How Siri’s Co-Creator Predicts the Next AI Wave with Adam & Noah Cheyer | [Sidecar Sync Episode 131]

Summary:

What happens when you put a Siri co-creator and longtime AI pioneer together with a next-generation events strategist? Adam Cheyer—co-creator of Siri, founder of Viv Labs, and a builder behind several influential AI startups—and Noah Cheyer, founder of Silicon Valley Speakers and a close observer of how event planners and audiences are responding to AI, join Mallory Mejias for a father-son conversation on where this technology has been and where it’s headed next. The episode spans the early vision behind AI assistants, why Siri was absolutely AI before the world had language for it, and how timing, trends, and “triggers” shape real innovation. Along the way, Noah brings the events-world perspective, sharing what buyers actually want from AI speakers, why hands-on workshops are replacing high-level hype, and where event professionals can use AI right now to do more with less.

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Amith Nagarajan is the Chairman of Blue Cypress 🔗 https://BlueCypress.io, a family of purpose-driven companies and proud practitioners of Conscious Capitalism. The Blue Cypress companies focus on helping associations, non-profits, and other purpose-driven organizations achieve long-term success. Amith is also an active early-stage investor in B2B SaaS companies. He’s had the good fortune of nearly three decades of success as an entrepreneur and enjoys helping others in their journey.

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Mallory Mejias is passionate about creating opportunities for association professionals to learn, grow, and better serve their members using artificial intelligence. She enjoys blending creativity and innovation to produce fresh, meaningful content for the association space.

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Read the Transcript

🤖 Please note this transcript was generated using (you guessed it) AI, so please excuse any errors 🤖

[00:00:00:14 - 00:00:09:17]
Mallory
 Welcome to the Sidecar Sync Podcast, your home for all things innovation, artificial intelligence and associations.

[00:00:09:17 - 00:00:53:13]
Mallory
Hey Siri, what's the best AI podcast for associations? I might be a little biased, but today's episode gets us pretty close. Hello everyone, welcome to the Sidecar Sync  podcast. My name is Mallory Mejias, and I am one of your hosts along with Amith Nagarajan. And today we are joined by Adam Cheyer, co-creator of Siri, and one of the true pioneers behind the AI assistance we now take for granted, alongside Noah Cheyer, founder of Silicon Valley Speakers, who sits at the intersection of AI and the events world, working directly with event professionals, speakers, and organizations navigating this moment in real time.

[00:00:54:15 - 00:01:51:19]
Mallory
 Adam's career is a masterclass in timing. He's been a co-founder or founding member of five successful startups, four of which were acquired for their breakthrough AI technology, including Siri, which was acquired by Apple, where he worked closely with Steve Jobs, and Viv Labs, which was acquired by Samsung and went on to power its voice assistant Bixby. And while that kind of intuition is really hard to capture in a bottle, in this episode, we give it our best shot. And with Noah, we get a completely different lens, what he's hearing on the ground from event planners, how audiences are actually responding to AI content, and what separates the speakers and organizations that cut through from the ones that don't. If you're trying to make sense of not just where AI is going, but how to communicate it, program around it, and make it resonate with your audience, this is a really good episode. Everybody, please enjoy this conversation with Adam and Noah Chire.

[00:01:51:19 - 00:02:28:02]
Mallory
 and Noah Cheyer, thank you so much for joining us on the Sidecar Sync podcast. We're thrilled to have another father-son duo. Believe it or not, we've had a father-son duo on the pod before. I wanted to do something a little bit different with this episode. So normally, I always ask my interview guests on the pod to share a little bit about their background with our audience who may not be familiar with them. But since I have a father and son who know each other quite well, I thought it could be kind of fun if, Adam, you tell us about Noah's background and then Noah, you tell us about Adam's background. So let's say, Adam, can you kick us off with this?

[00:02:28:02 - 00:02:37:02]
Adam
 Sure. So my son is Noah Chire. He graduated from Chapman University a few years ago with a marketing degree and a minor in entrepreneurship.

[00:02:38:18 - 00:02:40:20]
Adam
 He went right into e-commerce,

[00:02:41:20 - 00:02:46:12]
Adam
 marketing for an e-commerce company, and then got interested in the events industry.

[00:02:47:13 - 00:03:01:05]
Adam
 For the last few years, he's been running speaker bureaus, which hire experts for the events industry. And what makes me proud is he's doing this now on his own through Silicon Valley Speakers Bureau.

[00:03:02:12 - 00:03:33:13]
Adam
 And not only does he provide a service to the industry, he's a known speaker himself. He goes out and talks about how AI can be used to accelerate your job. Do more with AI. And I think he's providing a big service. He runs the largest job board for the event industry professionals. He gives a lot of free knowledge and information and subscribed to his newsletter and LinkedIn. So that's Noah.

[00:03:33:13 - 00:05:06:04]
Noah
 Yeah, you're really doing a great job pitching me. I got to return in a favor. So yeah, Adam, you could say he hopped on AI during the first wave. Everyone thinks about AI in 2023. Some people think about AI with the launch of Siri, which Steve Jobs called one of the first AI companies. But he actually jumped on it back in the 80s when AI was hot the last time. And then had been working in AI for 40 years, got to see kind of the dot com bubble was involved in companies there. But also over the past 20 years has been an entrepreneur. One of, I think the few entrepreneurs we hear people talk about that started in their 40s, which I think is a super unique story. But since then has started five companies and has been five for five. So he was a founding member and founding developer of change.org, which is the world's largest pitch platform. He also was a founding member, co founder of Siri, which a lot of people know and best known for, which has impacted people on billions of devices, of course. But then after that also founded Viv Labs, which ended up becoming Bixby, which is Samsung's voice assistant. So basically Samsung's version of Siri. And then most recently started gameplanner.ai that ended up selling to Airbnb was one of their first public acquisitions. And then now is still exploring kind of his opportunities in AI space. So you could say one of the speakers I work with was Peter Norvig who called himself an AI hipster. But I would say Adam is also an AI hipster who's been doing it before it was cool.

[00:05:06:04 - 00:05:11:06]
Mallory
 I love that the AI hipster Adam, do you feel like Noah did a good job describing your background?

[00:05:11:06 - 00:05:18:00]
Adam
 And me and Peter both are OGs who like to wear colorful shirts. We have that income.

[00:05:18:00 - 00:05:43:15]
Mallory
 Well, I love it. That was a really beautiful way to kick off the pod. So thank you both for engaging in some of my antics. So Adam, it sounds like you've been thinking about artificial intelligence since the 80s, long time ago, OG hipster, you might call it. And then Noah, you've been building your own business with AI more as a given, I imagine. So do you think that affects how each of you view it as a technology? Or do you think you have pretty similar takes on AI?

[00:05:43:15 - 00:05:59:24]
Adam
 What I really like and appreciate about Noah is, you know, it must be tough growing up in the shadow of someone like this and being kind of thrust into AI so early, thrusts into computers and all of this. But he's done a great job finding his own lane.

[00:06:01:02 - 00:06:03:07]
Adam
 So I've always been on the technical side.

[00:06:04:07 - 00:06:09:03]
Adam
 Noah went into entrepreneurship and AI, but from the marketing and communication side,

[00:06:10:04 - 00:06:11:24]
Adam
 very early. So literally,

[00:06:12:24 - 00:06:18:06]
Adam
 the chat GPT moment happened November 30th, 2022.

[00:06:19:10 - 00:07:06:21]
Adam
 And Noah immediately started an in-depth study, independent study on how AI can be used in marketing. Because he said this is going to transform everything. So I think he came from, you know, an AI. He saw AI around the house. I think he often says he's Siri's brother, which is accurate, but he has many other children because I built systems named Iris and Kaylo and Vivz and on and on and on, right? He's been around it, but he's always found his angle and I know nothing about marketing. And so we can talk about AI. We can talk about applications, but from slightly different viewpoints, me from the more technical one and maybe more from a business and communications.

[00:07:08:04 - 00:07:18:02]
Adam
 Field. So yeah, I think it's been really fun to partner with him and to watch him grow and build his own identity in this world.

[00:07:18:02 - 00:07:33:19]
Noah
 Yeah, that's a great summarization of it. I would say on the tactical side of how we approach AI, I would say Adam's always been very focused on the user. He's always cared about what is the user experience? How is this going to affect consumers?

[00:07:34:20 - 00:08:11:01]
Noah
 And how is it going to change how the everyday person uses AI? I would say I've always been very focused on the business side, on the how can you as a person in business use AI in your daily work, which I would say is very, very different. Once again, that's more generally contained to the workday that you have. Adam really thinks about how do you wake up in the morning? How do you go through your day? How do you do the basic things that we do as people and how can AI impact that? So I'd say that's another kind of differentiation between kind of what I talk about and what Adam talks about in his talks.

[00:08:11:01 - 00:08:19:08]
Mallory
 Yep, I feel like that's a great way to summarize it. Series Brother, I don't know if you like that title, no, but that's definitely... Who came up with that first? That's a good one.

[00:08:19:08 - 00:08:35:14]
Noah
 That, probably a friend of Middlesfull. It was not something I called myself. It was more something that I got the label put on me and I ended up just doing the running joke. And I was like, "You know what? I'm going to go with it." So I'm going to fall in high school. My friends used to call me Series Brother, but I would just kind of roll with it.

[00:08:35:14 - 00:09:37:18]
Mallory
 And now you've owned it. I like that. I was going to say I really appreciated the insight you just shared, Noah, on kind of focusing on individual work, more like productivity, and then your dad focusing more on the end user. And I think associations have to balance that as well. Often when we talk about artificial intelligence, we're thinking, "How much time can we save for ourselves in our daily workflow, which is really impactful?" But then also thinking about the end user or the member in the case of associations, and what can we create and how can we better offer services to reduce the friction that these members face anytime they need something from the association. So I feel like that's something we'll probably keep coming back to. Of course, I want to get into the story of Siri, which all of us probably know as a voice on an iPhone, but I'm assuming the real story is a little bit more complex than that. So Adam, can you give us a little bit of a background? In my research, I saw that I think the first iteration of Siri started in 1993. So if you can give us a high level, how did we go from that to the voice that we know on our iPhones?

[00:09:37:18 - 00:10:04:08]
Adam
 Right. So you can see the Siri story from many lenses. So some people just see it as an overnight success. There was a small team named Siri. We launched a free app in the App Store. Two weeks later, Steve Jobs calls our office unannounced. He's like, "Hey, it's Steve. Come over to my house tomorrow. What you doing?" And we went over, we talked. He threw out a big number, said he wanted to buy our company.

[00:10:05:08 - 00:10:14:14]
Adam
 And we said, "No, not interested." And we left, but he obviously is persistent. He called us 30 days in a row, and eventually we sold to Apple.

[00:10:15:17 - 00:10:24:10]
Adam
 And I went and ran the Siri team at Apple. So in some ways, magic. Launch an app. Two weeks later, easy. You're working at Apple.

[00:10:25:14 - 00:10:57:18]
Adam
 But of course, it took years to build that app. We had started it a few years earlier as a startup. We saw the iPhone come out, and I had been working in the space for a long time. But I said, "Now is the right time to bring it to market." And if I have one superpower, the thing that's led me to most of my success is I'm good at timing when to take a research idea or a concept and actually commercialize it. I built the first voice assistant.

[00:10:59:13 - 00:12:00:18]
Adam
 Many came after, Cortana, Alexa, Google Assistant, but we were first. I built the first social network for social change, change.org, 2006. This is the 20th year anniversary. Many came after. The first large-scale machine learning platform company, Sentient. We had more than 2 million CPUs and GPUs right as deep learning was taking off. And I built the first AI that could code Viv Labs. Today, AI for coding is a big thing. So I like to see an idea and get there first, because like a surfboard, you can be waiting, waiting for that wave. If the wave breaks too early, you don't go anywhere. If it breaks too late, you don't go anywhere. But if you catch the timing just right, you can go on a really long and satisfying ride. You're right. The first version of Siri was actually in 1993. It was not the time to commercialize it yet. Just to set context, 93 was pre-web.

[00:12:01:22 - 00:13:15:19]
Adam
 At the time, you had your PC, you would load it up with software, with floppy disks and CD-ROMs. Once you had your applications on your personal computer, that's what you could use to compute with. But I said, someday, there will be content and services spread around the world on other people's machines and we'll need a way to discover them and to interact with them. I always thought everyone would have an assistant and you would be able to say, "I want to know this or do that." The assistant would delegate your tasks, your sub-request to all the right places in the world, gather the results, present them to you, learn from an interaction, and help you get the job done. So that was my concept of really what became the World Wide Web. About a year or two years later, web browsers let you discover and interact with services. But I always thought voice and language and an assistant would be the way. Turns out, I was right. That wasn't the time to bring it to commercial market. We needed these companies to be able to expose web services and APIs. That could be consumed by an assistant.

[00:13:17:09 - 00:13:21:12]
Adam
 Now, we have AI smart enough to understand you.

[00:13:22:13 - 00:13:31:01]
Adam
 There's still a lot of work to do to create the original vision that I have, but I think it's now within potential grasp.

[00:13:32:10 - 00:14:10:14]
Mallory
 Absolutely. Yeah, hearing you talk about the idea of an assistant sounds very much like a genteck AI, which as you both know is just exploding right now. I feel like Claude Cowork could kind of be a version of maybe what you envisioned. But I want to talk about Siri as we know it. So we've talked a little bit about how it started back in 1993. We know it now as a voice assistant and maybe not internally at Apple and maybe not from your perspective, but from mine, and I would say maybe the general public, when Siri came out, it didn't seem like people were running to say, "This is AI. This is artificial intelligence." Right? That's not a term that I often heard associated with Siri, at least by the masses.

[00:14:11:20 - 00:14:30:20]
Mallory
 Obviously, we had this generative AI boom a few years ago, and now AI is like this buzzword. All we're having is AI speakers and AI apps and so on and so forth. But can you talk a little bit about what within Siri is artificial intelligence and maybe why the world wasn't ready to call that AI, even though it was?

[00:14:30:20 - 00:14:40:10]
Adam
 I would say that the world did call it AI. Now, it's been overshadowed because now we have an even bigger boom.

[00:14:41:11 - 00:14:57:17]
Adam
 But for 20 years, the phrase AI had not been used publicly. And as Noah referenced, when Steve Jobs went on the All Things Digital podcast and Walt Mossberg said, "Why did you buy this search company?" Because that's what everyone knew.

[00:14:58:24 - 00:15:08:12]
Adam
 This search company, he responded, "It's not a search company. It's an AI company." And at the time, no one knew what he meant. They didn't have any reference.

[00:15:09:14 - 00:15:53:18]
Adam
 And yet, when Siri came out on the iPhone 4S, it exploded. So Apple's stock price nearly doubled in six months. Just selling the iPhone 4S, which was literally the iPhone 4 plus Siri, they surpassed Exxon to become the number one highest market cap company, the most valuable company, not only at the time, but in the history of the world. So this was the first AI feature. But again, people didn't know what AI was. It hadn't been used for 20 years. It took a while for the phrase to rekindle. It was like a little burning flame.

[00:15:54:21 - 00:16:39:18]
Adam
 But it did. The movie Her started coming out and introducing AI. IBM came out with a program called Watson, which could play Jeopardy. Self-driving cars happened. All of a sudden, there was this rise of AI, and Siri was the spark. And soon, deep learning and neural nets was very popular in the 2010s. So it kind of grew, leading up to the crescendo of the chat GPT moment. And now people knew what AI was. Google had eight robot companies. There was enough use of the term that when this came on, when you said this is AI,

[00:16:40:21 - 00:17:09:07]
Adam
 everyone kind of could put it into a framework that didn't exist when Siri did. You asked why is Siri AI? Well, what is artificial intelligence? It's just machines trying to emulate the amazing capabilities that humans have. We had in 1996, Deep Blue, IBM's Deep Blue program beat the world chess champion. Was that AI?

[00:17:10:09 - 00:17:22:11]
Adam
 Well, yes, it was. Chess is one of our most intellectual accomplishments, and we now surpass the best player in the world. But then when people get over the hype, it kind of goes back down.

[00:17:23:15 - 00:17:26:11]
Adam
 It's not real AI, it's just search.

[00:17:27:19 - 00:17:49:21]
Adam
 When Siri came along, at the time, you could not expect to speak words and have a computer understand you. There were dictation systems, so you could speak and have it transcribe words. But to actually understand human language is an incredibly difficult task. If I say, "book a four-star restaurant in Boston,"

[00:17:50:22 - 00:18:01:10]
Adam
 you know exactly what that means. But think of the ambiguity. Book can not only mean make a reservation, but it's also a physical book. And book is a city in the United States.

[00:18:02:17 - 00:19:05:22]
Adam
 Star is a city in the United States. There are 13 Boston's in the United States. So which city are we even talking about here? Star restaurant is the name of a restaurant. But I'm not talking about, when I say four-star restaurant, I'm not talking about a restaurant name. So there are so many ambiguities. When you load in millions of business names and song names, you realize every word in the English language has so many meanings, and you put them together, the combinatorics, the ambiguities are immense. So in order for Siri to understand human language, even at a primitive level, it was a huge intellectual challenge. It was artificial intelligence. But of course, after the bubble, the hype, then it goes down and everyone uses Siri. There are billions of queries a day, but oh, it's not. AI. AI is magic. And today we're in the middle of another, I'll call it the large language model hype cycle. Wow, it's amazing. It's AR.

[00:19:06:24 - 00:19:30:03]
Adam
 People ask, "What will AI be in 10 years? It's going so fast." I go, "Well, everyone will use it, but we'll all be bored with it." We'll say it's not. AI, it's not real intelligence. It's not human intelligence. It's just large language models. We accept that, just like we accept calculators, chess claim programs, Siri, et cetera. Once we get over the hype,

[00:19:31:07 - 00:19:44:02]
Adam
 the excitement dies down. The utility picks up, but we're always looking for what's next. What's the next crazy, good magic thing? AI is magic in a way.

[00:19:45:06 - 00:19:54:00]
Adam
 It's exciting at the first part, but once you're used to it, you don't get that magic stimulation. So now AI is whatever is not here yet.

[00:19:55:08 - 00:20:13:03]
Mallory
 That makes a ton of sense to me. It makes me think of this wave of reasoning models that we've seen in the past few years where we're saying, "Okay, AI can reason," and then a couple months pass by and people say, "Well, it's not really reasoning, right? It's just simulated reasoning," and then we're on to the next thing. So I think you described that really well, Adam.

[00:20:14:13 - 00:20:22:06]
Mallory
 Noah, I'm curious, as someone who grew up with conversations just like that, I'm assuming, at the dinner table,

[00:20:23:09 - 00:20:40:06]
Mallory
 how did you view the generative AI boom that we'll call it, late 2022, 2023? Were you just sitting back saying, "Told you guys. I've been talking about this since the fourth grade. What was that moment like for you? Were you shocked or were you more like, "I knew this moment would come?"

[00:20:40:06 - 00:20:44:00]
Noah
 Yeah, I'm sure Adam is going to enjoy hearing this part.

[00:20:45:00 - 00:21:19:24]
Noah
 But growing up, Adam, of course, I think like any dad is lecturing me about technology and one of his very few sticking points on when he would pick something and say, "Hey, this needs to happen." But one of those sticking points was taking a coding class. So he required me in high school to take an intro to coding class. And it was my least favorite class that I took in high school. I hated it. I'm like, "I'm not a coder. That's not my background. I don't want to touch this." And I ran the other direction. I went towards communication, marketing,

[00:21:21:07 - 00:21:37:00]
Noah
 more people-focused industries. And I always felt like AI was completely unapproachable. Coming from that perspective, having Adam be the person in AI who'd done it all, I'm like, "There's nothing for me to do in AI that hasn't already done. I'm going to go do something else. I'm not a coder. That's not my strength."

[00:21:38:07 - 00:22:14:06]
Noah
 And that kind of all I would say switched in 2022 when chatGPT came out and I got to try it. And I was like, "Oh, wait. I'm able to do and interact with AI as a non-technical person without that background." And it helps me get to my marketing business, other interests that I had, and other goals. And that was the full circle moment, I guess, for me. And even now, looking in 2026, being able to use tools like quad code, which allow you to now code and allow me to code, even though I can barely write a for loop in Python,

[00:22:15:09 - 00:22:25:03]
Noah
 it's this full circle moment where Adam's like, "Oh, you have to learn how to code." And I was like, "Ah, I don't like coding. Coding's not fun." And now I get to code without coding.

[00:22:25:03 - 00:22:55:18]
Adam
 And I'm like, "Man, this is the most fun thing ever." But I also did when chatGPT came out, I said, "In the past, it's all been about being a programmer and a coder. But you know how to commute. You studied communication. And this is the new skill that's going to flourish in the future." So what is marketing? Marketing is saying, "If I express these words, I'm going to get a reaction of a certain desired type from

[00:22:57:00 - 00:23:06:15]
Adam
 people, a lot of different people." And the words matter, right? Choosing the right words to get the right behavior matters. Well, what's prompt engineering?

[00:23:08:03 - 00:23:55:05]
Adam
 This is a phrase people were learning that if you express things differently, if you phrase things differently to an AI, you get different behavior. So I said, "What's going to really matter is understanding how communication impacts and influences your listener." And in this case, it's not just someone, a human on the other side, it's the AI. And that's what's going to really, really matter. And now, as Noah said, we're at a point where knowing how to express what you want at the right level of detail is everything, right? That's a communication skill. And from that, oh, it can write the for loops in Python.

[00:23:56:09 - 00:24:12:05]
Adam
 But expressivity and communication is an incredibly important skill in today's world. And Noah, I think, was perfectly positioned at that pivot moment to leap right in from day one and start honing its skills in this area.

[00:24:12:05 - 00:24:28:15]
Noah
 I think that's one of the things that it kind of makes it ironic that I ended up running in the opposite direction of AI and it ended up almost serving me just as well, if not better than having to write for loops, things like that. Because once again, it's a tough market to be a computer science person right now.

[00:24:28:15 - 00:24:35:12]
Adam
 And look at you now. You spend a lot of time building software. It's just you're using your communication skills.

[00:24:35:12 - 00:25:45:11]
Mallory
 I love that. Full circle moment, I was going to say I'm picking up on the irony here, right? Communications mixing with technology. Also, look at what we're doing at this very moment, right? Communicating, expressing thoughts, hopefully educating some people talking about tech. Adam, I do want to talk about something you said. In my research on your background, I felt like you must have a really good sense of intuition, fortune telling, but understanding, of course, it's not quite magic, maybe a little bit of magic in there, but your sense of timing is really solid. And I've heard you speak in previous podcasts and YouTube videos about something that you called trends and triggers. So kind of having predictions in your mind, things that you think could happen and then waiting until there's some trigger in society that makes you know this is the right time. And I'm curious, this is a tall task, if you can kind of break that down into a process for a listener who's like, "Well, I don't feel like I'm a visionary. I don't feel like I'm a futurist. I struggle to look ahead. I'm focused on what's right in front of me." How do you look ahead and identify a trigger and say this is the right moment to act?

[00:25:45:11 - 00:26:04:21]
Adam
 I think anyone can do it. I mean, I've done it and I've been pretty lucky or skilled at doing it, but this is a process anyone can do. So what I usually do is I look for, you know, I'm a technologist, so I look for a technology that is not yet mainstream,

[00:26:06:24 - 00:26:35:15]
Adam
 not widely adopted, but it exists in some form, right? So for example, mobile for decades, we had kind of mobile, you know, there were phones, the Blackberry, the, you know, Motorola Razor, but they never really took off in kind of the smartphone area, right? It wasn't mainstream in that form. Or today you'd have like cryptocurrency.

[00:26:36:19 - 00:27:30:08]
Adam
 Like you could ask yourself the question, is cryptocurrency going to replace money? Like there are people who use it, a lot of people, but it's not money yet. Will it? So there's a question or augmented reality, you know, you can buy an Apple Vision Pro and you can buy this and that, but is it going to be always a niche thing just for gamers or for hobbyists or is everyone going to wear headsets in the future or whatever industry you're in, whatever technology you're in, pick something that there's an open question. It's not quite mainstream yet and ask, will this happen? So as an example, in 2004, for me, it was the 10th anniversary of the web. And I said, I'm going to make 10 predictions for the next 10 years.

[00:27:31:16 - 00:27:58:10]
Adam
 And they were all, I'm not going to go through them all, but one of them was social network, social networking are going to take off. Now in 2004, it did not really exist. It was LinkedIn, but niche for business. Friendster was the largest social network. It had about 10 million people, but that's miniscule. No one used it. You know, there was Orkut in Brazil. It's kind of popular, but like nascent.

[00:27:59:14 - 00:28:50:18]
Adam
 And so I said, I studied it. I talked to people. I thought about it. I read research papers. You know, I just got interested in that topic. I made other predictions. I said, all data is going to move to the cloud. We didn't have a cloud back then. We didn't call it that. We used to have data on our personal computers or, you know, in our businesses, but it wasn't publicly, you know, it wasn't hosted in the cloud, but I thought it would, et cetera. So I made these 10 predictions. And then I said, yes, I think social networks will take off. I said, yes, I think data is going to move to the cloud. Yes, I think this. And with that belief, that's what I call my trends. I now go through the world believing that soon we're going to have social networks, even though it doesn't exist yet.

[00:28:51:21 - 00:28:55:02]
Adam
 And then as things happen in the world,

[00:28:56:14 - 00:29:01:18]
Adam
 I can interpret them through the lens of these beliefs, these predictions.

[00:29:03:00 - 00:29:11:03]
Adam
 So a year and a half later, 2006, end of 2006, MySpace became the number one trafficked website in the US.

[00:29:12:21 - 00:30:28:19]
Adam
 Others are like, yeah, all right, that's good. They didn't really notice. I mean, yeah, it was kind of growing, but I'm like, oh, this is a proof point. Here it comes. That's just MySpace is just for music, but social networks are now going to be acceptable. They will be out for, you know, everywhere. So it is time to leap in. I'm going to start a social network for social activism, change.org, along with Ben Ratray, Mark Dimas, and some other friends. And we caught the wave. A year later, Facebook started to move out of these little college campuses and get mainstream. And now everyone was starting to get into social networks. And it was still early and you could build momentum around this. Another example is I had predicted everything moves to the cloud. I said, when we have enough data located in one place, in one company, machine learning will finally have enough data to process. So I started first large scale machine learning company, Sentient. And, you know, a year later, deep neural nets, all of a sudden starts taking off, surprise, surprise. And we were right there to leverage it. When the iPhone came out, people don't remember.

[00:30:29:22 - 00:30:31:24]
Adam
 Half the world said, oh, that's going to fail.

[00:30:34:00 - 00:32:48:15]
Adam
 Apple, it's just, they're a music player company. They make an iPod. Only a telephony company can make something as complicated as a phone. They're not a telco. They're going to fail. I had predicted that when data moves to the cloud, there will be a revolution at the interface. Because usually those who manage the data are not those who can best serve up the interface to the data. I saw the iPhone. I'm like, oh my gosh, this is going to change the world. Two years from now, everyone else in the telco industry is toast. They will be desperate to compete with the iPhone. So what could be better? What could one up the iPhone? Well, the Siri idea I've been working on for ages, you know, why what's wrong with the iPhone? Well, the screen is pretty small. It's hard to type. And it took one minute when you would click on 3G on a web link. It would take one minute round trip. I go, if you're going to buy something that's probably 10 clicks, that's 10 minutes. No one's going to do that. What if you could just say, get me two tickets to the Warriors game tomorrow night. And without typing on a small screen, one round trip says, here are the tickets confirmed. Yes, I'm done. Right. That could one up the iPhone and that and every competitor would be desperate for that. So the irony is we leapt into action, started the company, built Siri for the competitors of Apple. But Steve Jobs saw it first and swept it out, swept it out from them. So that that's the process that I use multiple times. But anyone can do it. Look around you, take something you're interested in that's not mainstream yet and look and see if you think it will go mainstream. And if so, wait. And when you get that confirming moment, oh, now it's going to happen. You're right on the cusp of that first thing that others don't really interpret it, the implications of it. But because you've been waiting for it, you're ready. Now you have to leap into action and go do something about it because you have a clear view to two years in the future. And that's an amazing advantage for everyone.

[00:32:48:15 - 00:33:53:02]
Mallory
 I feel like that's one of the most practical frameworks I've ever heard for innovation and thinking about our association listeners. I'm trying to dilute it into something maybe even more practical. So maybe it's not 10 predictions and maybe it's not 10 years. I feel like in the age of AI that we're in, maybe it's a few years, but having maybe five predictions that you come up with with your leadership team. If you're an association of CPAs, maybe it's as Adam said, something that currently exists, some trend that's out there that you think might take hold, but it's not quite mainstream. The same could apply to lawyers or teachers or whatever that may be. And then keeping your tabs, maybe every quarterly leadership meeting you have with your board, checking in on those predictions and saying, all right, has anything come out in the past three months that we could consider a trigger for this? I feel like that's a really good framework of thinking of that. Noah, I'm curious for you, do you use a framework like this in your work and maybe kind of a follow-up question, are there any greater trends that you are tracking or predictions that you have in terms of the event speaking space?

[00:33:54:03 - 00:34:09:05]
Noah
 Yeah, I would say I'm very micro focused comparatively. Adam is thinking about how are things changing at the high level across everyone. I would say I've been very, very focused on, I would say, looking at that through an event lens.

[00:34:10:06 - 00:34:29:00]
Noah
 So looking at once again, the tools, I've gotten to talk to hundreds of event professionals over the past year or so. And through that, I've kind of built my own idea where things right now, what are the needs of people within the industry? And then where do I think things are going? Or where are the opportunities as these tools evolve?

[00:34:30:02 - 00:34:34:00]
Noah
 Because as we've seen over the past two years, ChachPT came out in 2022.

[00:34:35:04 - 00:35:53:18]
Noah
 What we had as a product then, comparatively to the product today is, I would say almost night and day. The amount of context that something like GPT-3 or GPT-3.5 could handle originally was roughly 10 to 11 pages double space worth of context. And that's information you're putting in and information you're getting out. So if you think about that, that's not very much. That's maybe a training manual or a few pages of something you're able to put in. And then you're maybe able to get a page out. Now for context on the token side, it's roughly the size of a 365 page book of what you're able to put in and get out. And there's all sorts of types of integrations. So now it syncs to Google Docs, at least some tools do. You're able to integrate it or run it on your desktop locally, like something like Cloud Co-Work, where it's able to access files. It's able to say change spreadsheets. These are all things it's able to write to an actual code base and connect to GitHub. And you can actually build a project. These are all things that were not possible. So I would say generally, I've been looking at what does an event professional do on a daily basis? What are their bottlenecks? Maybe it's creating event timelines. They have to plan out everything that needs to be done for the event. What are the current tools they're using?

[00:35:54:18 - 00:36:44:21]
Noah
 And where are the tools going? So for example, specifically with Google Sheets and how people plan with projects generally. A lot of event professionals I've talked to, there's a few who still use binders. In 2026, they're still planning with a disability binder and haven't moved to using something in Google Sheets. A lot of the most advanced people I've talked to are still on Airtable. I'm like, "Okay, Airtable is great." But if you look at what AI is able to do, it's able to look at every single one of your past events. It's able to examine every single past event spreadsheet from every past version of that event you planned. And then it's able to write that out in a news spreadsheet based on your critical paths based on your specific deadlines. And that wasn't something that was possible until six months to a year ago, when a tool like Clod or a tool like Chatchept integrated with Excel.

[00:36:45:22 - 00:37:18:15]
Noah
 So it's really for me been looking at, "Okay, what are the needs for this specific task or workflow? And then where do the tools need to progress to for us to actually be able to do that from kind of the zero to 10 scale?" So I've kind of built out a framework across probably 15 to 20 different tasks, I would say, in the events industry, kind of ranking them on a zero to 10 scale of how good is AI at this from zero is like, "We never want AI to do this. We want a person to loop on this forever." And 10 is like, "You should start doing this today and or it can own the entire process and end."

[00:37:18:15 - 00:37:34:04]
Mallory
 That's again, very practical. Can you give us an example of something that would be a zero in that framework? Stick to the humans and then something that you would say right now all event professionals listening to this pod and there are many should go out and use artificial intelligence for. Can you give us one of each?

[00:37:34:04 - 00:39:38:12]
Noah
 Yeah, I think a clear zero is going to be being on site for events. Realistically, if you're an events person, you have to be there and make sure no fires are happening and that you're the one you can actually put them out. AI is not able to do that. I think it's going to be a really, really long time until we have AI that's able to be on site and handle the level of complexity and nuance that happens at events, whether it's a vendor not showing up on time, whether it's something else. AI will be the yes and in that situation where it'll be like, "Hey, the vendor said they're going to be there on time. Nothing's wrong." And you're like, "Well, the doc staff is saying no one's there." And the AI is like, "Well, you're supposed to have someone there." And it's like, "Okay, that's not very helpful. Someone needs to be making sure this gets figured out." And then I would say at 10, at least right now, what's easy for event professionals to integrate is the data visualization piece. So specifically looking at events and surveys, you of course survey people after the event. You get a lot of quantitative data, but you also get a lot of qualitative data, people filling out surveys, people sharing their thoughts. And it's really hard and not very time efficient to look at that at scale. If you have 200 form fillouts, 1,000 form fillouts, that's something where I talked about context, how you still only be able to hold or understand say 11 pages double spaced. Now that it's able to take in 360 pages or roughly around that amount, if you think about the amount of surveys that you can put into that, and then get really tailored insights out of it that'll impact how good your next event is, maybe it changes the sessions, maybe it changes the speakers you bring back, maybe it changes the topic of the theme. And there are all sorts of different ways to visualize it. You can visualize it in charts, you can put it in through text, you can even have it create an image for you if you want an image to kind of visualize this. So there's so many different ways to kind of understand the data that previously would have taken either experience in Excel and or just reading through all of it manually and then asking yourself, what do you think? So it's like a clear unlock value add that some people should definitely be doing today if they're not already.

[00:39:38:12 - 00:39:42:03]
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[00:40:35:18 - 00:41:01:11]
Mallory
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[00:41:01:11 - 00:41:31:23]
Mallory
 an excellent point. I'm curious Noah from your perspective with speak about AI, what topics or what sessions are performing most well are most requested when it comes to artificial intelligence? Are we looking at kind of the general intro to AI stuff or people kind of focusing on different areas? I know agentic AI is very popular now and something we talk a lot about at Sidecar for associations. Are you noticing any other maybe micro trends within the space?

[00:41:31:23 - 00:41:48:09]
Noah
 Yeah, I would say one of my biggest frustrations over the past two and a half or three years has been that in a lot of ways it feels like the discussion hasn't progressed as much as we would like. We look at a tool like Siri and the beautiful thing about Siri is that it was automatically on everyone's iPhone.

[00:41:49:11 - 00:42:04:06]
Noah
 And there was very clear marketing and use cases around what could you use Siri for? Like, hey, set a timer. Hey, what's the weather? So like if you think about the adoption speed, like we all look at open AI and how they were the fat like chat GPT was one of the fastest products to a million users.

[00:42:05:07 - 00:43:03:04]
Noah
 But generally, comparatively to what use case needs, like use cases need to be used. And like what usage should actually look like, I think we're still very far behind. A lot of the conversations that we've been looking in the last six months are still very high level, still very, I would say entry level. Well, I'll say I'm like a more macro view, I would say, generally 2024 was kind of the year of executives and boards really thinking about how do we run our organization? Is this serious? Is this not serious? I would say 2025 really felt like the year of them trying to explain to their teams that like, oh, AI is not just as fat, it's actually going to be used and has some real organizational use cases. 2026 feels more like the year where people are actually trying the tools. So something I would say that's been more popular in the last few months that we really didn't book that much of in the first two years was hands on workshops. So having either leaders or having

[00:43:04:07 - 00:44:51:11]
Noah
 kind of specific teams bring in an AI speaker who has experience in that area, and or is more technical, who can actually speak to their problems, understand kind of their tool stack, and how AI plugs into it. A lot of the adoption issues around AI generally are because they're not actually solving a problem and or they don't understand the ecosystem that already exists. To say that your company hasn't been using software is just a lie. You have all these different pieces, you probably have data issues, you probably have a tool issues already, and you have to figure those things out in addition to being able to integrate AI, AI isn't going to solve that. So I've been booking, for example, one of the speakers that I work with, Zach Ratner, for these internet kind of either technical or non-technical events. I'm going in and speaking to a team of either like developers or an entire organization about okay, here's the ecosystem you're in. Maybe you're in Google and you're primarily using Google tools. Okay, you're using monday.com as your project manager. Okay, you're coding on this platform, you're using Google's anti-gravity. How can you get more out of these tools? How do you make sure that you're integrating AI in the right places? And then how do you make sure you're also adding the right safeguards to make sure that they're still human in the loop checking? As I mentioned before, AI is still not perfect. It often says it can do things that it can't. It doesn't necessarily hallucinate. I think hallucinations have gotten a lot better, but it's kind of a yes, man. And generally, you need someone to say, hey, no, you did that wrong and or be accountable for it. So being able to really identify, okay, for each part of what needs to get done, who is the person responsible for it? And how do we make sure that they're giving the sign off, they're checking it. But then also, if something goes wrong, you have someone say, hey, did you do the right job? Did you really check for that thing the way that you should have?

[00:44:51:11 - 00:46:33:15]
Adam
 I would just add, I loved how Noah kind of laid out a progression and it really did feel like, what is AI? Do we need to be paying attention to it? That was kind of early. And oh, okay, AI is here. How do we add within our organization governance? And there was a lot of, how can we use AI? Now we're into that phase of, okay, we've set up our AI tools in our AI system and it's done in the right way. So privacy is protected and we're not going to leak out our things. So that's good. How do we train our employees to best use AI? So that to me feels like where we are now and it echoes the need for like, oh, give me some more hands on workshops. So how can we get we've set up the tools, made them available, but how can we best use this within our organization? And then as we, as organizations start to use it, I think there's going to be a transformation of work. And we've already seen, I've started to see some companies starting to talk about that, is like, what is the role of the human and the AI? What is the partnership? What do they do? What kind of people do you hire now and what are the skills for that? And how does that change? Because the roles are getting more blended. You're now getting used to these siloed areas where the programmers program, the product person defines the product, the UX people design the product. But now that product manager can like ask AI to build a mock-up prototype and can even have it do some wireframe designs.

[00:46:34:23 - 00:47:01:17]
Adam
 And it's like starting to bleed the roles, which used to be very crisp and clear are now starting to bleed over. So I predict that next year's, there will be a lot more talks about, okay, we're all using AI and we're pretty good at it. But what does this mean? What's the right size and shape of our organization? How do roles and responsibilities get set up,

[00:47:02:23 - 00:47:25:01]
Adam
 et cetera? What are the humans best at? What is the AI best at? What type of humans do we need? What types of AI do we need? So it's reshaping the nature of work. And I think we're not there yet, but I've seen a few forward-looking organizations already start to wrestle with that a bit. And I predict next year, that will be the big coming topic.

[00:47:25:01 - 00:47:29:20]
Mallory
 Well, look, if Adam Chire predicts it, I'd say I'm going to make my bet on that one.

[00:47:31:00 - 00:48:15:20]
Mallory
 To both of your points, I really resonate with that because at Sidecar, the first few years of us talking about artificial intelligence, we often had to lead those sessions internally or pull in experts from our more technical folks within our Blue Cypress family of companies. And now at our events this year, specifically and last year, we're actually getting association leaders to lead those sessions because they have hands-on experience with artificial intelligence, rollouts, implementations, and they're so well-suited to lead those sessions. So I think we're seeing that play out. And Adam, I agree with you. I'm reshaping the future of work. It's just such a huge conversation. It often feels impossible to talk about, but it's important to start now. I'm curious as we come to the end of this conversation.

[00:48:17:06 - 00:48:23:22]
Mallory
 Adam, what would you say if we were looking back at the 1993 moment for Siri for you?

[00:48:24:24 - 00:48:42:17]
Mallory
 What do you think is the moment, the 1993 moment right now in 2026? So what, looking ahead, maybe not quite as far, but looking ahead, you're thinking, "Hmm, this is something I'm going to pay attention to right now because I'm pretty confident. Let's call it five years, 10 years, 15 years. This is going to be transformative."

[00:48:44:13 - 00:49:04:19]
Adam
 So as Noah said, I like to think in terms of big, ball-sweeping paradigms. I have a framework that I call the 10-plus theory, and it describes how the interaction with computers changes every 10-plus years. So let's count.

[00:49:05:21 - 00:49:18:00]
Adam
 1984 is when the mouse and the graphical interface landed on a PC personal computer on everyone's desk. Great moment. We now started interacting with computers. 10-plus, one years later,

[00:49:19:03 - 00:49:19:12]
Adam
 95.

[00:49:20:21 - 00:49:34:22]
Adam
 A new paradigm emerged. It was the web browser, and you could now compute with hyperlinks and back buttons and use content and services spread around other people's computers, but you still sat at your desk.

[00:49:36:04 - 00:50:16:12]
Adam
 10-plus, two years later, 2007, "Hmm, what happened then?" "Oh, the iPhone came out, and all of a sudden, mobile was broken. It was the breaks for a moment for mobile, and you could now walk down the sidewalk computing, bumping into lampposts or whatever, instead of sitting at your desk. And in 2008 was the App Store, when every industry could now have an app and participate in that mobile experience. So I've been saying for more than a decade that in 10-plus, three years after 2008, so I predicted 2021, there would be a new

[00:50:17:15 - 00:51:29:07]
Adam
 breakthrough way for how people interact with computers, and it would be the conversational assistant. So if you take GPT-3, which was June 2020, and 3.5, or chat GPT, which was November 2022, split the difference. 2021 is right there on time. So I have a pretty confident view of where things are going in 10-plus, four years after 2021. So my prediction is 2035, it will all change again. There will be a new paradigm of interaction for how people work with computers. Until then, we're in this AI, this conversational AI age. And I actually think people say, "AI is going so fast, and we're getting new things." I actually chart it as going slower than the web. So I say we're about 1996 in the web. And there are three things that have to happen in this next few years to make AI as impactful as it should be, and a global paradigm. And the three things are the interface.

[00:51:30:18 - 00:51:42:03]
Adam
 Chat and text is not the right interface for most tasks. Imagine you're planning a trip. You want maps, you want photos, you want graphics, you want a side-by-side compare. It's a big decision.

[00:51:43:03 - 00:52:42:12]
Adam
 A text chat is not the right experience. It reminds me of when the web was just like static, ugly HTML pages. It evolved. Later on, we got JavaScript, interactivity, et cetera. We're waiting for that interface development on the AI side. The second thing is the platform. We're really good at what I call knowing questions, but I want doing as well. And when people say, "Doing well, don't we have that?" I go, "Well, with Siri, I can say, "Hey Siri, tell my wife I'm going to be late," and it sends her a text message. Does chat GPT do that? Oh, no. No, it doesn't send a message. Oh, right. With Siri, I say, "Hey, play my workout playlist," and the music starts playing. Does chat GPT? Oh, no. No, it doesn't do anything. Exactly. So we need a platform that evolves to knowing and doing. And I know there's a lot of buzz around agentic, but really,

[00:52:43:12 - 00:54:03:24]
Adam
 I feel agentic is people are trying to force fit doing capabilities into a knowing slash reasoning framework. And it's not designed in the right way. It's still leveraging what we've got, which makes sense. But doing is about transactions. It's about access control. It's about authentication. It's about boundaries. If something fails midway through a transactional boundary, where do you roll back to? AI doesn't have that. Its reasoning takes minutes or hours. It's not a doing framework. It's a hack, in my opinion, and that will evolve and balance. And the final piece, so we need the right interface, the right platform, and every paradigm needs all three things. The web needed it. Mobile needed it. Well, AI needs it. The third thing is the business model, the ecosystem business model. So with the web, everyone knew about SEO and advertising. Here's how you make money and here's how you get discovered. The app store came with the mobile and there was a whole new paradigm. You now have to learn Objective-C. That was your platform, but it could do transactions and it could do content. There was a new business model. You could have an app purchase. You could have subscriptions, free apps, paid apps, whatever.

[00:54:05:03 - 00:55:05:05]
Adam
 So what is that for AI? How does a company, say your open table or Expedia, how do you make sure your brand gets through, your interface is differentiated against your competitors, that there's the right level of transaction and security and access control. So you get a logged in user so you as a business can personalize. Those things are not developed yet in AI and the three need to be developed together. So in my view, the next nine years will continue to evolve and mature AI as a paradigm. We know that someday we won't use Google links as the starting point for how we research, decide, and do. Someday it'll be an AI assistant, but we're not there yet. We don't have the model, the platform, and the interface. So that's what happens for the next nine years. We mature. And then 2035, boom, it's all going to start again with my next prediction.

[00:55:06:17 - 00:55:29:16]
Adam
 Maybe I'll leave that as an open question for your audience, but I've got my prediction. I got to meet with one of the greatest prognosticators in history, Ray Kurzweil. I told him what I thought was going to happen in 2035. And he goes, hmm, yeah, that's right. And I'm like, oh, you won. So I'll leave that as an open time.

[00:55:29:16 - 00:55:42:07]
Mallory
 Wow. What a great way to wrap up the episode. I also really enjoyed that hot take on agentic AI and that we're kind of forcing it into a knowing models. I just think that's a really interesting take and you're right.

[00:55:43:13 - 00:55:57:15]
Mallory
 So I'm sure that will shift by the time 2035 rolls around. Noah, I know you said you're focused on the now, you're looking more at micro trends. We don't have to go all the way to 2035, but in terms of events and artificial intelligence and speakers,

[00:55:58:19 - 00:56:02:20]
Mallory
 what are you predicting for the next so many years?

[00:56:02:20 - 00:56:32:09]
Noah
 Yeah, I think one of the really interesting trends that I've been seeing kind of on the micro level is event professionals kind of becoming almost like a PM or someone who's able to actually create kind of these prototypes on the technical side. We're curing how people in large companies are able to design products and now start coding it a little bit. But I'm actually seeing this with event professionals where some people on the cutting edge are using tools like Cloud Code.

[00:56:33:11 - 00:56:42:10]
Noah
 And for example, they're working with, they're like an independent event producer and they're working with a healthcare conference or a healthcare association.

[00:56:43:16 - 00:58:08:09]
Noah
 And they're working on building say a way for their attendees to get personalized sessions and get a calendar of every single event they should go to based on their LinkedIn profile, based on the information they filled out initially, and they're building it themselves. They're then going to the healthcare association and saying, "Hey, you have your technical team, your software engineers. Here's this prototype I built. Can you get this for production?" And they're getting into production. And that's something that's already happening in a variety of different places. I see a lot more of that where events, which has typically been this very kind of siloed part of the organization, they don't necessarily get all the resources they want. We're seeing an energy crisis. We're seeing costs go up. We're seeing budgets stay the same in a lot of cases. And event professionals are asked to post a bigger and better event the next year with the same budget, despite the fact that everything costs more. And I think one of the best opportunities for people to do that is to start using a tool like Cloud Code. And I think we're going to see a lot more of it where event professionals are able to be this true multi-tool who can do more marketing, who's now able to build prototypes to hand off to a technical team that's able to do more sales and get more attendees, of course, with associations. That's always the question, "How do you attract more members?" So I think a lot of these organizations that have been on the smaller side and typically haven't had the resources are going to be supercharged using a lot of these AI tools.

[00:58:08:09 - 00:58:27:07]
Mallory
 And going back to your dad's prediction, reshaping work, event professionals, SPMs, I love that, Noah. Thank you both so much for this really insightful conversation. Father-son duo on the Sidecar Sync, it's been a great convo. Where can people find you, keep up with you? We'll drop the links in the show notes too, but it's always good to hear them from you.

[00:58:27:07 - 00:58:40:21]
Adam
 On my side, you can find me on LinkedIn and also Intro. If you have further questions or discussions or other ways I can help you, you can book some time with me one-on-one on intro.co.

[00:58:40:21 - 00:58:48:11]
Noah
 And then I'm on LinkedIn. I have a newsletter as well. And then I'm also often speaking at events like this in the events industry, whether it's webinars in

[00:58:48:11 - 00:58:53:21]
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[00:59:04:14 - 00:59:21:13]
Mallory
 Thanks for tuning into the Sidecar Sync podcast. If you want to dive deeper into anything mentioned in this episode, please check out the links in our show notes. And if you're looking for more in-depth AI education for you, your entire team, or your members, head to sidecar.ai.

[00:59:21:13 - 00:59:24:19]
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