Model X has become sufficiently capable such that the, again, using the term from Ethan Mollick, the jagged frontier has, I think, become less, slightly less jagged, so there's more of a curve than there are spikes.
It's like analog versus digital, I suppose, in that way, which is weird 'cause analog, humans, digital, machines. Um, but the... So yes, there are plateaus because when something new comes, you're like, "Well, shit, what did I not understand or what did I think the previous model wasn't capable of that it is now?" But that also means then that you have a responsibility as a builder to think about, like, to not be so wed to this idea that this thing that you built six months ago because the technology wasn't there yet- Hmm
is suddenly there, and now you have to let go.
[00:18:13] Henrik Werdelin: Mm.
[00:18:13] Eric Porres: You know, you have to be able to let go, and I don't necessarily agree or disagree with Jack Dorsey on a lot of things, but I wanna say 10 years ago, he did an interview in the Twitter days where he's like, "Yeah, I've, I've said no. I've had to let things go.
Things have fallen on the cutting room floor a lot, and I have to be okay with that." Um, you know, this idea of saying or, you know, subtract Leidy Klotz, uh, I have to, I have to say no to more things than I say yes to. And so what that means, where I'm going with this, Heinrich, is And I've written about this, uh, a lot in the last six months, is this notion of, you know, skills as software and abstracting the capability that you're building into a layer that any agent in the future, any harness, any control plane in the future can really understand and take advantage of.
So to a certain degree, like the, the, the PRD or the PRD that you're writing and building over time becomes even more important because now you can give, you can give that document rather than writing a piece of software to do the thing you want to do, you can give that document and that set of instructions to this capable AI, uh, partner that you have that is able to execute it for you in ways that you weren't able to do it before.
Do
[00:19:25] Henrik Werdelin: you have other of those concrete kind of suggestions? I mean, obviously skills as software is like a very concrete thing. Like, what are the things that are going on internally at LogJack that you kind of go like, "This is what other people who is not as far down the, the slope as I am should do"? Or, or cases that we see has just worked very well.
[00:19:43] Eric Porres: Yeah. No. Good, good, great, great question. So, um, so the buy-in, leadership buy-in And I mean leadership from the top, Hanukkah, right? So leadership buy-in is, especially in an enterprise organization, super important. What do I mean by that? Every global huddle that we have as a company, there is an AI in action moment.
So every month there's a different group, a different organization, so it's not representing, it's not IT, it's not marketing, it's, it's everybody has an opportunity to contribute to the AI in action moment at the global huddle.
[00:20:16] Jeremy Utley: You're saying this is codified, this is a priority. Whenever we globally meet, we spotlight something about AI.
[00:20:22] Eric Porres: We spotlight something about AI, and that, and that AI contribution can be something, um, as, that you might think of as, as pedantic, like, okay, supply chain logistics organization. But okay, nevertheless, okay, that's, let's, let's actually shine a spotlight on something which most people might think of as, ah, that's kind of boring and, and, and uninteresting to me.
Um, so it's, it's, we're not, we're not necessarily looking at all of the, like, the stars and dogs, so to speak. Like, there are some stars, there are some dogs which we then promote and are become stars of the show. It's also at the leadership team level, so every week the leadership team has a, an AI in action moment within the leadership team as well.
So it's not 18 people going around the table for, you know, 18 minutes, it's more like one person or two people sharing something that they're doing either personally, professionally, uh, for themselves, or representing, someone will come in and present to the leadership team, "Here's something that we're doing in Game Year, here's something that we're doing in- Do you, do
[00:21:18] Jeremy Utley: you facilitate that?
Does Hanukkah? How does that, that-
[00:21:21] Eric Porres: Oh, Hanukkah, Hanukkah does. It, it, it became... I, I, we, we talked about it and, and I said, I said, "I think this is really, this is, this is super important." She, and she's like, "Yeah, I agree." And so now, so it's codified at, um, at that level. Codification, and we didn't have this when we talked last time, another gem that we built is, because Hanukkah talked about this at the Women's CEO 50 event at Fortune in October, uh, was, you know, she talked about having an, an AI board member, and, and what does that mean?
So what do we have, our parallel to that is we've built, and I worked with, um, Sam, our, our head of legal, and also Jay, head of digital office, and Hanukkah as well, to create a gem, a board advisor gem. And the Board Advisor Gem, by the way, is available to anybody in the company. And so now, uh, the board advisor tries to play the role of, you know, could be curmudgeonly board advisor.
It can use the Socratic method. Uh, it's a reasonably, I would say, reasonably advanced Gem that we iterated on over the course of, you know, six weeks before we made it available in December. And now the leadership team members, before they go to the board, before there's a board meeting, they send their information first to the board advisor for the unbridled feedback.
[00:22:38] Henrik Werdelin: Mm-hmm.
[00:22:38] Eric Porres: And, and I, and I think part of this too, Jeremy, it speaks to a change in workflow, which is when you make-- when you embed AI into the workflow of an organization or of a process, then everything follows. If you add it on at the end, then it's not as necessarily as powerful and impactful. And this is the same thing with training, right?
If you're like, "Okay, well I'm, I get, I need to get trained in AI." Fine. What is it gonna do for me? But if the leader, if the person that you're working with says, "Hey, you know what? As part of our embedded process, we are going to make it part of our process where we have to work with AI in some way, shape, or form," then everything follows, uh, from, from that.
[00:23:22] Jeremy Utley: So members of the leadership team in that case then are requi- It's not just that this board advisor Gem is available, it's actually, uh, baked into the workflow. Prior to you submitting your slides for the quarterly board r- Yep ... readout- Yep ... you must get feedback from the Gem board advisor.
[00:23:40] Eric Porres: Is that right?
From the board advisor. Yeah. Mm-hmm. From board set. We call it, we call it board sets. Um, now again, I, I won't speak to, 'cause I can't, and I, I won't speak to the mechanical codification of that as like does, does every single person as part of the leadership team do that 100% of the time all the time? No. But it's an expectation.
So right? It's, it's like that's the expectation. And, and what I find too, when I, when I use-- I, I always learn something from the board Gem. I always learn something from... We have a presentation coach Gem. The other most popular Gem that we have is a presentation coach, where I've inserted lots of different great presenters, whether it be, you know, the, the cynic why, how, what.
Whether it be, you know, Spielberg, uh, thinking about ways in which we present ourselves, right? Because as, as much as we have technology- What are we? We're storytellers. We, we have to create a, a compelling narrative. And when you're, when you're trying to create compelling narrative in slides, like that is inherently a mismatch in terms of like when you're sitting around a campfire, are you gonna present a slide?
No, you're gonna tell a story. And so when we have to create presentations, we often lose some of the humanity that's associated with that. And so ironically, a presentation coach gem brings some of the humanity back into the story, uh- Mm ... that, that you're try- that you're trying to convey. So, so Heinrich, that goes back to your question.
So the codification of embedding AI into, uh, workflow and business practices is one. The board sense gem is another. The having a champions, a very public champions group of a hund- now 175 people across the world, uh, is another one. Because not only, again, for as much as I think we can kind of, you know, catch and, catch and release using the AI builder gem- Right, that only, that only gets you so far, right?
That, that'll, that... May-maybe that catches 50% of ideas. The other 50%... Or it's the water maker, and, you know, half of my ideas are good, I don't know which half. Um, the other 50% is then caught and, and extended through having a very public and active champions network.
[00:25:51] Jeremy Utley: I wanna get to deletions, 'cause that's something I know that you've been thinking about, and so that's kind of just earmark, that's the next thing.
Mm-hmm. Would you drill into champions network just a little bit more? Practically, how do you cultivate that? It seems like that's kind of a community of practice who's deputized to spark ideas and, uh, and availability as a resource in the organization. Correct me if I'm wrong, but can you say just a couple more lines- Yeah
about how does the champions network work before we get to deletion? 'Cause I know that's another- Sure, sure ... big principle.
[00:26:20] Eric Porres: Yep, yep. Um, so champions network is an entirely volunteer organization. Uh, I started it in June of, June of last year. Uh, it went, and then it's, you know, it's grown, and we have some people that, uh, that matriculate in and out.
No one necessarily... Well, people sign up for extra work in, in, in some way, shape, or form, and the extra work is, hey, if I am in the legal organization, I have... There are two people, or now, now there are more, now there are five people, but there are two people in the organization who started as champions saying, "Hey, we're going to actually team up together," because they're different parts of the organization in terms of what they have to do from a, from a law perspective, and how do I take this embedded knowledge that I have built over the N number of months and then share it with rest of organization?
Uh, there are other champions that are, because we have physical offices in different places around the world, uh, there are other champions who are site leaders, if you will, for, um, within, in, in Cork, as an example, right? Hmm. We have a reasonably big office in, in Cork, Ireland. They're the ones who are running the local huddles, and there's an AI in action moment that happens within the, the physical set sites.
And so when that happens, then you have, you know, champions who are part of the, the, the steering committee of ways in which to bring capabilities in, in, and interesting projects that are taking place in, in a, in a physical location, and representing it to each other, in addition to running the weekly office hours, as an example, right?
"Hey, I'm here. I'm, I'm working on..." And, and I still do it today. In fact, as soon as we finish this session- My next session is an hour where it's an open Zoom, and sometimes- And anybody can log
[00:27:58] Jeremy Utley: on with a question or,
[00:27:59] Eric Porres: yeah ... anybody can show up with a question. Sometimes two people, three people, five people, sometimes no people show up, and that's okay because people are busy, which I get.
And so, but that hour for me is a dedicated hour where all I'm thinking about, all I'm going to work on something that is wholly AI enablements and, and related. So what I'll probably do, if nobody shows up in that hour coming up, is I will work on, okay, here are some things I've been thinking about, now I wanna share it with this...
We have, so we have a private group chat of 175 people, and those champions also, by the way, you also have like what are the, why do you show up to be a champion? Well, you get certain perks. Uh, like maybe you get access to models that become available before others. Maybe you get access to, uh, new capabilities that we're working on that are still in development within our own control plane harness that we'd built for ourselves.
Maybe you get access to MCPs that are, you know, governed and secure and capable, uh, that we wanna push out to those, uh, ahead of time. So, you know, champ- champions are, are the, get, get the first look at, uh... One of the perks is getting first look at technology. And another perk, of course, is this goes back to from the top, um, couple of champions a quarter have lunch or dinner with Hanaka, depending on where she is in the, in the world.
Ooh.
[00:29:15] Jeremy Utley: That's
[00:29:15] Henrik Werdelin: cool. Hey, Erica, let's pivot a little bit over to, I know that you have, like a pretty robust personal kinda like set of tools. And so do you mind just giving people the latest on what is your current setup on a purely personal level? Like, do you have stuff that you just run on your own computers, and do you have a difference between that and your, your work computer?
And like, what is your, uh, what does your stack look like?
[00:29:40] Eric Porres: Sure. Um, so my stack right now, uh, I've got two screens open. Your, your one. My second screen is, uh, my f- my... I think we talked about this the last time. My five open tabs are still ChatGPT, Claude, Gemini, Logicube, Notebook. Those are the five places.
And, and in my, my other second screen here, I have, uh, Cowork. So I've, I've been a, a, a big user of Cowork since it came out in, in January. And I would say that for me, the blends, you know, because all I think about, think and do and create is, is something related to AI. I have certainly spent a, a good, a healthy portion of my time in Cowork and inventing ways...
I, I did not feel comfortable with my own capabilities to truly sandbox OpenClau when it first started. And so I said, "Okay, well, what are, what are the alternatives for me?" And I said, "Well, I, I f- I feel good enough about, you know, Anthropic and its practices and systems, et cetera, that I'm going to take the leap and really dive into Cowork."
And so within Cowork, not only are there the, right, the regular connectors, but as you were describing, Heinrich, I also built my own MCPs that run on this very computer here that I can connect to anywhere around the world. And those consist of, uh, there are f- really five MCPs that I created. One is for, uh, WhatsApp, as, as I'm sure many your listeners a- as, as well as myself.
And this is, this is also publicly available on my, in my GitHub repo.
[00:31:07] Henrik Werdelin: Such a difficult MCP to get to work, right? Like, you kind of have to re-auth it a bunch. You have to, uh- Yeah, you have to re-
[00:31:12] Eric Porres: you, you re-auth. Well, although the, the authorization now is actually much easier with the Baileys. Anyway, the, the point is that we are all part of many communities of practitioners, thinkers, learners, doers in some way, shape, or form.
I do not have the time to read all of them. So what I've done is I've created a skill that codifies what I'm interested in and what I'm not interested in, and then I apply that skill to a daily summary of the conversations that are happening in six different WhatsApp groups of different AI practitioners.
There's some overlap with some, but there's some that are unique. So what do I want to learn that is unique to each group, a practitioner group versus one that's more macroeconomic theory, et cetera, and then also, what's the, what's the crossover? So that one has been super, super helpful. Uh, the next one, and we talked, Jeremy, you talked about it before- is Whoop.
So I've been a Whoop member since 2020, and what I found s- uh, earlier this year with the arrival of co-work, is that I was spending so much time, um, I became, you know, as the Simon Willison, I was, I was bitten by the vampires. And as I, as I know-
[00:32:18] Jeremy Utley: Eric- ... both of you ... do one click into that for folks who aren't familiar with the...
'Cause that was gonna be where we go next, and you just went there. So for folks who aren't familiar with the concept of the AI vampire, would you just kind of describe the concept and then talk about your own victimhood?
[00:32:32] Eric Porres: Yeah. Oh, sure. Well, so like, so the, the great thing about, about working with AI in this way, it's like, it's the perfect slot machine in terms of variable intermittent reward.
So, um, you could be working on, you have, you have an idea that you want to bring to life, uh, this, you know, this, this WhatsApp problem, and you build something and you're like, "Ooh, wow, this is amazing. It works." Then you're like, "But crap," and as Henry, "Oh, the authentication was crap." So then you go back into it and you work a little bit harder.
Like, "Oh wait, but I know it's gonna work this time. Let me deploy that piece of code again. Let me test it myself." And then, you know, sooner or later you're like, "Oh wow, it's 4:00 in the morning." Uh, and because the variable intermittent reward of reward cycle of building in this way, build, test, iterate, refine, something broke, okay, and now ooh, and by the way, ooh, now that I just built this, ooh, here's another idea.
And so, like, your, your idea, idea flow can almost happen in perpetuity- Right ... hence the polyphasic sleep and, and the other things. So-
[00:33:25] Jeremy Utley: And they call that being bitten by the AI vampire. They call that being- So basically saps your life- Yep ... without you kind of even being aware of it. It drains your life, and it's this sense of productivity, discovery, et cetera, and what basically gets sapped is your sleep or your...
Right? Is that... Am I, am I summarizing right? Sleep,
[00:33:42] Eric Porres: relationships, health, taking a ta- take your pick. So-
[00:33:45] Jeremy Utley: Yeah. And this is a well-documented phenomenon. This is a well-documented- It is a, it is a- ... phenomenon. Right. Yeah.
[00:33:49] Henrik Werdelin: I had that the other day when my wife came into bed, and I was sitting there talking, you know, through my, to my bot.
[00:33:54] Jeremy Utley: Conversing
[00:33:55] Henrik Werdelin: with your- And, and, and she was like, "You really rather would like to talk..." My main bot is called Iggy. And she's like, "You would rather talk to Iggy right now than talk to me." I was like, "Kind of." And you're like, "Okay,
there's
[00:34:05] Henrik Werdelin: something
[00:34:05] Jeremy Utley: wrong here." You're... No, Henrik's, Henrik's famous line is, "Not, not that."
Okay. But, so Eric- Yeah, that's- ... what have you done? What have you done, you know, configured to protect yourself from the vampire? It sounds like- Exactly ... I'm hoping you have a solution for us.
[00:34:19] Eric Porres: Well, I do have a solution for you. And so in, in, in my case, uh, because I've also measured myself in some, you know, part of the quantified self movement for, you know, over a decade, um, what I noticed is that, you know, my, my sleep, you know, unsurprisingly was, was suffering.
My sleep quality, sleep score, I know for me, it's one of the most impor- like, what are the things, right? Like nutrition, morning sunlight, sleep, and regular sleep. So, you know, no matter like- Going to bed roughly the same time, getting up roughly the same time. That was not happening. So I said, "Well, what can I do to change that?"
So WHOOP has an API, and so I said, "Well, I can take... I can turn this API into an MCP," 'cause if I turn it into an MCP, then I can use Cowork to converse with it, or I can, I can fetch that information. By the way, Cowork also has a, an iMessage send/receive capability. So in the evening, I can look at my overall strain.
It will look at my overall strain and capacity score from the last 24 hours and say, "Hey, Eric, you know what? Probably time to put the pens down or, or close the computer." Um Relax or, or, or don't do, do- don't do anything. So that's in the, that's the evening, that's the evening check-in. Um, if my score in, for those of you who either use WHOOP or, or others, right?
If I'm in the kind of the yellow or the red zone, then in the morning, so I have a set of alerts and summarizations that take place in the morning for me as well. And it will modulate the amount of information I receive first thing in the morning on the basis of my recovery. So if my recovery is crap, I'm not gonna get that same kind of feed, uh, that I would get versus if my recovery is in the, in the green, if you will.
[00:36:01] Jeremy Utley: And you're saying, you're saying the AI has enabled you to summarize and to access information that would b- hitherto be u-un-unimaginable, and your default is, "I wanna consume it all." Like a, you know, like somebody at a buffet, "I'm just gonna eat everything." And what you're saying is, you now have a data-backed governor on how much information you get fed, which is based on your recovery, and if your recovery is poor, the AI goes, "Buddy, the buffet's closed today."
[00:36:30] Eric Porres: Yeah.
[00:36:31] Henrik Werdelin: 100%. It's, it's kind of interesting 'cause I think we obviously were all reading the habit books, you know, like back five years ago, right? Like the best way. And it is interesting how I think many of us who's very deep on AI now is not trusting ourselves to build the habit, but we're trying to get the agents that we work with to basically nudge us towards it, right?
So same thing, like my start, like every time after 10:30 that I say, "Hey, we should start working on that," it goes like, "
[00:36:55] Jeremy Utley: Yeah, but maybe we should wait until tomorrow 'cause, you
[00:36:59] Henrik Werdelin: know..." Maybe we should wait tomorrow. May-may-maybe, maybe you should really should. And, and what, but so Jeremy, right, is the ultimate proof is in, is, is the,
[00:37:04] Eric Porres: the, it's in the
[00:37:04] Henrik Werdelin: proof,
[00:37:05] Eric Porres: which is, right?
You know, whereas before my sleep score, my recovery score was trending into the like 60s, um, now my sleep score and recovery is trending into the 80s.
[00:37:16] Jeremy Utley: You have quantitative evidence that
[00:37:17] Eric Porres: this is working. I have, I have quantitative evidence that, that this is working, and I, and by the way, I'm reading like more physical books now and doing things in the evening other than what I would be doing with-
[00:37:27] Jeremy Utley: For folks who are watching the video, Eric just held up a copy of Leidy Klotz's Subtract as an allusion to a previous guest that we had.
It's a great book. You should read it. Eric, I'm still dying to get to deletions, but I, but you've like tempted me down this rabbit trail. How many others at Logitech have you assessed are suffering from the AI vampire? And is your MCP-powered, WHOOP-powered quantitative solution helping them as well? Like I just wonder, if you think of yourself as a lead user, so to speak- Yep, good question
are there a lot of other people getting bitten by the vampire, and are they now asking you for intervention support as well?
[00:38:05] Eric Porres: Well, uh, so, you know, prior to this role, I had, um, I had run an innovation software group within Logitech as I had sold my company to Logitech about meeting performance and meeting hygiene, et cetera.
And what I led was something called Smart Habits, which is still available. It's a piece of software, smarthabits.logitech.com. And, and Smart Habits was all about finding the space between the space, something you hear a lot about in jazz, uh, which is, hey, if you're working for a certain period of time, you're probably not hydrating, or you're probably not doing any deep breath work, or, you know, take, take a break from here or you know what?
Stare off into the distance for 20 seconds, you know, 20 meters for 20 seconds- Mm-hmm ... so that you don't have eye strain, right?
[00:38:47] Jeremy Utley: Right.
[00:38:47] Eric Porres: Most people in, in the world, in the United States specifically, uh, 75% of people are chronically dehydrated. So, like, what Smart Habits did was it would nudge you to encourage you to hydrate more in the morning versus the afternoon.
This light that, that works behind me right now, this light is set to the circadian clock of this area of the US where I live. And so the light will change its intensity as well as its color throughout the day because you want as much light in your eyes as you can in the morning, uh, and then you gradually want to reduce the color and intensity during the evening.
So this notion, uh, this nominal notion of habit creation and habit enforcement is something that's been deeply embedded in me. But even then, again, you know, in spite of that, right? Like, I still needed to instrument-- I still needed a way to not only instrument intervention, but then also have a way to measure it a- and ultimately thinking about, you know, adding, you know, adding years to your life and life to your years.
Like, I wanna add life to my years and, and sleep, as we know from science of the last, you know, century, especially the last 20 years, is one of the most important ways to do that.
[00:39:53] Henrik Werdelin: Can we get back to, you had two MCPs that you mentioned. You said you have five that you use. Sure. Can we, can we get back to the other ones that the person who's about to copy everything that you're doing?
Right.
[00:40:04] Eric Porres: We talked about WhatsApp, we talked about Whoop. Um, LinkedIn, believe it or not, there is a way in which you can create a LinkedIn MCP such that, uh... So because, right? Like I, I've, I'm-- There's certain things I'm interested in, there's certain things I'm wholly not interested in. LinkedIn is, is j- recently announced, right?
They're, they're getting, or at least they're, they're deprioritizing with 94% accuracy, like the amount of AI slot commentary that shows up in LinkedIn posts. I spend very, very little time in LinkedIn now than, than I did before because again, similar to WhatsApp, I have a skill. Here's what I'm interested in.
This is the kind of content that is relevant to me in my role, the people I follow, the people I pay attention to, and please summarize that for me rather than me having to hunt, peck, click my way through, okay, I wanna find what Jeremy's saying, I wanna find what Heinrich's saying, I wanna find what Ethan Mollick's saying, I wanna find out what Bryce Shalamon is saying, I wanna find out what Greg Chubb is saying.
Now I can have that, you know, summarized for me in, in a much more, uh, intelligent way. The most important one, Heinrich, for me- is a, and it's not just an MCP, but it's also, is that there's an entire system and it's like, it's, it's a whole session of its own. I wrote about it. People can find it. Um, the blank page is not deep work I built my own memory palace of every conversation I've ever had, every coding session I've ever done with AI over the last three years is now retrievable via either MCP or, or a direct call to, uh, a Supabase instance, which is now has, uh, Voyage.
Uh, so Voyage is a, is a company that's now owned by Mongo. Voyage does embeddings. Anthropic actually recommends Voyage for its embedding. So I've embedded my knowledge to cr- help me in the future. Every new session I start, almost every new session I start in a certain project, I say, "Help me use, use Deep Memory," which is what I call it, "to help me build context about some of the things that I've been thinking about in this topic."
[00:42:02] Jeremy Utley: It's like, remind me what I think, what I think about this, or remind me what I've done with this. Remind
[00:42:05] Eric Porres: me what I think about
[00:42:06] Jeremy Utley: this. Yeah, exactly.
[00:42:06] Eric Porres: Yeah. Yeah. Because, because, and, and, and because I can... Because it also has some pretty intelligent re-ranking that you can do on, on the moment of, of demand, uh, the chunking, the embedding, and the retrieval now become part of my...
It's just, it's part of my workflow. I cannot begin to describe in the time that we have left, uh, how valuable this has been for me. Like, imagine every conversation you had across all of the surfaces, so whether that be Gemini or GPT or Claude, cowork, coding sessions, having that all retrievable at your fingertips.
You
[00:42:39] Jeremy Utley: know, when it's- Give, give us one discrete example of it impacting you in a meaningful way. Just so f- because I think that will really help people imagine the possibilities. Uh- What's one time that you go, "Wow, Deep Memory totally changed the trajectory of this piece of work or undertaking"?
[00:42:57] Eric Porres: Yeah. Mo- so, so most of the presentations I, I give, um, when it, when it comes to presentation building, like, hey, how do you build a presentation?
Well, you need to build it with context. Um, what is your context? Is it personal? Is it professional? What are the co- concepts that you have explored, thought about, tried and failed, or better to try and fail than, than fail to try. Uh, and so I will say, "Hey, I am thinking about creating a presentation for the following.
Use Deep Memory to... Here are some hypotheses I have in this for, for this, for this particular presentation or article for writing." I want to go back first and think about, like, have I covered this? What have I covered before? What have I thought part of the way through? Have I built something and broken something?
And have I invalidated a certain hypothesis that I had? Because, again, because, like, the role that I have is one where it is truly horizontal in nature, um, that it is hard to sometimes keep track. Sure. It, it is legitimately hard to keep track of, of all the different projects and work that come through my brain, and so I want to use this as a way to ground, to provide some kind of pivot point for my own thought- Because it's like, okay, I now have this fulcrum, now I want to be able to move the world in this direction based on this fulcrum, and this fulcrum is based on the building my, my own context of how I've thought about an idea or a topic or a project.
Or, and, and also time-bound it too, Jeremy, right? 'Cause something I thought about two years ago may not be relevant today. And so that's where you can do re-ranking and retrieval, and there's some interesting ways in which you can build re-ranking of your own thoughts, um- You know,
[00:44:34] Jeremy Utley: it's interesting- ...
[00:44:34] Eric Porres: using, using a time horizon
so
[00:44:35] Jeremy Utley: it, from a cogniti- So one, one kind of age-old tactic of innovators, scientists, et cetera, is keeping a commonplace book, you know, of favorite quotes, favorite anecdotes, et cetera. It could be a Spark file. Different people have different names for it. But the only way it's valuable, like, this is just, like, a fun kinda anecdote, not to mansplain neuroscience, but the only way it's valuable is if you read that, right?
So Steven Johnson, who we had on the show, is one of my, you know, heroes of authors. He has a three-monthly habit of he always rereads his Spark file.
[00:45:06] Eric Porres: Mm-hmm.
[00:45:06] Jeremy Utley: Um, and it's, you know, it's hundreds of pages long. But, but the point is, there, there's this idea that Jim March, he mentioned the, that there's something to what he calls the simultaneity of arrivals, that it's when two...
He calls it the garbage can theory of innovation. That primarily innovation consists of the simultaneity of ideas arriving. And if you think about your brain as kind of hurtling through time and space-
[00:45:29] Eric Porres: Mm-hmm ...
[00:45:29] Jeremy Utley: an idea that you had two years ago is, is completely relevant for different reasons today than it was a year ago, right?
And now, with Deep Memory, I think it's kind of cool that it basically effectively, it expands your surface area for the simultaneity of arrivals. Which is a very- Well- ... nerdy-sounding statement, but I think you know what I mean It's,
[00:45:46] Eric Porres: it's, it's nerdy but lovable, Jeremy, and you're right, because the other thing I have here you don't see here is- Nerdy but lovable
I have, I have, I have this, I have this whiteboard, and I could not work... Uh, people who work, who've worked with me over the last 20-plus years know that Eric does not work anywhere without a whiteboard. And so the whiteboard is a place where I start to piece together some concepts first, right? So the concepting is, is, is, is blank page, but it's blank whiteboard in this case.
And it can be little points of light. And then I say, okay, now that I have this, sometimes what I'll do, Jeremy, is the other thing I've done with Deep Memory is I've now created an, the ability to create an embedding. I take a picture of this. I say, "Remember this." It immediately posts it into, into Deep Memory, and now I say, okay, now that you've remembered this point in time, now I want to go explore these vectors right now.
And I don't want to, oh, let me go back. Oh, what was that thing I did? Oh, what was that project that was... Oh, cra- And then you're spending all that time- Going through retrieval-
[00:46:44] Jeremy Utley: Yeah ...
[00:46:45] Eric Porres: when instead I have the in- the, the retrieval instantaneously.
[00:46:49] Jeremy Utley: Dude, you just gave me- And so you can- ... such a cool idea for, for my own life, which I'll tell you offline, but thank you.
It's right here, and I can't... Okay, before we wrap, we have to hear about deletions b- just because I've been, I've said it now five times. So I, and the r- and the context I wanna give here for the listener is- Sure ... Eric just, and I'm gonna give you a compliment, so plug your ears so that your head doesn't get too big.
I think Eric has done probably a better job of instrumenting AI adoption in his organization than anybody I know, and there are lots of really cool things that Eric could show us. If we had two or three hours, he could show us, you know, by person in the organization, their proficiency in all different ways.
And yet, you've written quite eloquently recently, Eric, about there's a better measure than maybe typical metric dashboards are measuring, and you- Mm-hmm ... you talk about deletions and also creation. Can you talk about why that's so important and how, how leaders and maybe, call it transformation architects should be thinking about what, what metrics they really should be tracking?
I feel like we'd be remiss- Yeah, so- ... if we didn't give you a chance to talk about this.
[00:47:53] Eric Porres: Well, no, it's a good question, and, and I don't think I... It's, it's certainly not perfected in my own mind or in, in my own practices. W- what I will say, and, and we talked about this earlier, this, this notion of, you know, Dorsey saying no, um, and leaving a bunch of things on the category floor, is like it's, it's really getting to...
Deletion is about getting to the essence of, essence of the thing. What are the core... Like if, if I, if I go back and think about, you know, my, my martial arts practice of 20-plus years, there are a certain set of routines, motions that one can go through, whereas like if you understand those motions, those basic forms, um, it is the building block for everything.
Piano. I've played piano since I was four years old. Um, scales, right? Practicing scales. You know, as people talk about it, you know, practice makes perfect, but it also makes permanent. Scales are the building block. So when you start adding things on top, right, layers upon layers, upon layers, upon layers, um, you can dilute the essence of the thing you are really trying to master.
And so deletion is about being able to say no to, um, ham-hocked practices because, you know, that's the way we've always done thing here, done things here before. And so the encouragement that I've been giving certainly to the champions, you know, the champions are, are, are the front line of this, or they, they get the brunt of Eric's ideas around this, is like your job...
Six months ago, I said, "Your job is to no longer like come up with an idea, but actually come with an a- come with an artifact," right? Come with something because, you know, the ideas are now cheap. You know, execution is, is everything, and distribution, I suppose, is king, and we can talk about later concept. So come with an artifact, but when you come with that artifact- Tell us that something, the artifact that no longer exists, right?
So
[00:49:37] Jeremy Utley: like you- When you bring, when you bring a new thing, you have to tell us what you deleted.
[00:49:40] Eric Porres: What did you delete? Exactly. What, what did you get rid of? Was there an old report? Was there an old... Like we, we, we as a, as a species, and I, and I know this from, from being able to see it We work with an unnamed dashboarding company or, or data visualization company.
And as a company, we have thousands of these visualizations, thousands upon thousands of them. The actual number of ones that are used are more like, like 4%. 4% or 3% of the thousands actually get used repeatedly in one way. So why do we still have all of these dashboards? Because it's what we've been... Well, that's what my KPI has been.
That's what I've been trained to do, so I have to do more of that. And I think if we look at examples in history, most recent history, again, for all the challenges of, of Elon Musk, right? Like, well, why can't we land the booster rockets back on Earth? Why can't we? Well, it's always been done where we jettison them off into, uh, into an area of the Atlantic or the Pacific, that then Bezos has gone down with over a 30-day period and, like, you know, lifted up the Apollo 11, you know, rockets that are now in the Smithsonian.
Great. That's something that we did for decades until somebody said, "Well, no, that's stupid. We don't have to do that. We can recover what we, what we have." So deleting the process, deleting the jettison these rockets, is the way in which he said, "Now I can actually create something new. I can create this repeatable new process, which will change space exploration forever."
So this is a real world example- So
[00:51:14] Jeremy Utley: when, when you think about this, I, I love it. When you think about this- Mm-hmm ... as a measurement, how do you measure deletions? We talked with Leidy about how one of the challenges with subtraction is there's no evidence of the subtraction, right? When you add, you go, "Look at what I added," right?
When you take away, people go, "There was nothing there before," right? And so- Uh-huh ... and, and so when the work of subtracting is actually a sophisticated, elegant, nuanced work of innovation, how do you then log in on the dashboard? How do you give somebody credit for a deletion?
[00:51:42] Eric Porres: Still a work in progress. I wish I, I wish I had a very, a clear answer for you.
I would say this, you know, to your point, it's like if we meet together in, in s- in six months' time, this is something that I'm very focused on, uh, right now, which is this very problem. Uh, because there are... And I, and I actually, you know, Leidy, when I wrote about it, he, he reached out to me and he's like, "Hey, I'd love to talk to you more about this problem," because it, because it is, it is a problem that is not sufficiently, not, not sufficiently addressed by current instrumentation.
[00:52:10] Henrik Werdelin: Do you think one of the issues with us now dumping everything into databases is that when I went on sabbatical, I had these small notebooks, and at the end of each notebook, I basically put the notebook down, and I had to, from memory, percolate anything that I remember for then into the next page. And then by the time at the end of the sabbatical, I had this notebook with basically what was the best thoughts by using the method of basically what could I recall, right?
Now, you have now this database of where you dump like all your code and co-work and all this stuff it kind of like puts in there. And in many ways, we're now asking AI and chunking and, and vector databases to do that percolating for us. So I wonder if you've... what, what you're thinking in making sure that what we can recall has a filter, and the filter is something that is deeply human to us, so that when we then have a recall, the thing that we remember is not just anything that we ever thought, you know, said or done, but it's the thing that we felt was important when we did it.
Like almost how do you put a weight on what you put into
[00:53:21] Eric Porres: it? Well, yeah, a w- a weight on retrieval. So there, so there's a, the, this notion of re-ranking, and re-ranking is, can be time ordinal boxed. Re-ranking can be done by what I described before in terms of ingesting, like here's what I'm actually most interested in right now.
It starts as a whiteboard, then it becomes a retrieval re- an embedded retrieval object, and then the re-ranking that comes is the, the, the similarity to, to that re-ranking. At a separate time, we can also talk about, and I'll probably write about this over the summer, is, uh, auto-research. So, you know, Karpathy published auto-research as a thing to do with, um, with code or be able to do loops.
And so I've, I've now taken that and, and, and, um, Azeem from Exponential View also has done this, which is created an auto-research hypothesis, hy- hypothesis test, iterative loop, steel man argument. Does this hold water? Does this hold weight as well? So I auto-research my own hypotheses as well. So it's a combination of retrieval, temporal indexing, and auto-research to come up with final, like the, the, what, what is the actual argument?
Because I can be, right, like I can, I can be wrong, too. I'm happy to be wrong, uh, and I'm happy to be proven through the scientific method, um, here's why you're wrong. Uh, as opposed to just it being a, you know, a, a set of opinions that I have based on my own objective, uh, my own objective reality. So, so that's, so, so Henrik, that's the answer to the, the, the question.
And I would say n- it has been net more positive than it is negative, which is why I keep using this method for myself in terms of my own, a smarter way to have and maintain a memory palace based on the work that I do.
[00:55:02] Jeremy Utley: I think that's a perfect place to end. Um, this, we, we could, as is clear, we could talk to you for hours, and we can just do like a weekly s- Why don't we have a weekly office hours where we just talk about this stuff, right?
This, this is like, this could be the weekly BTP, like, uh, the subscriber-only package.
[00:55:19] Henrik Werdelin: Okay. Jeremy, he's such cool and so nice to get him back on. It's very inspiring always. We also, as, as people might not know, but we're in a WhatsApp group together, and I am always very excited when, uh, Eric kinda like drops another GitHub MCP idea.
[00:55:37] Jeremy Utley: Absolutely. You love the, you love the GitHub. You love the GitHub MCPs.
[00:55:41] Henrik Werdelin: Uh, I love the GitHub. I mean, like, I think it's because I'm a non-engineer, and then suddenly, like, all this code that's been available on GitHub through all these years is available to me. So it's like a little bit like somebody who finds like a library for the first time, but just- Yeah
for things I can use, right? And so- Yeah, it's brilliant ... yeah, I'm very giddy, giddy about GitHub.
[00:55:58] Jeremy Utley: Giddy about GitHub. Giddy up Do
[00:55:59] Henrik Werdelin: you, do you want to go? Do you want to go, or should I go? Should I go?
[00:56:02] Jeremy Utley: I mean, I would say he's so knowledgeable. He's got so much experience not only building from first principles himself, but also enabling others to build that there's, there's something for everybody to love in this episode.
Um, I thought, you know, if I, if I just think about some themes that stood out to me, AI in action moments feel like that's kind of a... There are many layers in the organization where that matters. In the all hands, Hanaka is highlighting AI in action across different functions. In our senior leadership team meeting, they're highlighting AI in action moments.
Then he mentioned even at different offices at Cork, Ireland, right? There's AI in action moments. To me, it's a very kind of portable tactic to say anytime we're gathering folks regularly, let's spotlight how people are leveling up, augmenting, amplifying themselves with AI. That's... And it's just anytime there's a gathering, how are we spotlighting AI augmentation?
To me, it felt like a very... It seems that's authentic to what he's done there, and I love that as a simple tactic. I'm always looking for those kind of simple stealable tactics.
[00:57:08] Henrik Werdelin: I also think that he seems to be one of the few people that I've seen that manage to be very hands-on, but then kind of pass that hands-onness onto the organization.
Mm-hmm. Mm-hmm. You know, he's- he seems very accessible. Obviously he seems to have office hours weekly where people could just call in and do it. But also I like this idea of using gems as an object that you can then have people rally around. Yeah. Yeah, so cool. I agree. And so I think a lot of AI development is happening now in the different, uh, parts of the organization.
Having something that is kind of, like more generic, uh, and available to everybody seems interesting. And what it remind me of, and I know somebody- somebody mentioned in one of the podcasts we have that, that there could be this moment in time where the, the HR officer, which now, now would be not just human, but also agent officer-
[00:57:59] Jeremy Utley: Yeah
[00:57:59] Henrik Werdelin: could be a chief resource officer. Yeah. And the chief resource officer was somebody who would help the organization become more efficient and better at growing the organization, right? So the, the
[00:58:10] Jeremy Utley: both are critical- I think, I think Moderna actually did that. They merged HR and IT. I don't know if they've called it a chief resource officer.
I do like that. And I- But I think there's something there ...
[00:58:19] Henrik Werdelin: and when, so when, when Eric is talking here, I was like, ah, maybe this is actually... I know he's chief AI officer, but in many ways he is becoming the chief resource officer, like the one who are creating resources for other people at Logitech to then use to become more resourceful themself, right?
I think it's like such an interesting kind of way of thinking about it.
[00:58:41] Jeremy Utley: Yeah. And I, I mean, it fits your framework, right, of resourcefulness, and I actually love that. I, I think there's very little difference between helping someone get augmented with AI and helping someone become more entrepreneurial.
There's a high degree of overlap between those things in terms of agency, in terms of problem orientation, in terms of bias towards action, and I think that that gets captured actually in chief resource officer in a really nice way.
[00:59:04] Henrik Werdelin: And what was nice about it was when you hear about the different gems, obviously in many organizations you feel that there's still a bit of AI theater going on where somebody have done a few things and then people toot the horn of that and basically says, "Oh, look, we're doing AI stuff," and it's...
You get the sense like, yeah, it's like a little thing over in the corner and like that. He seems to be just by- Audacity, having kind of like this abundance of stuff that he's making available to the organization and helping the organization develop itself. And what's nice is that when you can go all the way from kind of soon- super small kind of like features all the way up to the board, uh, level, and obviously Logic being a, a, a listed company, then I feel you're really shown that you can kind of move at all levels of the organizational stack.
And that I think is actually, is fairly uncommon, so
[00:59:54] Jeremy Utley: fascinating to see. Well, it's a very, it's a unique personality for, for someone to be able... And I've heard, I've heard this said before, so this isn't an original idea, but you're just pro- you're prompting it for me. You've gone beyond the prompt, Henrik.
Um, but there's something about the person who can have a board level conversation, a CEO level conversation, and a frontline worker conversation, is a unique persona. Not everyone is capable of doing that, and if you think about Eric as kind of a prototypical chief AI officer, you need someone. I mean, he, I know, I, I, I don't think I'm speaking out of school to say this, he's in regular communication with the CEO, and he's got a weekly Zoom where anyone in the company can log on and talk to him, you know?
And there's something about being, uh, fluent in that kind of spectrum of call it hierarchy or seniority that's really, uh, necessary for a chief AI officer or chief resource officer.
[01:00:50] Henrik Werdelin: Then the last thing was this kind of idea, of course, of adding more specific MCPs to your world where you create a database that's accessible to your foundational model of choice.
Um, which make me... I'm gonna, after this conversation, make an MCP version of Beyond the Prompt so anybody will be able to get MCP access to all our conversations, and I'll see how that go. Why not? Yeah. But for me, for me, for sure, it'll be, uh, usable. But I do think that we are probably getting to the point where a lot of us have made different bots, a lot of us have made different skills.
What we have not necessarily done is to figure out how do we architecture the different MCPs, kind of the, the, the servers that we need to create that has what data and how do we get it in there and all those different things. And so that might be something that I'll do over the summer, get
[01:01:41] Jeremy Utley: more into.
To me, one, one thing actually that it's, it's a non-trivial thing. Sometimes it's im- the trigger is sometimes implicit. For example, like a deep memory. The trigger for that is Eric's going, "I gotta make a presentation. What have I thought about this?" Right? Or, "I'm writing an article. What have I said about this?"
So sometimes the trigger is kind of obvious and it's on the user. But then the other thing, Henrik, that I notice is sometimes the trigger has to be... You gotta, you've gotta build the MCPs so that the loop closes itself.
[01:02:08] Henrik Werdelin: Mm.
[01:02:08] Jeremy Utley: So for example, his Whoop MCP is connected to his daily briefing MCPs, right? Mm. And so it's not incumbent upon him as the user to trigger that connection every day.
He has actually instructed his briefing agents to consult his Whoop MCP, his Whoop data via MCP, before th- his briefing agents determine how much to give him.
[01:02:36] Henrik Werdelin: Yeah.
[01:02:36] Jeremy Utley: Right? Which I think is pretty interesting.
[01:02:38] Henrik Werdelin: And I think a lot of us are now trying to figure out what do we do with memory across our different agents.
I, I'm a little bit... I posed the question, I don't think I, I posted in a way where my, my point was kinda like properly made, but I do worry that we have to be careful about how we position our memory stack. And what I mean by that is, um, Eric the other day sent around to a few of us a script that he created that would allow you to basically create a skill file based on, on how you like to write so that you could write more authentically like you.
Now, the question then becomes quickly- Does this have to be a skill file about how you actually write or should this be about how would you like to write, right? Because that's the difference, right? Or is this is when you write your finest stuff, or is this is when you write to people, and when you write it to people, it gets more human.
And so I, I think there's all these nuances that we'll have to kind of grapple with when it comes to how do we store the digital versions of the stuff that we want to retrieve about ourselves and be a little bit purposeful about that, and I'm not quite clear yet that I have a perfect idea of how to do that.
[01:03:55] Jeremy Utley: Yeah. I'm trying to see if there's anything else. I love that, just to recap, you know, stuff that maybe folks heard but will appreciate being reminded of. The most used gem in the company is the Gem Builder Advisor that not only lets people know what are the tools available to them, but also what's the prior art, what have others tried to facilitate human connections.
Mm. I thought that was very cool.
[01:04:18] Henrik Werdelin: I like that, too.
[01:04:19] Jeremy Utley: And then, of course, the second most used gem is the presentation storytelling gem, and I love what he said, what's the purpose there. To prevent folks from losing their humanity when they're telling stories in the company. I thought that was beautiful. Um, anyway, again, something for everybody here.
I'm excited to... I think when he comes back, he owes us more thoughts around how to actually measure deletions. That's one thing, and then the second thing was, it was right at the end. What was the second thing he owes us? He said we need to talk about in six months.
[01:04:50] Henrik Werdelin: I have a delete of that.
[01:04:51] Jeremy Utley: How about that is the code word.
The code word is the answer to the second thing. If somebody knows it- Oh ... we'll send you a book. How's that sound? We're
[01:04:58] Henrik Werdelin: so goldfish, the two goldfish here. I can't remember what we talked about, like, 15 minutes ago.
[01:05:05] Jeremy Utley: Hi, I'm Dory.
[01:05:08] Henrik Werdelin: Awesome. And with that, we'll say goodbye. Bye bye. Bye
[01:05:12] Jeremy Utley: bye.