The Great AI Rivalry and the Future of the Global Economy

It is just this completely wild unknown world we're heading into where basically these five companies are going to decide everything when it comes to the economy, business, and geopolitics.

Welcome to the Artificial Intelligence Show, the podcast that helps your business grow smarter by making AI approachable and actionable. My name is Paul Roetzer. I'm the founder and CEO of SmarterX and Marketing AI Institute, and I'm your host. Each week, I'm joined by my co-host and SmarterX Chief Content Officer, Mike Kaput, as we break down all the AI news that matters and give you insights and perspectives that you can use to advance your company and your career. Join us as we accelerate AI literacy for all.

Welcome to episode 207 of the Artificial Intelligence Show. I'm your host, Paul Roetzer, along with my co-host, Mike Kaput. We're recording on Monday, March 30th, 2026, right before 10:00 a.m. Eastern time. I don't know if we're getting new models this week, but there is a lot of chatter going on about what's coming up from all the labs, Mike. So, I would say this episode we're going to be setting the stage for what I think is going to be a pretty busy spring. In some ways, we might see some pretty rapid advancements from the models, and these labs are pushing out a lot of stuff. We're going to try and provide the context to what's going on and help people frame it into what it means for what they've got going on in their careers and their businesses. We will try and connect some dots. There's a lot happening. As we were getting ready for the show, even just two minutes before we came on, Mike and I were like, "Wait a second. Didn't this happen in 2024?" So, we're going to do our best to provide a little historical context into what's happening.

This episode is brought to us by AI Academy by SmarterX, which helps individuals and businesses accelerate their AI literacy and transformation through personalized learning journeys and an AI-powered learning platform. New educational content is added weekly so you always stay up-to-date with the latest AI trends and technologies. The AI for Departments collection features five course series and certificates designed to jumpstart AI understanding and adoption. We have AI for Marketing, AI for Sales, AI for Customer Success, AI for HR, and AI for Finance. Mike is wrapping up AI for Operations this week, so that one's going to be coming soon. We've got five already ready to go. If you join AI Academy or if you're already a member, those are all in there already. Operations is coming soon. So tell your peers in your organization if they're trying to figure this out; there's a department series for them. These series are an ideal launchpad for organizations that want to level up their teams and accelerate AI adoption and impact. Mike teaches the AI for Sales series and is going to be sharing some insights towards the end of today's episode, some takeaways from that series. Individual and business account plans are available now, or you can buy single courses and series for one-time fees. Visit academy.smarterx.ai to learn more.

If you're new to this, every week we give you a little rundown of how this works. We go through what we call our AI Pulse, where we take an informal poll each week of our listeners on how they feel about topics we talk about in that episode. Then we'll go through three main topics and then rapid-fire items.

AI Pulse Survey Results

From episode 205—last week's episode, because then we had an AI Answers episode that was episode 206—the first question was: OpenAI is building an enterprise deployment arm with private equity backing. What's your reaction? This one, Mike, looks like a perfectly split pie. 25% say it is a smart move because AI companies need distribution, not just models. 26% said they don't have an opinion. 28% said it was inevitable and every AI company will do this within a year. 20% said it's concerning because it blurs the line between AI vendor and consulting firm.

The second question we had was: Anthropic's 81,000-person study found the number one fear is hallucinations, not job loss. Does that match your experience? 43%, the largest percentage, said no, job displacement is still my top concern. 34% said yes, unreliability is the biggest barrier to trusting AI at work. We had 13% at neither, saying their biggest concern is something else entirely. 9% said they are not particularly worried about AI risks right now. That's interesting.

Then we did ask one more: How many AI tools does your organization officially approve for employee use? 45% said one to two tools. 34% said three to five. Only 15% said six or more. There was a small sliver that said none, AI is blocked or not addressed. I would imagine if you're listening to this show and you work for a company that's blocking everything, there's a decent chance you might not be at that company very long. You might be looking for a new career opportunity where you get to apply everything you're learning in AI. You can go to smarterx.ai/pulse to participate in those each week.

The OpenAI vs. Anthropic Rivalry

We are going to start off today with a topic that spun out of OpenAI canceling their Sora app, the individual app. We zoomed out and said, okay, let's talk about the bigger thing going on because we touched a little bit on this last week about how OpenAI was refocusing their efforts. I think we're starting to get a little bit more sense of why that's happening and where this is going. We wanted to frame it within the OpenAI versus Anthropic topic.

[Mike Kaput]: We had this week a major Wall Street Journal investigation that actually traces this OpenAI-Anthropic rivalry way back to basically almost a decade ago to a San Francisco group house that in 2016 multiple players were living in. It reveals that this feud—and it very much is a feud—is shaping the future of AI and is as much about personal wounds and power struggles as it is about these bigger picture topics of philosophy or safety. This piece from the Wall Street Journal is based on interviews with current and former employees at both companies. There are a ton of details in here that were previously never reported.

Tensions actually started very early. After Anthropic CEO Dario Amodei joined OpenAI in 2016, he watched Elon Musk very quickly thereafter order layoffs in ways that he considered needlessly cruel. He also watched Greg Brockman float the idea of selling AGI early on to the nuclear powers on the UN Security Council as they're all projecting out where AI is going to go and what they should do about it. Dario, as early as 2016 or 2017, started considering that kind of proposal tantamount to treason and nearly quit over it early on in his tenure at OpenAI. When Sam Altman took over OpenAI after Musk exited in 2018, things apparently got more complicated. Altman made Dario a promise that Brockman and Ilya Sutskever would never be in charge, or would not be in charge at the moment, and then turned around and made conflicting promises to Ilya and Greg.

As research into GPTs took off, Dario blocked Brockman from working on the language model project. Daniela Amodei, Dario's sister, who was co-leading that project, offered to step down rather than let Brockman join. Apparently, by 2020, relations had deteriorated to the point where Altman accused the Amodeis of plotting against him to the board. This all culminated in late 2020 when Dario, Daniela, and nearly a dozen employees left to found Anthropic. Before leaving, Dario wrote a memo arguing the ideal AI company would be 75% public good and 25% good for the market. Now, five years later, both these companies are valued at hundreds of billions of dollars and racing towards an IPO.

In recent months, Amodei has escalated the conflict sharply. He compared the Altman and Musk legal battle to basically Hitler and Stalin fighting. He called Brockman's $25 million pro-Trump super PAC donation just straight-up evil, and he likened OpenAI to a tobacco company. This is all happening as there are some very real competitive pressures reshaping both companies. This week, OpenAI shut down its Sora video app, and that was burning at one point a million dollars per day and it dropped to just under half a million users. Fidji Simo, the head of applications at OpenAI, described Anthropic's gains in the enterprise market recently as a wakeup call and told staff, "The company cannot miss the moment because we are distracted by side projects." Paul, the Wall Street Journal publishes this deep dive. There's a lot of personal drama here. How much of this is just personal versus the bigger picture philosophy?

[Paul Roetzer]: It definitely seems like there's just a lot of residual bad feelings. If you're relatively new to all of this—if you've been listening to the podcast for the last four years—you've heard this story unfold. Now, as Mike said, there's details within this that we didn't previously know. A lot of these elements, though, were relatively known, certainly the friction between them, but how it all came to be is the most detailed unfolding of events that I've seen. The reason we want to talk about it is because it's so relevant to all the other things that are going on right now. You have this battle over government contracts where we've got Anthropic being designated a supply chain risk. We'll talk about this in a couple of topics here, but the judge putting an injunction in place to not allow that, then OpenAI steps in the day they're getting blackballed and is like, "Hey, we'll take the contracts." For Dario, this is just like daggers. They have this long history. They're both racing to IPO this year. They're both trying to beat each other to the market. They're both being funded by a lot of the same people and companies. They're now in a battle for the enterprise, which every day I'm talking to companies and leaders at companies who are moving to Anthropic. It is a very common recurring theme I'm hearing.

When you look back in retrospect, November 2015 is when OpenAI was created. It was created intentionally as a counterbalance to Google. In the early days, it was Musk and Altman and Ilya Sutskever and Greg Brockman, and they wanted to be the alternative to Google, which they considered basically the evil empire. They didn't want them to get to AGI first. They wanted to create this nonprofit to do this research out in the open. It quickly becomes not a nonprofit, which creates the friction between Musk and Altman that we're still seeing play out that will go to trial. I think in April it's coming up fast. There's just all this drama going on.

The way that the Wall Street Journal tells this is a lot of this does stem from Dario Amodei not getting the kind of credit he thought he deserved for his contributions to really the whole transformational phase we find ourselves in with language models. Brockman tries to get Dario and Daniela to come join them. Greg is hanging out at the house, this group house they've got. Greg and Daniela, if I'm not mistaken, worked at Stripe together because Greg was the Chief Technology Officer of Stripe and Daniela was an executive at Stripe. I'm guessing that's probably how they got to know each other. Dario was working as an AI researcher at Google. 2016, Greg's trying to get them. Eventually, they come over. They don't agree to come on as founders, but they come over pretty soon thereafter because Greg's hanging out with everybody.

There's one other name that we haven't mentioned in great detail: Holden Karnofsky. This is an important element to the story. Karnofsky was the founder of a philanthropy that promoted effective altruism, which is the antithesis of techno-optimism. You have the Silicon Valley venture capital world that is pushing for acceleration at all costs, and you have effective altruism which is seen as the counterbalance to that. Karnofsky, who is Daniela's fiancé, is a major player in this, and Brockman actually starts to take an interest in some of the ideas behind the effective altruism movement. They start having all these debates in 2016 around, okay, well, if we do end up building AGI, if it goes this direction, who should we be telling? Should we be telling Americans about this—300 million people—that it's coming for your jobs, or should we go talk to the government first? Dario argued that when it came to sensitive topics like how fast AI was developing, it was actually better to go to the government first.

By mid-2016, Dario joins the lab. He's up working late with Brockman. They're actually working on AI agents. At that time, they're looking at video games and other things. This is when Musk is really heavily involved in OpenAI. Altman is not the CEO yet. They're just building this nonprofit. Ilya is playing a major role in the research direction of the company. Then the layoffs happen, led by Musk. In the fall of 2017, Dario actually brings in an ethics and policy adviser and they're talking about the future research direction and the impact it could have and the need to get the government involved. This is when Brockman, within the presentation, sees the fundraising idea that OpenAI sell AGI to governments including China and Russia, and Dario's like, "This is treason. What are you talking about?"

It starts to create all this friction. Then Musk exits in 2018. Now we've got the blow-up between Musk and Altman that leads to what you know today is going to trial. Altman steps in, takes over as CEO. They start really going down this path of the for-profit ideas. Karnofsky has since married Daniela and he's actually on the OpenAI board. Tensions really start to flare when OpenAI researcher Alec Radford—who we haven't talked a ton about, but is a name that matters—had laid the groundwork individually for these large language models. He was playing around with this stuff building off of the Google paper about transformers and he's developing Generative Pre-trained Transformers or GPTs. They start seeing the language model direction starting in 2018 and 2019. Brockman wants a piece of this and Dario, who was research director at the time, is like, "No way. Don't let Greg anywhere near this." Daniela, who's co-leading the language model project with Radford, tells Brockman he cannot work on it, and she offered to step down as head of the project rather than allow Brockman on it. You start to see the friction here is Brockman over and over and over again. You hear this throughout these issues through the years.

When Brockman said that he and Altman were going to meet with former President Barack Obama—they're now in the GPT-2 and GPT-3 range—Dario is now playing a major role in the development of this and the scaling laws and all these things. Dario gets cut out of a meeting with the president. Now he's pissed. That's when he gets a promotion. Altman does the thing where he says Brockman and Sutskever won't lead this. Eventually, Dario is like, he wants to leave and he says, "I want to report directly to the board or nothing. I'm either out or I'm reporting to the board. I want nothing more to do with all this drama." He's seeing the difference between market companies and public good companies. He's thinking they need to go in the direction of the public good. It becomes this wild unraveling and that eventually leads to them leaving.

The thing I referenced earlier that Mike and I were talking about right before we jumped on is Brockman's role in all this. If we go back to episodes of our podcast in 2024, we tell the story of Brockman taking a leave. What we eventually find is that at first, it was just he needed a break because he hadn't had one in nine years. Then it came out that the Wall Street Journal revealed the sabbatical was actually a mutual agreement between Brockman and Altman stemming from internal friction about Brockman's management style. Just to frame that 2024 time period, September 2024 is when the o1 reasoning model comes out. Brockman takes his leave in August. A month later, the breakthrough is released that they had been working on for a while called Project Strawberry, which was the first reasoning model. Mira Murati, who's the CTO at the time, then leaves the week that they announced the reasoning model, and then Greg comes back.

It's just wild drama, but it's all tied to what we're seeing play out today. The friction that exists between all these labs is they all know each other. They all came up together. They were all working in the same direction and they just kind of started going in these different areas. Each of these labs is working on what I would call these dimensions of AI progress. A few of the real important ones are Agentic, which we're obviously hearing a ton about. I'm going to drop a link in the show notes to a Lex Fridman podcast I actually just listened to. It was three hours long. Luckily, I had to clean my garage out yesterday, so I had three hours to listen. It's an interview with Peter Steinberger, who created OpenClaw. If you want to understand the moment we're in and what's happening with the agentic stuff and how these labs are so bullish now, you listen to this whole thing. It's wild.

There's agentic in that realm. There's something called computer use which allows the agents to use your computer. Continual learning is a big one. Memory is a really big one. Reasoning, and maybe the most important one, is recursive self-improvement. It's this idea that as these labs automate AI researchers, those AI researcher agents can then work 24/7 and they think from there we get to this recursive self-improvement moment where the labs or the models can actually continually improve themselves without human insight and oversight, and that then leads to the fast takeoff moment. World models is another one we've been talking a lot about.

What this leads us to is you still have these five frontier labs. When you think about what leads to a frontier lab, they need funding, they need data centers, they need energy infrastructure, they need compute capacity like Nvidia chips, and they need the most powerful models. Your tier-one labs today are Google DeepMind led by Demis Hassabis, OpenAI led by Sam Altman, and Anthropic led by Dario Amodei. Those are the three that matter the most at the moment. Then what I would consider tier-two would be Meta with Zuckerberg, and they're kind of the wild card. They've fallen off for the last 12 months, but maybe they get back in the game. Then you have xAI led by Elon Musk, which will go public as part of the SpaceX IPO later this year. They're not relevant in enterprise right now in business, but who knows where that goes. Tier-three is maybe at some point Microsoft gets out of their own way and they figure this all out.

Generally speaking, you have three major labs and two of them are at war with each other. Then when you go to the tier-two, xAI is suing OpenAI. It is just this completely wild unknown world we're heading into where basically these five companies are going to decide everything when it comes to the economy, business, and geopolitics. There are obviously labs overseas, especially in China, that should be part of the conversation, but I'm talking specifically about American AI labs. Knowing these backstories and knowing these characters is actually extremely important because when you look at that list I just gave you, DeepMind and Google somehow managed to stay politically neutral. Sergey Brin is actually on this new council Trump's created, but overall Google is trying to just play in the middle because they know governments change and they have to be in the game no matter who's in office. OpenAI historically has been similar, but then Brockman shows up and gives $25 million or $50 million to the super PAC and becomes the biggest donor to Trump. Now, whether OpenAI wants to be perceived in that way or not, there's no avoiding the fact that their president is the largest donor to the current administration. Then you have Anthropic, who is the enemy of the administration right now and they're very much left-center at this point. They're embedded in the tech administration and everything they're doing, but they don't really believe in a lot of those things. Then you go to tier-two and Meta and xAI are 100% in with the Trump administration.

The reason I bring that up is because politics sways. What happens if in two years or even during the midterms the power switches and then the companies that have gone all-in on one side or the other, what happens to those labs if all of a sudden the government doesn't award contracts to them? You see what's happening to Anthropic. What if it flips and somebody does the same thing to Meta or xAI? Then the only ones that are left are the politically neutral ones just trying to make the world better hopefully. There are so many layers to this and I think for people who care deeply about this and especially the downstream effects on the economy and the environment, it's really important to understand who's building this tech and what their goals are for it so you can pick and choose who you're cheering on and who your company's investing in or whose technology you're using. It's not a binary decision. There are lots and lots of layers to all of this. I'll stop there, Mike. I could honestly spend the whole episode just talking about this stuff. I just think it's really important for people to understand the complexity of what's happening.

[Mike Kaput]: Hopefully someone's writing a book about this whole background and history between these people because one thing that just jumped out to me is that whether you agree with the AI hype or not, all of these people have been taking seriously the prospect of AGI or something beyond it ten years ago. Ten years ago, before they even had a company, before they even had a business model, they were taking seriously who should have control of this technology and who should be notified of what and when. Now we're starting to see some of the fruits of that labor play out where we're suddenly in this mode where people are starting to seriously worry about how powerful the technology is. Who is behind the decisions really does matter.

[Paul Roetzer]: I will say when you listen to the Fridman podcast with Peter Steinberger, it sure as hell sounds like he's selling to Meta. I was actually shocked he talked as much as he did because Lex asked him point-blank, "Everybody's got to be coming after you. What are you going to do?" He's like, "Man, I've scaled a company before with VC money. I don't want to do that again. I'm not the CEO. I want to just build some stuff." He's like, "Well, who are you talking to?" and he goes, "Well, you know, I've had great conversations with both Sam and Mark and both have some positive things, but I'm kind of excited about the idea of going and working at a big lab and just getting to build some stuff and have unlimited GPUs to access." He's like, "Yeah, Zuckerberg was just playing with OpenClaw, building stuff and messaged me on WhatsApp and next thing I know I'm like, 'Yeah, I'd like to jump on a call in 10 minutes.'" It sure sounds like OpenClaw is going to get acquired by Zuckerberg for billions of dollars and Steinberger is going to go there and become part of that super intelligence lab. I can't see an alternative at this point unless Sam pulls a rabbit out of a hat and convinces them to come to OpenAI. It seems like it's one of those two places right now.

Anthropic's "Claude Mythos" Leak

[Mike Kaput]: Next up, we actually found out that Anthropic accidentally exposed details of an unreleased model that is nicknamed Claude Mythos through an unsecured content management system. This is being reported as a Fortune exclusive. Roughly 3,000 unpublished assets were apparently accessible for a time to anyone without authentication from Anthropic's website, even things that weren't published. These included draft blog posts, internal images, and documents about this unreleased model and also about an invite-only CEO retreat in the UK that Anthropic was running that was not public knowledge. The leaked drafts of this material describe Mythos, this new model, as a new tier above Opus, which Anthropic says is larger and more intelligent than the Opus models and has dramatically higher scores on tests of software coding, academic reasoning, and cybersecurity.

After Fortune asked about this, Anthropic confirmed the model is real. They called it a step change over previous models and the most capable they've built to date. They also state Mythos is currently far ahead of any other AI model in cyber capabilities and warn that it presages an upcoming wave of models that can exploit vulnerabilities in ways that far outpace the efforts of defenders. Anthropic actually planned to release it first to cyber defense organizations before making it more broadly available. Anthropic overall blamed the leak here on human error in their CMS configuration. This is unrelated to their AI tools having vulnerabilities according to them, though it is important to note their entire brand is built on being the responsible alternative and details are leaking out of this thing.

At the same time, OpenAI says it has finished pre-training its next major model. This is code-named for the moment, Spud. Altman told staff he expects a very strong model within weeks and that he said can really accelerate the economy. Paul, two big models. I don't think that means create more jobs. That might be a very intentionally worded way of saying that: "really accelerate the economy." So we've got maybe in the next few weeks two huge models. Clearly, at least one of them is a bit dangerous when it comes to cybersecurity. When do you expect these to drop?

[Paul Roetzer]: Who knows? Things change when they're going through the red teaming to make sure they're safe. It sounds like Anthropic in particular actually already has it in the hands of some beta users. Part of it depends on that feedback loop and when they're ready. But my guess is if they've got stuff queued up in a CMS that's unsecured, it's ready. You're getting ready to go to market. These things probably finished training months ago and they've been in post-training and red teaming getting them ready. But again, this is why we always say you cannot make plans based on your current experience with these models. There is always a more powerful model in training. The labs have already seen 6 to 12 months ahead of what you know to be true about reality. They know roughly what the capabilities are and they're probably just trying to make them safe at this point.

This Anthropic story is crazy. First, I feel for the marketing team or whoever owns the CMS. I would imagine somebody lost their job over that. I'm just speaking from experience of running a marketing agency. I can't even fathom being the person that allowed that to happen. Part of this is a story about accidental disclosure, a warning for other people to think about this stuff. Think about how much easier discovery of this sort of thing is going to be with agents where if you're competitive or if you're in more of the black-hat kind of stuff and you're trying to find vulnerabilities and exposures, you just run your agents 24/7 and go look for this kind of stuff.

Most importantly is this idea that there's going to be a leap in model capabilities soon. The exposure was 3,000 assets linked to this blog, which is crazy. The part that I found really interesting is Fortune informed Anthropic. Fortune finds this, they actually bring in cybersecurity researchers to assess it, but then they alert Anthropic to the fact that it's all there and they, to my knowledge, have yet to publish any of the information other than broadly saying a new model is coming and there's a CEO retreat. They didn't publish the blog post. They have access to all this stuff—images, documents, blog posts—and for whatever reason Fortune chose not to release the information. My guess is there's probably a quid pro quo here of, "We will give you an exclusive on whatever in the future, don't release it," and in exchange, you're going to get a first look at the actual Mythos. Media relations works in funny ways, but there's got to be some reason they did not do this.

The bigger models worry me. They talk specifically about reasoning, coding, and cybersecurity. None of this is new. We've known all the models are getting better at these things, but just the fact of how unprepared people are for what already exists and to know we're very close to these next-level models is worrying. Wall Street reacted not great. Cybersecurity stocks slumped based on news. I feel like Anthropic tanks the market once a week. We had Crowdstrike, Palo Alto Networks, and Zscaler drop about 6% each that day. SentinelOne tumbled 6% while Okta and NetScope each fell more than 7%. Tenable plummeted 9%. That was just on Friday. The idea that a new model is coming that's better in cybersecurity—which is funny because we knew this, it wasn't like this was, "Oh wow, they figured out how to cause flaws in cybersecurity." We've predicted this for two years. But anyway, it's how Wall Street works.

The Spud one we touched on last week, but the idea that Altman said the company would be renaming Fidji Simo's product organization to AGI Deployment. We are entering the phase where they truly all think we are approaching whatever you want to call AGI. We are there. That led me to go back to the stages of AI that we've talked about many times on the podcast. Back in July 2024, Rachel Metz of Bloomberg did a story called "OpenAI Scale Ranks Progress Toward Human-Level Problem Solving." In that, she had gotten access to OpenAI's internal stages, which they later confirmed were in fact true. They came up with these five levels to track progress toward building artificial intelligence capable of outperforming humans.

The company believed at that time—this gives you a sense of how fast we've moved—in a year and a half, OpenAI executives told employees at that time that they thought they were at Level 1, which was chatbots, AI with conversational language. That was summer of 2024, less than two years ago. According to a spokesperson at that time, they were on the cusp of reaching the second, which it calls Reasoner. Level 2 is Reasoners, which is human-level problem solving. That goes back to what we talked about in the first topic, which was September 2024. A couple of months after this comes out, we get our first reasoning model. In a meeting in that summer, they actually previewed the o1 model that would then be released in September, right when Greg Brockman was on his leave and Mira Murati was piecing out of OpenAI to go start her own lab.

Level 1: Chatbots. Level 2: Reasoners. Level 3: Agents, systems that can take actions, which we are right in the midst of takeoff with agents. Level 4: Innovators, AI that can aid in invention, which we are seeing early signs of. Level 5, which is why OpenClaw becomes so critical to this whole conversation, are Organizations, or AI that can do the work of an organization. That was a topic I didn't want to have to get into in 2026. My hope was that we would have another year or two of runway before we were talking about Level 5 being within reach. But I do think that throughout this year we're going to have a lot more conversations around entering into the early phases of Level 5. I think Innovators, we will clearly be at that stage by this fall. I think you can make an argument we're kind of already there in some disciplines, but I think across most industries we will be clearly into Level 4 by the end of this year. I do think that in some industries you will be seeing very early signs of Level 5. I don't honestly know; I would guess they probably have a Level 6 internally. I don't know what it is, but just so people understand how fast we went from Level 1 to emerging into Level 4 in basically 20 months. That is a way shorter timeline than I would have thought.

Brutally Honest CEO Perspectives on AI

[Mike Kaput]: Our third big main topic this week is about a couple of different comments from some CEOs that are a bit brutally honest about AI and its impact. The first one comes from Uber CEO Dara Khosrowshahi, who broke what amounts to an unwritten rule in tech this week. He did an interview on the very popular podcast Diary of a CEO and he said he has personally heard executives privately admit the true scale of AI disruption and then watch those same people go on TV and tell audiences that everything will work out fine, which is something we have talked about on this podcast. He said that he understands why they do it because being honest about job displacement scares investors and drives up fundraising. However, he said he estimates that AI will eventually replace the work that 70 to 80% of humans do, including in knowledge jobs within the decade and physical roles like driving within 15 to 20 years. Which begs the question he was asked: what do Uber's 9.5 million drivers and couriers do next? And he literally said, "I don't know."

At the same time, we got some comments from PwC's US CEO Paul Griggs, who told the Financial Times that partners who are "not paranoid about being AI first" will be replaced. He said, "I don't think anyone gets a free pass here. Anyone, an employee who thinks they can opt out of AI is not going to be here that long." Interestingly, PwC has cut 5,600 staff last year. They're shifting tax and consulting services into certain AI-powered subscription tools that, at least in the first steps of operation, work without a PwC person in the loop. Paul, I thought those were two pretty telling comments. We've talked quite a bit about what you're hearing behind closed doors, how people are not talking about this publicly. Is the dam starting to break here? Because six months ago, we wouldn't have heard any of this.

[Paul Roetzer]: I just don't feel like there's going to be any way to avoid it. Every three months these CEOs have to get on earnings calls and it's getting really hard to not say out loud what they've been saying privately. This echoes what I've been trying to create urgency around these last couple of years, which is what executives are saying privately to me and what they're saying publicly have been two completely different things for a year and a half or two years now. This is where I'm spending a lot of my time. I'm going on a trip with my family coming up here and I have long plane rides. I think I'm going to use that time to just try and unplug and think more deeply about this. I've shared a little bit with you of the direction I'm going here. I've actually had some conversations with some listeners at some big enterprises who are thinking about these things as well. No names, but I appreciate their perspectives on this. It's very helpful for me to think this through.

Where I'm currently at is I think AI-forward managers and above—directors, VPs, C-suite—who have a deep understanding of AI capabilities plus domain expertise and institutional knowledge are going to be in good shape in the near term. I think if you go all-in on this stuff, you figure it out, and you can help design workflows and systems and integrate agents, you're going to be worth way more money today than you were yesterday. Your companies will figure that out. So, I think your career prospects, if you fit into that AI-forward manager and above category, companies are going to be looking for that talent.

I think professionals across all levels who are resistant to learning AI and evolving are going to have a very difficult time remaining employed where they are, as you highlighted with the PwC example, and finding employment once we get outside of the next one to three years. It is the brutal reality that I don't like, but I just really feel like across industries and across jobs, people who just resist this for whatever their reasons are—and some of them are very good reasons and I empathize with those reasons—I don't know what else to tell you. You won't be employable. It's a very brutal reality.

My biggest concern is entry-level work. I just keep coming back to this. I don't know what you're going to hire those people for. I have some theories, some ideas I'm at least working toward to try and crystallize in my own mind. That's why I need time to think more about this. But I don't know the answer to what those people do when the layer above can do all the tactical work by simply prompting a system. It can do all the things they would have done to learn the administrative work. All of it's going to be easily done by these models. That's before we have the step change that's coming apparently this spring.

You mentioned this National Bureau of Economic Research paper. I dug into this one a little bit that was related. I had not seen this yet. Great use for NotebookLM. You and I both, Mike, use it. You have a whole podcast with all of our episodes in NotebookLM. It's a great summary thing for me. I'll take these dense research papers. I'll just read you the summary that NotebookLM wrote on this. I thought it was really helpful.

"2026 National Bureau of Economic Research working paper examines how AI is transforming corporate productivity and labor markets. Through a survey of approximately 750 financial executives, the authors identify a productivity paradox where executives perceive high performance gains from AI that have yet to fully materialize in official revenue data." We see that all the time. Sometimes you have to look at leading indicators, but it's not going to show up yet in GDP or revenue within the organization. "While adoption is widespread, investment intensity and motivations differ significantly between large and small firms, with larger companies focusing on labor cost reduction. Despite concerns regarding automation, the study finds minimal aggregate employment declines, suggesting the AI currently functions more as a tool for task enhancement than for total job replacement. However, a significant reallocation of labor is underway as demands shift away from routine clerical roles towards skilled technical positions. Ultimately, the research suggests that AI-driven growth is primarily fueled by innovation and product development rather than simple capital deepening."

The one thing I'll note related to this, Mike, is the audience of people they interviewed is from November to December 2025. So, relatively new data given the moment. But they are interviewing CFOs. While there are exceptions to the rule, the CFO is generally not the person I've been meeting with in enterprises who has the greatest comprehension of the moment we find ourselves in from a technology perspective and what these things are capable of doing. They don't always have the highest degree of AI literacy and capabilities themselves. They're not pushing the models every day and finding business cases. It's not usually the CFO doing that. Therefore, those CFOs who you're asking about this might not even be aware of the reasoning capabilities or the agentic advancements that are happening. When you think that the research was done in December, that was before the Claude Code moment that basically changed everything, before OpenClaw, and how much has changed just in three months. While it's always good to look at this kind of data, you do have to frame it with who they were asking and what the AI literacy and competency levels of those people were. Not that they're not super smart and super accomplished, but it's just not their job to be the one that's staying up on all the latest model news. It's just information. It's good. Put it in the filing system in your brain to understand the context of where we are and how to talk to people in your organization, but it's not an end-all-be-all. It doesn't mean that all of this is exactly true within your company or industry. It's a very dynamic place and we need all these different perspectives, but you have to piece together your own story.

[Mike Kaput]: One other thing that jumped out to me that reinforced a lot of what we've discussed over the past year is the PwC US CEO Griggs, who said basically an employee who thinks they have the opportunity to opt out of AI is not going to be here that long. I assume that's been very clearly communicated internally if he is telling the Financial Times that. If it's not, that's probably a good memo to get out this week. I know that can read as harsh to a fair amount of people, but I really appreciate the honesty because I know behind closed doors, I know of organizations where people are already complaining about employees who are not embracing this stuff because they know they have to. It's not been expressed to them clearly that this is a condition of their employment whether you agree with it or not. At least the expectations are very clear and I think that's more important than ever.

[Paul Roetzer]: It's like anything else in life. Think about kids and stuff. Sometimes you have to tell people the hard truth and they may not get it yet. It might be five years until they grow up and realize their parents were right. I feel like this is kind of one of those situations where people don't want to hear this and I totally understand that. I have complete empathy for how hard this is and, honestly, how unfair it's going to be. But there is no control over that. This is happening. The models are going to get smarter. They're going to get more generally capable. They're increasingly going to do the tactical things you and I do for our work every day. Pretending like that's not happening or that it's not going to affect you or your family or your peers is just not a winning scenario. As harsh as it seems to say what the CEOs are now increasingly publicly saying, I would much rather they just said it than pretend like it's not going to happen. I know plenty of enterprises and leaders who know what's going to happen and just refuse to publicly say it or to say it to their own people. I would really rather we just dealt with the hard stuff now and had time to be proactive about doing something about it than pretending like it's just going to be okay because it always has been before when general-purpose technologies came into the world. That is either choosing to lie or being ignorant to how different this transformation is versus the previous general-purpose technologies. There's not much room in between that. It's one or the other largely.

Rapid Fire: Anthropic vs. The Pentagon

[Mike Kaput]: Let's dive into some rapid-fire topics this week. First up, we have an update in the Anthropic versus Pentagon saga yet again. This past Thursday, federal judge Rita Lin issued a preliminary injunction blocking the government's supply chain risk designation against Anthropic. This is in response to lawsuits Anthropic has filed challenging that distinction. In the ruling, Lin wrote that nothing in the governing statute supports the "Orwellian notion that an American company may be branded a potential adversary and saboteur of the US for expressing disagreement with the government." She also found that Anthropic is likely to succeed on the merits of its lawsuits. This injunction blocks 17 federal agencies from enforcing this ban on using Anthropic, including the original February 27th order from Secretary of War Pete Hegseth and also President Trump's social media directive to not use Anthropic.

The Pentagon is not backing down, at least publicly. Hours after the ruling, CTO Emil Michael called this a disgrace. He claimed it contained dozens of factual errors and argues that one of the two supply chain risk designations that they have put into effect remains in full force under a separate statute. The government has seven days to appeal this. Dean Ball, who is a commentator we talked about quite a bit here as well and previously served in the Trump administration, called this a devastating ruling for the government. Paul, where does this actually leave us? It seems like this is just the next battlefront.

[Paul Roetzer]: I guess we're just waiting for the appeal. The judge said everything that everybody was thinking. It sure seemed like this was just a vendetta. I've said on the podcast before, I just think it's egos and vendettas and politics, and it's not really about the technology or Anthropic. We touched a little bit earlier on how politics does unfortunately play a role in this increasingly. I hope they eventually negotiate it. I keep thinking they'll eventually come down, but each side keeps digging in. We'll wait and see what the appeal brings. I'm sure this will take forever to actually come out the other end, but it seems in the meantime the government's going to keep using their tech anyway.

This Week in AI Politics

[Mike Kaput]: Some more political news. We have some more AI political moves this week. First up, Senator Bernie Sanders and Representative Alexandria Ocasio-Cortez introduced the AI Data Center Moratorium Act, which would pause all new data center construction nationwide until Congress passes federal AI legislation that has protections for workers, consumers, the environment, and civil rights. It is one of the most aggressive AI policy positions staked out this Congress. It is worth noting over 100 local communities have enacted their own data center moratoriums. According to the bill, this ban would only be lifted after passing those federal AI regulations or legislation that would have those kind of protections. Once the ban's in effect, they have to pass a law that actually satisfies the conditions here to get the ban lifted. This bill is unlikely to advance, but does reflect some very real political pressure and shows how perspectives on AI are scrambling party lines ahead of the midterms.

Second, in basically the opposite direction, President Trump has appointed Mark Zuckerberg, Jensen Huang, Marc Andreessen, Sergey Brin, and other major tech leaders to a new President's Council of Advisors on Science and Technology focused on AI that is co-chaired by David Sacks and Michael Kratsios. Notable absences from this council so far include people like Sam Altman, Elon Musk, and people from Microsoft. As a note, co-chairing this council is going to be David Sacks' new role within the administration because he very recently stepped down as AI and Crypto Czar. Sacks also told Bloomberg that Congress could pass bipartisan AI legislation within months, creating a national framework that would override the patchwork of state laws. We've talked about how the White House has recently released their legislative blueprint or wish list for AI, which calls for child safety protections, streamlined data center permitting, IP protections, and more. It is an open question whether or not the two parties can cooperate to actually pass bipartisan AI legislation, especially before midterms. Paul, I'm curious what you make of these two recent developments. Symbolically, that data center moratorium seems to be trying to tap into some populist anger.

[Paul Roetzer]: AI is becoming more political, which we assumed. A pause is not going to happen. Their efforts to raise awareness about the issues is good. It's going to get citizens more educated and involved hopefully, but it is not to get the legislation passed. That's not happening. I also would not hold my breath on any federal legislation around AI. I think it's just a stall tactic to even be pretending like they care to do that. I would be really surprised if there was actually any AI federal legislation before the end of the year.

This council, there's almost nothing known about it. The White House's own announcement about it was like three paragraphs long and it just pretty much said that these are the people who've agreed to be on it and that it could be up to 24 members. That's pretty much all we know about it. It's not really worth talking about much other than there's some big names on it and some names that aren't on it, which is noteworthy.

The related thing is another pro-AI PAC popping up. Axios had this: a new pro-AI political operation is jumping into this year's midterms with a plan to spend more than $100 million. The latest push by a big-money group to promote a deregulation agenda. The group is dubbed Innovation Council Action and has the blessing of Sacks. It's distinct from other pro-industry groups in that it's focused on boosting President Trump's priorities. The new group is led by Taylor Budowich, a former White House deputy chief of staff for Trump. He also formerly led the pro-Trump group MAGA Inc., a super PAC. The group compiled a scorecard assessing how supportive lawmakers are of Trump's AI agenda, which will be used to determine who the group supports or opposes. Because the organization is a nonprofit, it is not required to disclose its donors—a dark money organization, as it is generally called. Sacks said Innovation Council will play a critical role in advancing the innovation agenda championed by President Trump.

Other AI-focused political groups include Leading the Future, which has raised $50 million. That group's list of donors includes Greg Brockman, Joe Lonsdale, who's a co-founder of Palantir, and Marc Andreessen of Andreessen Horowitz. Meta has launched a pro-AI super PAC effort that is expected to spend around $65 million for midterms with plans to focus on state-level races. Quick math: just those three alone is almost $300 million in ads about AI deregulation and trying to elect people who want to accelerate at all costs. That is why I would not hold my breath on any federal legislation. You're going to see more AI ads than you could want to ever see. It's going to be interesting.

AI Agent Nightmares

[Mike Kaput]: As AI tools get more powerful and more people rely on them for real work, the security risks are scaling up just as fast. We got this week a case study in what that can look like. Most AI tools are actually built on top of layers of software packages, often open-source software packages that developers install and end up trusting to power their software. Andrej Karpathy, former director of AI at Tesla and OpenAI co-founder, flagged what he called a "software horror," which was an attack on one of these open-source packages that millions of people and programs depend on. He outlined this in a post on X. This package, called LightLLM, has 97 million downloads per month. It is widely used across the AI ecosystem. This past week, attackers slipped malicious code into a routine update. What it meant was anyone who had it installed had their passwords, cloud credentials, API keys, and other sensitive data silently stolen and sent to the attackers. This spread far and wide because a lot of tools depend on LightLLM behind the scenes. The poisoned version of this program was live for less than an hour, but it was only discovered because it had a bug that crashed a developer's machine. Karpathy noted that if the attacker hadn't made that mistake, this could have gone undetected for days or weeks. The attack was part of a broader campaign that hit five different software ecosystems.

The point is, AI agents are about to make risks like these much, much worse. OpenAI just backed a startup called Isara at a $650 million valuation. They are building software to coordinate thousands of AI agents working together. That sounds great, but as agents start installing software, making decisions, and managing systems on their own, this kind of thing where your agents are going to download open-source software that has been poisoned or compromised is going to grow dramatically in its frequency. Paul, if you have agents running for you, how can you be sure you're not downloading something that's handing over your personal information because it's been exploited or poisoned?

[Paul Roetzer]: I have no idea. I'm pretty convinced that most people using these things have no idea. There are just so many unknown risks. That's why people keep talking to me like, "I can't believe you're not doing this and that." It's like, dude, I don't even understand the risk associated with that stuff. I'm just in no hurry to find out. I've said for the last couple of years that IP attorney is one of the safest professions to go into for the next decade because of all the issues tied up in AI and the use of copyrighted materials. Cybersecurity is another safe profession. The surface areas where you can be attacked and the complexities that are going to need to be solved to use this kind of stuff within enterprises is endless. We're going to race ahead and have these really advanced models and these agentic capabilities, and then the risks just compound when you start doing this stuff. That's going to create a lot of friction for adoption within organizations, which honestly at the end of the day is probably going to be a good thing. The model companies aren't going to slow down, so I think enterprise and human friction might be the only thing that saves us here—just that it's going to take a while for us to figure all this out and integrate it into what we do. Just because the models are capable of replacing some human labor doesn't mean they're going to right away. In the end, that's a good thing.

[Mike Kaput]: It's almost the flip side of what we talk about as the benefits of some of these tools where AI gives non-specialists this ability to do specialist things, but there's a danger there because now I'm suddenly exposed to all sorts of decisions that are in domains I have no experience in. If I want to go "vibe code" something and an agent recommends downloading three open-source packages to facilitate what I want to code, there are probably 18 different questions that a software developer would have that I don't even know to ask that are very dangerous.

[Paul Roetzer]: I can build apps all day now. I can just play around in Claude and just build some stuff and it's amazing. But to move it into production and to put stuff publicly live and open up—that's not my area of expertise. I'm in no rush to put things out before I understand what we're doing.

Apple's AI Reboot

[Mike Kaput]: Apple is planning to open up Siri to rival AI assistants in iOS 27. They are ending ChatGPT's exclusive role inside Apple software. According to Bloomberg, users who have Google Gemini, Anthropic Claude, or other AI apps installed will eventually be able to route Siri queries directly to those services through a new extensions system in settings. Apple plans to announce these changes at WWDC on June 8th. This basically eliminates the need for one-off integration deals like the original OpenAI partnership. Any AI app in the App Store could potentially plug into Siri. Apple is actually going to take a cut of paid subscriptions through its payment system.

Separately, Apple is building a standalone Siri app with a full chatbot-like conversation interface and a unified search system. The goal is to transform Siri from a voice assistant into an actual system-wide AI agent, but a lot of these updates were first announced in 2024 and have been delayed multiple times. Lastly, behind the scenes, The Information reports that Apple's partnership with Google is a bit deeper than previously known. Apple has complete access to Google's Gemini model in its own data centers and is actually able to distill it into smaller models that run directly on Apple devices. Paul, some interesting updates here. Most notable is that Apple is trying to expand the types of AI that can be used with Siri while they apparently get their act together.

[Paul Roetzer]: It's a continued waiting game. At some point, Apple's going to figure it all out and they'll show up and it could change everything from an adoption perspective and from a usage perspective because they have trust and they have access to everything—all the apps, all your data. If they solve the health side, I would totally rely on Siri more than I would anybody else because they already have all that health data in my phone. They are the wild card here and it seems like a smart strategy to just let everybody else spend the hundreds of billions of dollars building data centers and infrastructure and frontier models and they'll just serve them up to the billions of people that use their devices and not try and compete in that game. In the end, it may work out in their favor that they just missed the game up front and they're going to show up late and figure it out.

Doesn't this make Perplexity just irrelevant? We don't talk about Perplexity much anymore anyway, but isn't that their whole thing—that you can just choose whatever model you want and connect whatever you want? If I can just do that through Apple through my Mac devices and through my iOS devices, what would I ever need something like a Perplexity for?

[Mike Kaput]: Yeah, just another chapter in "Perplexity needs to get acquired quick." Sell at the top, which might have been 18 months ago.

SmarterX Use Case Spotlight

We hear from listeners all the time that one of their favorite parts of the show is when we talk about how we're actually using AI at SmarterX. We wanted to try to make this a regular segment. Every week we're going to attempt to give you a quick dedicated look under the hood at real AI use cases that we are exploring, building, or deploying in our own work. Paul, you've been working on some stuff related to AI learning journeys.

[Paul Roetzer]: Like I've said before, some of the stuff I traditionally wouldn't even talk about publicly before we just did the whole thing. But more and more we're just trying to build in public to a degree and share what we're learning as an AI-native company and try and just help other people along. I spend a lot of my time on the vision and innovation side of the company and trying to think about how this technology empowers us to innovate in new ways, build new things, and create more value faster for our customers. On the AI Academy side, I always tell the team we're not in the business of selling courses. We're trying to power personal and business AI transformation. You can go to LinkedIn Learning and get amazing courses. You can go to Coursera, Udemy, or directly to OpenAI or Anthropic. They all have great stuff and we would recommend those courses. We're not trying to compete with any of those companies; as a matter of fact, we would do deals with those companies.

I think more broadly about what it takes to actually drive a transformation either individually or for an organization. What role specifically do courses and certificates play in that bigger transformation? I think more holistically from a change management perspective: you need assessments, employee surveys, executive briefings so that they're on the same page, employee communications plans to tell people jobs are changing and the future of work looks different. You need the learning management system, the courses, personalized learning journeys, and workshops. I've basically been devising what I'm calling an AI Transformation System. This is something I'll share more publicly and publish some stuff on.

I've been working on this for a couple of years and made a lot of advancements in the last two weeks in particular, but the design and the visualization of it is just not my area of expertise. I have sketches—I literally lost a sketch at a hotel in Arizona years ago. I hadn't taken a picture, but I remembered I actually had a friend who was a designer take a picture and he sent it to me. Thank goodness I was able to retrieve it. But I can't get there. I just kept running into these barriers where I couldn't figure out a way to visualize this thing. Last week I thought, "Wait a second, what if I just wrote, as I would a project brief for a designer or developer, the whole story of what I'm trying to do?"

I spent three hours writing a prompt. The whole prompt is 1,000 words and 7,200 characters. It's not an insignificant prompt. I said, "I want to create an interactive visualization representing paths of AI transformation across our AI Transformation System. It's a collection of resources and systems that accelerate literacy and success. The core component is our AI Academy. We see literacy as a fundamental part of personal and business AI transformation, and personalized learning journeys are at the heart of what differentiates our approach. We want to show learning journeys that are made possible by our courses and experiences. But we also want to convey how those are just part of the overall process. The visualization should convey a sense of time and progress."

There's another thousand words to this thing. Then I just put it into Gemini, Claude, and ChatGPT. Gemini gave me an infographic, so that was useless. Claude gave me a solid V1 with a drag-and-drop capability of building these custom journeys and timelines where you can go by month, and it was amazing. Then GPT-5.4 Thinking gave me a really solid prototype that was similar in style to Claude where I could interact with it and I could actually build these custom journeys. Both of those were far beyond anything I had conceived of with my sketches. My sketches were just obsolete. They were more like what I got out of Gemini. It was basically an illustrated version of my sketches from Gemini, and the other two things gave me totally interactive things. It's a really interesting example of the need to test multiple models when you're doing these high-value use cases and to think about this project brief approach. If you really want to do something high-value, take the time to write a prompt as though you were giving it to an outsourced person or an internal person who's going to run with that project. Think the whole thing through. I did it in depth. I thought through every element of the transformation system I'm designing. I gave descriptions for every one of them. I built our entire course catalog into this thing. It was very extensive. Then you just hit go and pray and wait. Seven minutes later you're like, "Holy cow, I can't believe it just did this." Then you start moving things around and using the filters and you're just like, "Oh my god." Months and months of work, and what would have cost me tens of thousands of dollars easily to work with a developer to build, I had in seven minutes. It was just shocking in an amazing way.

[Mike Kaput]: That is incredible. I will just quickly also share something I've been working on. I am obviously creating quite a few of our course series for AI Academy. There's this big problem I run into every time I sit down to do a course series: I spend weeks on research, synthesis, scripting, and outlining, and basically wrap up the course, except it's still not really wrapped up. I face a final slog, which is I have to literally create hundreds of slides before I can record anything. Each department series we do has four courses. That's hundreds of slides per series. We have templates, so we've streamlined this process quite a bit, but it still takes hours of work to do. It's not intellectually rewarding work.

What I've been trying to do for months is try to get AI to create slides for me. There are generic AI slide tools that have been decent for a while, but we have really specific branding and templates. I can't just say, "Hey, create a deck for me from scratch." I had something that's a little more bespoke. Finally, I was actually able to get Claude Code to do this with a pretty high degree of fidelity for the specific stuff I'm working on. What was really cool about this is taking the time up front to really pull together an excellent set of example files and guidance and actually put it into planning mode before creating anything. I said, "Here's what we're trying to plan out. Here's all the nuance and context. Here's what's gone wrong in the past. And by the way, here's a folder with all the examples." After some wrangling back and forth, I actually got to a point where we now have a skill where Claude Code can take some scripts and actually put those into your presenter notes in the right places for each slide and actually build the slides for you with some placeholders. It's not perfect at everything, but last Friday I got to a place where instead of hours and hours, this process took maybe 20 minutes back and forth. Obviously, it took hours before that to make it actually work, but I was so happy that I finally got to this point. I think it was a more diligent approach to the context. Because Claude has gotten better with PowerPoint, this might have been the unlock.

[Paul Roetzer]: That's awesome. That goes back to 2023 when we were getting these early previews from Microsoft and Google of what was to come and how all of your productivity apps were just going to have AI infused in them. Then it ends up Claude builds a better way to do PowerPoint than Microsoft does. It'll be interesting, Mike, because I build courses also and do public speaking. I build slides first. Mike's a script guy. Mike develops the scripts first. I actually don't script things. I'll often do an outline of what I want it to be, but I generally build best when I just start putting slides together and then I'll form my thoughts from there. Most of the time for me when I do presentations or courses, I don't have scripts at all. I don't even know that Mike's approach will work for me because we just approach our workflows differently. But it's awesome and it almost makes me want to try scripting the next time I do it to see if I can figure it out.

[Mike Kaput]: That's a super important point, too. That's why I kind of dissuade people from saying, "Look, I could give you the skill if you wanted to." It's going to be useless to you. It's so bespoke to what I do and how I work. Plus with something like Claude Code, it's referencing other skills and preferences and memories about what I like and don't like. It also requires eight other skills that are required for course creation. The point here is just know what's possible and then go experiment doing it on your own in your particular context.

[Paul Roetzer]: It goes back to the whole AI Transformation System idea. Personalized use cases are so critical. If you just approached this broadly and said, "All right, let's automate the creation of PowerPoints," that's not even uniform because you have different workflows. You really have to drill in and create these very specific personalized use cases. When you do that right and you take the time up front, that's when you can unlock dozens or hundreds of hours of productivity or efficiency by just doing a little extra. Take the three hours, write the thorough prompt, and think it through like you're going to give that project brief to somebody.

AI Academy Spotlight: AI for Sales

[Mike Kaput]: Each week we're going to start spotlighting one of the courses in AI Academy that is currently live. The real point of this is to give you a peak behind the curtain of what's actually in these courses and give a value-driven takeaway that you can use right now. This week we are talking AI for Sales, which is our four-course certificate series built specifically for sales professionals. I was going to maybe just run through a couple of big takeaways that came away from that one for me.

First up, what really jumped out here to me is that sales reps really only spend about 30% of their time actually selling. That number has not changed in several years according to some research from Salesforce. Basically, you just spend way too much time on stuff that is either leading up to the sale or that is admin or distractions from the sale. What we do in the course is we approach this very practically and help you find those immediate use cases that can actually free up your time so you can sell more. That's goal number one of this course: making you more productive and freeing up your time so you don't have to do all this stuff that's a distraction.

The way we do this is first we start out with the advice of when you're looking for your own AI use cases, run what we call the "checklist test." If you're thinking about all the stuff you do in a day, if you can write the steps out for that—if you could teach this to a new team member pretty easily and they could follow it without needing to ask too many questions—guess what? That is something you should highlight as a candidate for AI automation or augmentation. Any sales rep could sit down right now and in 10 minutes walk away with a few ideas of what they are doing in a day that has the same steps every time. You do not need to be doing that yourself.

Takeaway number two for sales pros is when you go to think about what AI can do that stuff for me: audit your existing tech stack before you buy anything new. All the new AI shiny stuff we talk about is incredible, but sales does so much in existing systems. Pursue longer-term technology projects and new tech that you want to integrate into your CRM, but look to your existing CRM and systems first because things like Salesforce Einstein, HubSpot, and Microsoft all have really powerful AI increasingly baked in. Even if the AI is not perfect, using the thing you already have that's already approved makes your life so much easier.

Finally, it's really important to remember this basic but powerful advice: if you're still prompting AI of any type, whether it's in your CRM or a separate tool, if you're prompting it like a search engine, you need to evolve your approach. We actually show this side-by-side in the course. A one-sentence generic prompt is going to give you a very simple, very generic output. However, if you really structure your prompt with things like giving the AI a role, telling it its task, giving it context, examples, and telling it what format you want, that is the way you get truly exceptional results from AI. The more context you give these tools, the more value you get.

[Paul Roetzer]: So many of those are takeaways from really any department. We're spotlighting sales here, but really those three steps are applicable to whatever department you're in or whatever your role is.

AI Product and Funding Updates

[Mike Kaput]: To wrap up this week, we've got some AI product and funding updates. First up, Harvey is the AI platform for legal work that is used by over 100,000 lawyers across 1,300 organizations. They just raised $200 million at an $11 billion valuation. Their total funding is now exceeding $1 billion.

Next up, the OpenAI Foundation announced it will invest at least a billion dollars in 2026 across life sciences, jobs, and economic impact, AI resilience, and community programs. The foundation actually received a 26% equity stake in OpenAI as part of the company's restructuring. It's worth about $130 billion on paper.

Also related to OpenAI, they have shelved plans for their adult mode chatbot indefinitely. That follows pushback from staff and investors about the effect of sexualized AI content on society. This joins Sora on the list of the side quests being dropped as OpenAI refocuses its core business.

Anthropic has launched Computer Use and a feature called Dispatch for Claude Pro and Mac subscribers on macOS. Computer Use lets Claude control your mouse, keyboard, and screen to complete tasks across applications. Dispatch enables continuous conversations across devices, so you can assign Claude a task from your phone and pick up the results on your desktop.

Google has set a 2029 deadline for migrating its systems to what they call post-quantum cryptography. They warned that quantum computers are going to pose a really significant threat to current encryption standards and it might happen a little earlier than they expected. Android 17 is already integrating quantum-resistant protections.

SpaceX is preparing to file its IPO prospectus with regulators. They're targeting a June public listing. Advisers predict the company could raise more than $75 billion, which would actually surpass all the money raised by US IPOs last year combined. They were last valued at $1.5 trillion.

Microsoft has told managers at its Azure cloud and North American sales divisions to suspend new hiring, citing the need to restrain costs and improve margins. This freeze covers tens of thousands of employees. Microsoft stock is down significantly this year; it's one of the worst performers in big tech.

Finally, a cluster of news about Meta this week. Mark Zuckerberg is building a personal AI agent to help him be CEO. It helps him retrieve information he'd normally go through layers of people to get. Meta employees are now using personal agent tools like MyClaw and Second Brain, as they're called internally, to talk to colleagues and their agents on their behalf. Apparently, AI tool usage is now a factor in employee performance reviews. CTO Andrew Bosworth is taking over Meta's AI for Work initiative, overseeing the push to make the 78,000-person company as nimble as AI-native startups. Meanwhile, Meta has launched a new executive incentive program that, to fully pay out, would require them to have a $9 trillion market cap by 2031. That's a 500% increase from the current 1.5 trillion.

Finally, on the research side, Meta introduced something called Tribe V2, a trimodal brain encoder foundation model that is trained on 500-plus hours of fMRI recordings from 700-plus people. This creates a digital twin of neural activity and enables predictions for how the human brain responds to sights and sounds.

[Paul Roetzer]: That last one sounds kind of a little sinister. I hate ending podcasts like this, but anybody but Meta, I would have liked to have seen this research come up. What is a social network going to do with that—predicting how human brains respond to sights and sounds? I can't come up with a positive use of that type. When I saw that research, I was like, "Oh god, stop." They don't have the best track record of doing things like that for the good of humanity. Maybe they'll turn it in a positive way, though; that would be nice.

One final reminder: our AI Pulse survey this week is in the field at smarterx.ai/pulse. This week's survey asks about your perspective on some of this company messaging about AI and jobs. We're also going to ask your perspective on the new data center construction in the US. Paul, thanks for breaking down a busy week in AI for us.

Next Tuesday, which is April 3rd, our regular weekly is going to be replaced because I will not be available to record it. Mike and I are going to do something different. We're actually going to do a quarterly trends briefing. We are going to drop an episode next Tuesday, but it's going to be a Q1 trends briefing. We're going to look at everything that's happened over the last quarter. We usually do this as part of our AI Academy. We're thinking about moving the trends briefing to a regular podcast episode because it's so valuable and it's so helpful to frame this for everybody. Just something to look forward to next week. We will have an episode for you next week while I'm away, and it'll be a Q1 AI Trends Briefing for Business. Keep an eye out for that. Have a great week and a half or so before we talk to you again. We appreciate it.

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