#211: GPT-5.5, ChatGPT Workspace Agents, The Messy Reality of Agents & Google Cloud Next

0:00It's so hard to predict what is worth investing time into anyway in AI because a year ago someone would have been like go build all your own agents and you might have done really well with that but then OpenAI comes out with this and you're like why did I waste any of this time? Welcome to the Artificial Intelligence Show, the podcast that helps your business grow smarter by making AI approachable and actionable. My name is Paul Reitzer. 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

0:30Chief 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 211 of the Artificial Intelligence Show. I'm your host Paul Reitzer along with my co-host Mike Kaput. We are recording at an unusual time this week. It is Friday, April 24th, two o'clock Eastern time. We normally record on Mondays. I feel like I went

1:06through this already this week explaining a weird time which I probably did. That was probably this Monday. So normally we record on Mondays but Mike and I are both traveling on Monday the 27th I guess that would be. Yes. And despite our best efforts to coordinate schedules to do this on our usual time it was not happening. So here we are on a Friday afternoon. Bear with us because I think both Mike and I have had a week like it's just we were just saying before we jumped on like I don't know you man but I'm just mentally fried right now. A hundred percent. And it doesn't help that we get new models

1:41agents everywhere like a lot going on. So we certainly weren't going to skip this week. There was way too much happening to not do it. But we have a lot to talk about with a new model from OpenAI, new DeepSeek model. Everybody's rolling out something to do with agents this week. So we will do our best as always to cover it and give you the best analysis we can to make it make sense and actionable for you. So today's episode is brought to us by MAKON, the Marketing Ag Conference, now in its seventh year which Mike is hard to

2:13believe. We launched this conference back in 2019 believe it or not. So this is our seventh year. It's going to be October 13th to the 15th in Cleveland, Ohio. That is our home. That's why we've always held it in Cleveland. It's an amazing place to run an event but it is our home base. That's why you know I do get asked sometimes why is it MAKON in Cleveland? That's why. It's our it's our hometown and we wanted to build something that meant something to our local community and economy. And so we thought if we could build an event that would draw thousands of people why not do it you know somewhere that mattered to

2:44us. So that's why it's in Cleveland in case you're ever curious. The conference is bringing together more than 2,500 marketers and business leaders focused on one thing how to actually make AI work inside your organization. We've already announced two keynotes worth the trip alone just this week. I'm extremely excited about both of these. Karen Howe, the author of Empire of AI is back. She was actually our very first keynote in 2019 and she's returning with a deeper story how ideology money and power shaped open AI and why it matters to every business leader right now.

3:16Funny quick backstory Mike you'll probably remember this but when I did the MAKON in 2019 and I was trying to create the agenda for it I had read an article by Karen at the time she was working at MIT Tech Review and she'd written an article called what is AI and it was this super simple beautiful visualization of like what is and is not AI and I reached out to her at the time and I said Karen have you ever done this as a talk because I need this talk at MAKON it's like a great introduction and she had not but she turned it into a talk for us and so back in 2019 before Karen you know blew up

3:50and become this best-selling author and yeah I think she went at the Wall Street Journal um you know at the time and she's just an amazing person amazing author amazing researcher and so she came and did that that talk then and then she led a panel for us on ethics actually on AI and ethics back in the time and so I've been trying to get her to come back ever since and and the stars aligned this year where she was actually going to be in the country um for a few week period and we were able to get her to agree to come back so I'm I'm extremely excited about that one and then Dan Slagan also returned Dan was with us in 2024 he was on the main stage um at the time he was the chief

4:28marketing officer of tomorrow.io put on an amazing talk he's now a senior vice president of marketing at Zapier so he's going to be back with a extremely practical grounded view on what's going on we've talked a little bit recently about some of the things Zapier is doing especially on their like AI literacy and you know how they're infusing it into their own employees and workforce so um Dan's going to have a great story to tell I think we're still trying to figure out like which story to tell you know because there's so many angles he could go with so Dan will be back um and new speakers can be added every week we have a couple other really big keynotes we're working on right now so uh stay

5:03tuned but macon.ai it's m-a-i-c-o-n dot a-i and you can use pod 100 to save 100 off current current rates I think the rates go up every 30 days or so so you know get in early get your tickets early and you can save hundreds of dollars and then use that pod 100 so again it's macon m-a-i-c-o-n dot a-i all right Mike uh AI pulse survey so if you're new to the podcast every week we go through a we put up a pulse survey and our listeners can go through and answer two quick questions it takes about 30 seconds

5:34um so it's smarterx.ai forward slash pulse we'll tell you this week's uh pulse questions at the end of the episode today but on last week's episode on uh 210 we asked is AI driven search chat gpt claude google AI mode starting to affect your website's traffic yet um 43 said don't track it 26 said not yet but watching 23 said some impact and then major impact or clear decline was a small percentage might yeah I don't know what that is like less than 10 percent yeah um and then the second question was

6:08are AI agents genuinely starting to change how your team works or is it still mostly chat based AI so by far biggest percentage 53 said still mostly chat 30 said early experiments only 13 said agents are real for us um and then no AI yet is a very small sliver yeah um that one's going to become more relevant today's conversation mike because today is all about agents all right so let's get it kicked

6:40off though because we did have a new major model release from open AI yes paul so open AI launched gpt 5.5 this past week they call it a quote new class of intelligence for real work empowering agents built to understand complex goals use tools check its work and carry more tasks through to completion it is open AI's first fully retrained base model since gpt 4.5 and the first API model from the company to ship with a 1 million token context window so pricing comes in at $5 per 1 million input tokens

7:1630 bucks per 1 million output tokens that roughly double gpt 5.4 there's a gpt 5.5 pro variant at $30 per 1 million input $180 per 1 million output on a bunch of benchmarks gpt 5.5 took the top spot on the artificial analysis intelligence index with it has a score of 60 which is three points ahead of cloud opus 4.7 and gemini 3.1 pro preview it leads the browse comp uh benchmark at 90.1 percent

7:47frontier math tier 1 through 3 at 52.4 percent and it also posts an 84.9 percent on their gpt val benchmark which is measuring how ai is good how good it is at doing real work sam altman framed this release as saying hey we believe in iterative deployment although gpt 5.5 is already a smart model we expect rapid improvements there were a couple people also reported after having early access some of the results they were getting so aaron levy we've talked about a bunch ceo of box said the model saw a 10 percentage

8:22point jump in accuracy on their most complex knowledge work evals uh the lovable team the the vibe coding uh tool lovable they reported a 23 reduction in tool calls per request i called it the most capable model for people taking on complex builds with technical depth so paul a lot of stuff we can kind of unpack here um just kind of curious about your broader thoughts here i mean just again another new model but there was a big emphasis open ai stated just outright about agentic coding computer use knowledge work

8:55and early scientific research they said those were areas where these gains of the model were especially strong and i don't know if you could more succinctly put like a series of trends of like exactly where ai seems to be going we've talked a lot recently about opening i refocusing you know they you know cutting the sora app um they're thinking about robotics but not heavily invested in it quite yet they dropped the idea of having like a social network so they're doing their best to try and refocus i think in large

9:26part due to the success of claude you know if we go back to the start of the year um not only did claude all a sudden start getting a lot of headlines and a lot of attention for the quality of its work um not only in coding though but in in knowledge work like and we talked about it so much on this show mike of the ways we've been using claude and it just seems to have been um post-trained really well to do knowledge work to do strategy documents and research papers and um and and so open ai has been watching anthropic making gains and seeing their revenue skyrocketing and a lot of it's coming from their work

9:59with enterprises and i'll share a little bit more about you know my last couple weeks but you know i was at the google next event this week and every person i talked to was using claude i mean they have co-pilot licenses they have gemini licenses but i didn't talk to anybody that wasn't at least experimenting with claude as well and in some of the cases i was talking to massive like fortune 50 enterprise leaders in some cases who are in charge of ai within their organizations um and they're giving people claude access on top of everything else so like open ai seeing this

10:32they're hearing this it's why they're they're having to not only like do all these deals with the consulting firms but um they have to focus on the real work and so when you read the post that they put out about this release it's it's very obvious as you said like where they're going so it said we're releasing gpt 5.5 our smartest and most intuitive to use model yet and the next step toward a new way of getting work done on a computer gpt 5.5 understands what you're trying to do faster and can carry more of the work itself it excels at writing and deduct debugging code

11:04researching online analyzing data creating documents and spreadsheets operating software and moving across tools until a task is finished instead of carefully managing every step you give gpt 5.5 a messy multi-part task and trust it to plan use tools check its work navigate through ambiguity and keep going now we're going to talk a lot about agents on this episode but this is the kind of stuff people have been using codex and claude code for and things like that um and gemini but the that what they're saying is the average knowledge worker wasn't seeing those same capabilities you had

11:39to be a developer you had to be a technical person to get those capabilities which is what we've been stressing on the show is that these like claude co-work open call these things that they're great for developers like you have to be technically minded we're trying to talk to the people who are outside of that world who are trying to just go in and build an agent and then they get into like an anti-gravity like what the hell do i do with this like it it's not intuitive so we're um opening eyes obviously going here is moving in that direction of bringing those coding capabilities in a more reliable secure way right into the platform that the average knowledge worker would use

12:14so they continued they said the gains are especially strong in agent decoding computer use knowledge work and early scientific research because the model is better at understanding intent it can move more naturally through the full loop of knowledge work finding information understanding what matters using tools checking the output and turning raw material into something useful and then just some quick context here mike i listened to this core memory uh podcast with ashley vance which i think it's a new podcast um and if i'm not mistaken it was a gated podcast like you couldn't get it and then uh

12:47someone had proposed like well why don't you raise money or something and and and make it open and someone paid a hundred thousand dollars to unlock this podcast and so just this episode so it was with sam altman and greg brockman so um ashley vance sat down with the two of them and i think it was the first time they've ever actually done an interview together so on my flight back from vegas on wednesday i listened to this and i'll just highlight a couple things because this came out as a prelude to 5.5 but sam and greg were obviously talking about some of the things they were doing so sam um talked a

13:21lot about the tech but said they haven't connect the dots enough on what the abundant future will look like i thought this was fascinating because an episode or two ago i was saying how there was a pr problem in the industry yeah and how they were all talking about this abundance and yet no one understood what that meant so i was fascinated to hear sam basically echo exactly what i was saying and he was like we're not doing a good enough job as an industry making it tangible for people what this amazing future is that we're envisioning um he also said they're not far away from a model that knows the complete complex uh uh complexity and context of your life and this is the memory

13:58component and i think this is a really important thing for people to understand and so when you're using 5.5 you're they're obviously starting to rely more on memory but they're also relying more on the fact that the memory is just going to get better and so when you have models like 5.5 and eventually six um that have full context through memory and they also like are able to continually learn which i'll talk a little bit more about in a minute the need for prompting in the ways we've

14:28become adept at prompting goes out the window like you you don't need to do context and interview me and all these things that have become standard ways of prompting because it knows everything already and so prompting literally just becomes hey do that report for me that you know i have to do on sunday nights and it's like okay i mean it just goes and does the thing um and then greg along those lines talked about personal agi which is the first time i think i've heard him talk about it in this terms so what they're saying is rather than like a universal agi as this model and then you know

15:02the next generation models come out it starts to know you so well that it feels like general intelligence to you because it does have this full context and memory and ability to learn from what you're doing and so i'm in that um vein they talked a lot about this idea of still this jagged intelligence that we still are on this age where sometimes these things feel superhuman and then like it gets hung up on a stupid thing and you're like oh it's no smarter than a preschooler when it comes to this thing but it's superhuman at this other stuff and then they just really talked a ton about

15:33agents so greg said at the moment they're at the transition agents agents are going to do all the work they they specifically highlighted context computer use and memory as the core components they want to bring codex the coding capabilities of codex to everyone and that's what i think we're going to start to see we'll talk about the the agents from specifically for this new workspace agents in a moment um they want personal ai that is not only feels like agi but it's proactive it actually anticipates what your needs are going to be and it does things in the background for you and surfaces

16:03things like hey you asked for this last week i went ahead and ran this for you like that kind of stuff so the interviews worth listening to um it's nothing groundbreaking like i was expecting with the two of them together they were going to talk about a whole bunch of things they'd never talked about but they did get into sort of the evolution of the relationship the evolution of greg's role and what he's doing moving forward and then they did talk a little bit about the elon musk lawsuit and how how painful it was for both of them personally and one because greg's personal journals got like

16:35yeah you know put in as evidence so like real personal stuff was out there um but sam did say at the end that his biggest fear right now is that elon's gonna drop the lawsuit like the day before it starts because sam's like we went through the hell basically for this like i want it all out there now like all of our lives have been put out for everybody let's have this trial and let's hear let everybody hear what really happened so ish i could totally see elon dropping the lawsuit just messed with them enough to like make their lives miserable and then like ask for it um but if this goes to trial man

17:08it's gonna get it's gonna get messy and make for some pretty interesting conversations yeah i bet greg brockman is regretting keeping a journal at this point yeah he he kind of glossed over it as like it is what it is but it's i mean no one wants their personal thoughts out there no like this all right so our next big topic this week open ai has launched workspace agents in chat gpt this past week so the company kind of calls these an evolution of custom gpts and positions them as

17:39shared agents that can handle complex tasks and long-running workloads across tools and teams so teams build an agent once essentially and use it together inside chat gpt or slack at the moment with the agent improving over time now agents are being powered here by codecs running in the cloud so they keep working even when the user is offline they can run on a schedule or they can be deployed directly into slack channels to pick up requests as they come in open ai is shipping pre-built

18:09templates here for finance sales and marketing agents with out-of-the-box connections to things like slack google drive microsoft apps salesforce and more the availability of these is a research preview right now for chat gpt business enterprise edu and teacher plans with a gradual rollout across business and enterprise over the next several weeks the feature is off by default for enterprise workspaces pending admin enablement and the pricing appears to be free for the next couple weeks

18:39after which they shift to kind of a credit-based model but they're still not have not yet disclosed kind of the rates and things here on the governance side open ai is shipping with these role-based admin controls over who can create and share the agents there's required human approval for sensitive actions like sending communications or modifying records and a compliant api that exposes every agent's configuration and runs and safeguards as well against prompt injection attacks so paul i know this is something you and i have been talking about quite a bit this week you've done a little like

19:13uh initial experimentation with this um any thoughts like how big a deal is this i so this is one of those things where you initially look at like this might be a really big deal um and i'll i'll give some brief context so i was as i mentioned i was at google next this week and it was all about agents like literally everything every talk um from the leaders of google about agents yeah and one of the things they previewed was this agent designer and then i actually sat in a master class where you could build agents with this agent designer and i was like this is slick like this is really cool direction

19:47unfortunately it's not available like i don't know when it's coming but sometime later i think it's in some sort of a research preview mode so almost everything that google showed was for developers so it's like vertex ai anti-gravity things like that and you need some elements of technical capabilities and you probably need it involved so i was like oh like just that this is cool oh wait i'm disappointed again and then that same day uh open ai announces these agents as does microsoft announce their agents so we'll get to that in a minute so i see the chat gpt one and i'm like

20:22oh my gosh that's that's amazing is that actually available like can we get this so i go into my chat gpt account and sure enough there there it is and i was like awesome and so you just click on like so again i'm i'm in our um team account for chat gpt and i just click an agents it's in the left column and then i can click browse agents and i can do browse templates and you immediately get a sense of what's what's possible now um it shows there's also recent uses so you can look and see that you can see a built by me agents and the smarter x directory in our case so if you've ever gone into

20:56the custom gpts area it's kind of like that but for agents i would say like it's the easiest way to kind of envision how this works but the beauty here is they have these pre-built templates and i'll just read three of them quickly to you because it gives you a sense of what what's going to be possible so they have a template and you can start with a template or you can create your own by just using words like hey i want a keynote abstract writer so they have a chief of staff and this is how they describe it prepare a high signal operating brief for from schedule inbox and team chat context great for users who want sharper priorities meeting prep to do capture source

21:30link follow-up guidance and requested email or chat follow through in one concise daily artifact and then you can connect it to google and microsoft calendars microsoft email and teams and slack they have a data analysis one that's a again a custom or a template agent a data analysis plugin arranged around the life of an analyst rather than a tool checklist use it to sharpen the question write and improve sqls inspect the shape of a data set beard build clear visuals prototype dashboards and run a final quality pass so basically just teach it skills that are specific to what that person

22:03would do in this case the agent and then one other one sales assistant agent use generalized sales workflows for account intelligence competitive research value engineering meeting prep follow-up pipeline planning seller coaching great for teams who want stronger prep clearer strategy and better execution across the deal cycle and then it shows you a bunch of bunch of capabilities and i'll actually do one more um customer support agent so there's a generalized customer support workflow for ticket triage case investigation response drafting escalations customer research and knowledge

22:34creation so now with each of these you can connect it to things so i just picked these because every one of those if we connect it to hubspot completely changes our workflows and potentially our staffing plans yeah so if these things actually work in a reliable environment that i as a ceo am okay with us experimenting with it it completely evolves the way i think about how we're going to do our hiring this year and how we're going to analyze it and the thing i keep coming back to is this need for

23:04to to somewhat centralize we'll talk a little bit more about this in the next topic too with this agent usage but this idea of like centralizing the building of these things and so what i did is on the flight back i messaged mike and jeremy on our team and i put a calendar invite for next week and i was like we're just going to run a lab on this like kind of like a hackathon lab and like let's just take an hour together and figure out what these things can do yeah and so jeremy and our team's looking into the connectors and trying to make sure we're you know good from from a perspective like a safety perspective to do these things and then we'll we'll actually do this like we'll spend an hour

23:37next friday like hacking together and like let's let's pick a couple of these agents let's build something and see what happens um and it again like i i don't want to overstate this but if these things actually work like this goes back to when we first got like some form of workspace studio agents in google and then it was it's like they're fine but they really are just this is a few months back for like automating email stuff and like some calendar things but it's okay they're just like rules based things though it's nothing too crazy this is a different level this is truly doing the

24:09work and you know the ability to build agents for each role in the company um it really just starts to change how i think about this because it's so easy to do like you could literally train anybody to do this even even somebody who's like has been hesitant to do anything with ai yeah we could run an intro to ai 30 minute class here's what it is here's how it works here's what agents do and like let's build an agent for you in real time and you can just do these things in these lab environments so i don't know like i you know until we actually do this next friday mike and until we have time to like

24:42play around i don't want to you know say this is transformative per se but it has all the signs of being a very important thing and then microsoft did the same thing google with this agent designer is going to do the same thing like it's pretty clear that by fall of this year if not sooner depending on which platform you're on they're all going to enable a knowledge worker a non-technical knowledge worker to build agents and run them yeah okay you know it's really interesting to read through

25:14the announcement about these and start playing with them because what really occurred to me is it was a subtly important point to read that it's powered by codex because if you're on if you're one of these more non-technical user which i am one um if you haven't used codex or clawed code this is why people are freaking out about those tools because it's a preview essentially in a different modality and not exactly the same as these agents but they basically do the same types of things for non-coding tasks they

25:46do agentic work using files code tools and memory skills to do skills to do way more than you can do with a prompt or just a chat so i think people are about to wake up to what's possible here and just to kind of connect the dots like this is why we keep harping on about these tools because the game changes when you go beyond just chat i think yeah and it it changes many things and um organizational design like i said and yeah yeah it's again i don't i don't want to oversell it but i i said

26:21you know if you go back to episode 141 and even go back to episode 87 prior to that my projection was that ai agent explosion would happen 2025 2026 would be the starting point of it and then that would continue on and by 2027 we would completely transform work with agents so this is something we've been known was coming for multiple years we've been talking about this um and i i feel like we are we are clearly in the very early stages of not just the agentic capabilities for the technical

26:53people and for development work but now bringing that to knowledge work to make it as simple as building a gpt which leads me to like the usage and stuff because yeah there's so many people have never built a gpt so like even that is is advanced for most average users of this technology i want everyone to keep this discussion in mind as we get into this next topic because you know paul we've been you and i have been talking quite a bit informally this week about

27:24um agents at large and how you actually deploy them inside a real business today so a couple updates that came out and we're going to kind of get into what this discussion about agents has looked like for us personally over the last couple weeks but first up some things that kind of spurred this discussion so first we saw jason lemkin at of saster owns and runs saster posted a pretty widely shared take this past week about their use of agents in how they run that event and some really interesting stuff on podcasts and on posts online where he's basically talking about using all these

27:57specialized ai agents to essentially run different parts of the company they use artisan for outbound qualified for inbound agent force for reactivation they use agents for new customer acquisition at the same time microsoft also like you had mentioned made co-pilots agentic capabilities available generally across apps and co-pilot um and also we talked about just how open ai is rolling out workspace agents google is hyping up agents at google next which we'll talk about but these land in

28:29the middle of this bigger conversation you and i have been having about kind of where we're at on all this and the open questions around ai agents because there's like no shortage of voices we hear from them out there asking these like some version of the question why aren't you all on it all in on agents like why aren't you doing every possible thing you can with agents right now and paul i don't know correct me if i'm wrong we're not anti-agent i feel like they're 100 the future and we're actively experimenting with general purpose things agents like clawed code and codex we have not gone all

29:03in yet on things like open claw but there's always like really important open questions and nuance and i feel like people are just shoving under the rug here about like what is actual production usage look like what about security what are the specific use cases that actually matter for a business and the usage question you just alluded to like how do we price the usage of these things so paul let's just like get into this like where do you want to start here we've talked about this thing yeah so i mean really what happened is i got back late wednesday night um i'd already put this lab

29:36meeting on the calendar for mike and jeremy and i and i hadn't had a chance to actually play with the agents yet and so i got in the office thursday morning and i was like all right let me just jump in chat gpt real quick so i jump in and i'm like browsing these templates and looking at it the connections like oh my god like this this might be it this might be what we've been waiting for and then mike came in the office and i was like dude look at this showing him these sample agents and these templates and so again coming fresh off of google next i like all of this is fresh in my

30:08mind because um i met with some really interesting people and it's just that random like how you know sitting next to somebody at lunch randomly or the person you're sitting next to like the keynote and you just you have these conversations and these are you know you might randomly run into like a person who's heading up gen ai adoption managing token budgets at these major companies yeah and you're like well what are you doing like what like what's happening at this company what's going on with your developers what's going on with like marketing sales and customer success like how real is this stuff within enterprises so these are the kinds of conversations i'll allude to often on the

30:41podcast like we're talking to the real people like and there's this balance between developers who are hardcore pushing the frontiers of everything that's possible seeing into the future a future that no enterprise is going to touch for a while like they aren't going to do those things and so when we're talking about this stuff on the show we're trying to talk to the the practitioners and the business leaders who are the non-technical people often who have to actually figure out what does this really

31:13mean they're trying to solve for what are the token budgets we're giving our developers and you know some people are like oh let's just do token maxing like burn all the tokens you want and then i talk to somebody who's in charge of tokens and they're like burning through like our whole monthly budget in two days like how are we supposed to budget for that and they're going back to these vendors being like we can't do this this isn't a sustainable way to handle this then there's like the vendor selection do we go all in with anthropic or do like well there's chat gbt 5.5 like is that a

31:43good model should we be using that or is this new agent designer from google gonna be the thing and should we just put all of our eggs in one basket with google so these are tough choices the pricing models getting back to the the token budget like i've been transparent before about this i just went into hubspot today and we're like we're already out of credits i'm like how the hell did you run out of credits already that it's like three days old is the billing cycle like what what did we do to run out of credits and i actually like went in and i'm like trying to audit where did the credits go like what are they being used for and it makes no sense and so i'm just like god this is so frustrating

32:16and then you mentioned risks the other thing um we'll hear about and and the saster episodes are amazing by the way we'll put the link into it they're just like here's what we're doing we're using 20 ages for this whenever for that and you start to realize that when you actually are on the frontier trying to innovate with these agents within a real business how the hell do you govern them like okay now there's 20 agents running loose that have access to all these different connectors and these people have the freedom to just go get more whenever they want and mike can go get this subscription jeremy can get that's and so like now you actually have

32:49to manage these things and these agents they function off of knowledge bases they function off of skills those things get outdated like how are you managing those and updating them is that in a google sheet like where are we doing all this stuff and then at google next i watched a um a demo from the co-founder of of wiz the recent acquisition for uh for google cloud and he was showing how they're actually managing the risk of these agents and it was it was beautiful like it was incredible to watch

33:20but also makes you how makes you aware of how unprepared most people are for everything that goes into running and governing these agents as they get access to more and more data um so yeah i don't know i just keep coming back to like i love these practical use cases like saster is doing inspiring stuff like it's really cool to hear these stories and in a real business that's like our business i mean run events it's like it's close to home for me and i listen to what they're doing it's like oh that's a pretty cool idea but you also listen to them and they're being totally transparent about the fact

33:53that they're just figuring this all out because they'll build something in repli and then like they launch it and then it breaks and they're like what do we do now like how do we fix this like we have no idea what's even happening um and then they're going and talking to claude and being like what what broke like how do you because they're not the people who would usually take those things to production and that's another element of this agent stuff it's like we're being empowered to build these things but like i don't know how to take things to production and i don't know like how to deal with it if something breaks so i don't know yeah it's like we could literally go any direction

34:27with this but those are just some of my thoughts for the week having spent the week seeing agents being debuted hearing them talked about and then talking with real leaders at massive enterprises who are

34:43they're nowhere near prepared to to do this stuff with agents like outside of their developers and even then it's like it's like a free-for-all and they have no idea how to manage the tokens and which vendors to use and so yeah i don't know it's it it is the wild west right now but the people are figuring it out or getting a really fast event competitive advantage yeah and you know i wrote down kind of as we were preparing just a few big unanswered questions i have about agents or let's call them at least not sufficiently answered i'm

35:15gonna share them really quick just in case they're hopeful to people but like first is really how can i more clearly think about different let's call them types of agents because like in a practical sense the more i learn the more there's not just one type of agent really like quad code runs agents to do things in real time with periodic guidance partnership hand-holding from humans but that's like materially different in practice from something like open claw which can do similar stuff but does so persistently

35:49and autonomously and i don't necessarily think one is better or worse it's just that like when i think about this it's already nuanced that people aren't addressing where i'm like no it's not just like ai agents it's like these are two at least very distinct paths today and i'm sure there's others in here i'm missing but like i think there's more nuances like just because i'm not using open claw yet or like a 24 7 persistent agent i don't think necessarily means you're at a disadvantage it just totally depends on the use case right so i think about that a lot and i'm still kind of trying to work that out on my

36:20own i often also i'm thinking like what are the actual use cases for always on agents like open claw that sounds really obvious to say i could rattle off 20 different ways you use these and keep in mind again reference the previous segment i am not bearish on these i think this is the future but there's the real consideration like if i have to worry about this thing all the time if i have to manage it all the time or try to troubleshoot it if it breaks regularly how is it remotely worth it for me to spend time on this versus something like shouldn't i just be building out even better

36:54and more expansive skills for quad code or building the workspace agents in chat gpt i don't know the answer here but like that's a real consideration for me and then finally you just hit on this like how in the hell do you pay for 24 7 persistent agents i feel like there was this like honeymoon period because i think until really recently you could just plug open claw or something into your clawed max account right and use it that way so like you didn't have to just pay via api i don't think

37:25and you can't do that anymore they like turned it off so how on earth am i going to spin up like a 500 a month agent to like do my grocery lift i'm not thinking across that much but i have no idea that's the point it could cost five cents it could cost five thousand dollars a month i genuinely have no idea how to gauge this and that's just like a personal experimentation like how in the heck do you figure this out as a business like how would you i mean like that's what you're getting at right is like there's no predictability here you can't budget for them right well they've already shown in the

37:56last six months they're going to keep changing the pricing models so then you know and i'm not saying they're going to do this in a deceitful way but the way this traditionally works in business is you get somebody hooked and then you jack up the price yes so you know let's say for us we go next week on friday we're like oh my god these agents are incredible and then we build a team internally that basically goes department by department and looks at workflows and problems and goals and rocks and says okay we're going to centralize the building of agents because it's going to be too complicated we have everybody doing their own thing and let's get this small team together we go

38:28through or prioritize these things we start tackling a couple workflows couple problems at a time you build a bunch of agents they're crushing it they're part of our twenty dollar a month per person plan and then all of a sudden they're not right now their hubspot's model where we're like burning credits and i have no idea where the credits are going yeah and to your point like maybe it's now five thousand a month instead of three hundred a month but now i'm hooked like now these things are built into our workflows so and maybe they don't change it in two months maybe it's in a year when they figure this out um and it goes back to that pricing and i think i you know i'd said this

39:02to you yesterday morning mike i'm like i i don't get how this isn't eventually a human replacement cost thing like it it just seems like if there was a a simple way for the labs to calculate the value of their own technology which i don't think they're currently capable of doing um they would just charge more for it so like for example if i go into these agents next week and i figure out like wow we can actually build like a customer success assistant that's going to do these things each week each

39:37month and if i had to hire someone to do that that would be like a hundred hours of work that's a full time hire that this agent's basically going to do that work and now let's go do the same thing for sales like we'll build an sdr agent and it's just going to basically do what an sdr would have done um or like an event market or whatever like if we figure out a way to actually do it then i like i would happily pay like if i knew as the ceo that that agent i just built or a collection of agents

40:07working together is doing the work of three people and opening i came to me and said hey like built these agents like you know the value of that would be 300 000 a year um we're going to charge you 3 000 a month instead of 20 bucks a month i'd be like yeah all right let's go like okay okay and so i feel like for for finance to truly get involved and manage this process as these agents become more prevalent within organizations i i can't imagine how a token or credit based budget where they're you're

40:40constantly running into a limit is is in all possible or scalable for anybody and i i keep coming back to it has to be simple it has to be clear it has to be understandable um i'm paying x a month you're i'm getting use of these things and i don't know if it's just like you know these models get 10x cheaper each year and so maybe it's at some point over time maybe well yeah maybe at some point you're just like 5.5 is good enough like these agents crush it i don't need gpt7 and i know

41:16that it's going to cost you the lab 10x less to serve me this model in 12 months so yeah just keep let me stay on the old model i don't know or or maybe that's where the open source stuff comes in it's like once we have an open source model that's good enough like the deep seek the numbers on deep seek are that it's basically like on par with some of these frontier models right and so does it go back to the open source does it swing back where you're like yeah i'm happy with fifth generation models like i don't i don't need i don't know and i don't i truly don't think the labs know because

41:48they've focused so much on building for developers that are cool with the token maxing model and we're just going to pay for our tokens because they're used to that approach and i don't think they've yet solved for how to charge the way sas traditionally would have like what is the evolution of a seat-based license um yeah and then yeah then you're like hubspot and you're like okay i'm just going to build these agents and i'm just going to connect them over to hubspot so i actually i'm going to get rid of a bunch of my seats because i don't i don't need any more and i can just access it through chat gpt

42:19yeah there's a lot more nuance to it than just go use agents yeah yeah and i think like sometimes you get pushback on you know the not trying to belittle the the capabilities of the agents or not give them enough significance i just think sometimes people don't have the nuance of what really happens in an enterprise and like how complex this is and that's we spend our time talking to these companies all the time who can't even get co-pilot rolled out or nobody's ever been trained how to build even build a

42:51gpt or analyze a workflow and figure out where ai can fit into it it's so messy when you actually get into the real stories of adoption it's easy to um you know just see the technology and think oh my god everybody should be doing this and it's like no they shouldn't it's not it's not ready for prime time yet but if you can embed codex and you know clawed code right into the user interface that the average knowledge worker can use them it changes everything oh yeah and to your point you mentioned to me in the office is like even on the gpt front it's like very few enterprises have fully explored

43:27what is possible simply with gpts or simply even with connecting standard chat to valid useful data sources right so it's like there's so much value to be accrued and and created there it's like i'm not saying you don't need agents and that's for sure where we're going but why why does it just have to be that this is also a path where i think it's overlooked because we're all you know in the twitter or x a high bubble right yeah where everyone's like oh my gosh i'm running my entire

43:57company with agents which is amazing like i'm sure some people are doing that but the vast majority of people are not remotely close to that if you're an ai native company and you can do that from the ground up you can take those risks go for it yeah that's not the reality for the vast majority of companies these these ones that we want ai emergent they're trying to figure out how to work within legacy systems legacy talent legacy governance structures um highly regulated industries like it's not the it's not reality well yeah i mean i won't harp on this but just one more consideration it's like

44:29you know it's so hard to predict what is worth investing time into anyway in ai because a year ago someone would have been like go build all your own agents and you might have done really well with that but then open ai comes out with this and you're like why did i waste any of this time also the architecture behind something like rag and things like that i don't want to get over my skis on the technical stuff like some of these methods are like totally out of date now so i should have spent six months figuring this out when i should have really just been probably building vpts or skills or something and then they flip the switch and i can just click a few buttons and make an agent in chad gpt it's a

45:03very hard i'm not saying like that's the right path but it's really hard to predict like should you just actually wait until it becomes a little easier to do right right all right paul so before we get into rapid fire one more announcement for this week this week's episode is also brought to us by ai academy by smarter x which helps individuals and businesses accelerate their ai literacy and transformation through personalized learning journeys and our ai powered learning platform we add new educational content weekly so you will always stay up to date with the latest ai trends and technologies

45:37and we wanted to spotlight this week our ai for departments collection which right now features six course series and certificates designed to jumpstart ai understanding and adoption across departments right now we've got marketing sales customer success hr finance operations i just actually wrapped up paul ai for a legal this past week so i believe that would be coming out next week don't quote me on that but very soon we'll have that done um these are the ideal launch pad for organizations that want to level up their teams and accelerate ai adoption and impact

46:12i'm actually going to share a little later in the episode a few quick insights from the ai for hr series which i taught just as a note individual and business account plans are available now you can also buy single courses and series for one-time fees so go to academy.smarterx.ai to learn more

46:31okay paul first rapid fire this past week you were at google cloud next 26 in las vegas that event wrapped up their headline announcement was gemini enterprise agent platform this kind of full enterprise stack for building scaling governing and optimizing ai agents that basically effectively absorbs and replaces vertex ai going forward this bundles a few things like a low code agent studio an upgraded agent development kit agent runtime a persistent memory bank and some governance tools it also has

47:05access to 200 plus models including gemini 3.1 gemma 4 and also outside models in there i think what's that i think you can get it yes you can cloud as well it's in there um and then tech crunch actually framed the platform as google's response to things like amazon bedrock agent core microsoft foundry um they have a bunch of launch customers using this uh they paired the platform with a refreshed gemini enterprise app uh they made a 750 million dollar commitment to their 120 000 partner network to

47:38accelerate agentic ai deployments there's also a new agent marketplace so paul you were at the event what was your read on what google announced i mean it seems i think agent is safe to say probably the word of the year here at this point that's for sure yeah so i'm part of the google cloud leader circle so you get um it's like an invite only thing and and so i get a day with like google's leaders and so that was tuesday i got to sit through some pretty amazing talks including the opening talk from thomas curian

48:10the the ceo of google cloud um and it was very apparent from the jump that they're they're all like everything's agents so he said the goal is to make gemini enterprise the best place to run and manage agents and then uh in his opening keynote at google next he said bringing ai to every employee and every workflow was like the goal they were focused on um now the thing you always have to differentiate with google cloud is like again when they're talking to developers and when they're talking to the non-technical users and a lot of the things that they traditionally would announce is like focus

48:42more on that developer audience a lot of things they've built like vertex and anti-gravity they are not for your average user you really need technical capabilities to get into them um one of my favorite sessions at the leader circle event was google ai at google so they were basically had some of their key people who are working on ai transformation uh ai strategy at google talking about what they're doing so i'll highlight a couple of those real quick so ryan valk who's the vp of ai transformation talked about these lighthouse workflows and so he was saying they're basically trying to

49:13focus on moving from just tasks into the actual workflows and they want each business unit focused on two workflows so they're all about like prioritizing where the impact could be and i really like this concept it's something we've talked a little bit about ourselves internally you want to get past the cost savings focus on growth and innovation which you know i obviously love that thinking he talked about this analogy of going from fishing where you're throwing lots of lines in the water trying lots of use cases to farming where you're getting very strategic and deliberate and then um

49:44one of my favorite things the echoed that we say all the time is this idea of reimagining work so seeing significant changes and how teams work together they're starting to field experiments within ai native work labs which that might have stuck with me when i was thinking about doing this lab internally i don't know yeah um but he also talked about how it's so difficult right now to predict change and that the lines between roles are starting to blur we've talked a lot about that on the podcast how like as the ceo i all of a sudden have the ability to do people's jobs because i can just

50:14go in and like yeah use claw it it's like i'm getting annoyed something's not ready like oh i'll just do it tonight i'll do it myself and so they're seeing smaller teams emerging where these blurred roles are sort of allowed to blossom i guess it's like cool that everybody can kind of do each thing um there was also joshua spanier who's the vp of ai and marketing strategy at google he said there um even within google they were struggling to get everyone internally to use the technology which again is kind of counterintuitive to a lot of people but it's it's not if you've spent time with these labs

50:46themselves it's like they're just like us like they have marketers and sales people and cs people who doesn't mean just because you work at google that you're like ai forward necessarily so you're there to do your job so you know you talked a little bit about that and how they started a dedicated ai team that was actually in charge of like the contracts the data sets the tools the systems and so that team builds out a suite of tools that then is shared with teams to use so it goes back to the idea of chat gpt agents like maybe we just build agents and we we say hey sales team here's your three agents and

51:16here's cs team and that's a big question for me moving forward and i think for all of our listeners that we often think about is are we centralizing the building of ai capabilities and then like distributing them to teams or are we allowing everybody just sort of do their own thing they um he just said they relied less on individuals to figure things out they made a big investment in ad creative development and testing and they're seeing a massive impact on cost and performance and then he said something i thought was really interesting no one joins google and i wrote any or any company myself to to just be efficient like no one's goal in their job is to be as efficient as

51:50possible right so that's why they focus on trying to bring the creativity and innovation and then the one other note i'll share i was really excited about this one so jeff dean was the closing talk um uh at the leader's circle the first day and if you don't know jeff dean we've talked about him on the show many times he was the 30th employee at google he's actually the one who named gemini and the name came from the merging of uh google brain team and deep mind so it was like the sisters like the gemini um and he said that even then so again going back to this how mature are agents

52:25he said his words starting to see glimpses of the agent economy meaning we are still early he highlighted specifically the lack of reliability and trust agents that we should all have in agents right now for giving them access to credit card information filing systems all of these things so again we say this on the show but this is jeff dean an authority on the topic saying agents are early you have to be very cautious with them you have to be conscious of what you're giving them access too but they're getting really good and we're seeing glimpses of them making an impact and then

52:59on um breakthroughs for agi like how close are we again there's very few people in the world more qualified to actually talk intelligently about this topic he said he thinks we're still one to two major away which echoes what demis hasaba says and when talking about what does he think like that key is he alluded to that he thought continual learning was likely one of them now having listened to jeff and others for the last 15 years i've been studying ai um usually if they pick something it means

53:30that it's something they've been working on and they've made advancements on and continual learning to me i've said this many times over the last 12 months i think that that is the unlock that they most of these labs think if they can solve for continual learning that the model doesn't stop once it's comes out of its training that it actually learns like humans do from experience and inputs and outputs it constantly changes its own weights and it can get smarter and more capable that is that might be the final unlock and my guess is deep mind has made progress on this

54:04and i would imagine the other labs have as well it's also a very um complex thing to put into the world because it can lead to the fast takeoff concept that we're probably not prepared for so really cool stuff they do an amazing job at those events i mean google's just incredible um and google cloud puts on the leader circles great and then the event itself i was only able to stay for the first half of the first day of the actual next conference um but even that was you know awesome and then if i don't know i did uh so sarah kennedy who's a good friend of mine um she led a panel with uh sean

54:41white and bryson de chambeau sean white the olympian and bryson the golfer it was awesome like hearing those two guys talk about what they're doing with ai and their sports but just seeing them and and their personalities was really cool like bryson's kind of a one of those people like a lot of people like like to not like bryson when you sit there and listen like i don't know how you couldn't like the guy i mean it was it was a really cool story and i was i was like excited to kind of get to experience that that's awesome all right next up in less positive news uh a leaked internal memos

55:13past week revealed that meta is trying to basically install tracking software on their us employees computers uh to capture mouse movements clicks keystrokes occasional screenshots across a designated designated list of work apps and sites and the memo frames the rollout as a way to teach ai models to use computers by giving them real examples of how people actually use them and cto andrew bosworth described the end state as one where our agents primarily do the work and our role

55:44is to direct review and help them improve the memo assures staff the tool will not read or read files or attachments will not be used for performance evaluation and will not learn incidental personal information picked up from the screen there are reports that meta staff are protesting the rollout internally i wonder why um separately meta also it leaked and then meta had to announce it i believe that it is going to cut roughly about 10 of its workforce with layoffs beginning may 20th there are

56:15additional cuts expected in the second half of 2026 a big part of this is the cuts are part of their effort to run the company more efficiently and the chief people officer janelle gale told people that it was to allow us to offset the other investments we're making i would just like to without over speculating point to what other investments meta is making there's exactly one that is quite large and that is its capex guidance of 115 billion to 135 billion that is spending basically on ai infrastructure

56:49that is nearly double what it spent in 2025 so ai somewhat adjacently is probably responsible for some of this um so paul the current reason we're talking about this um be curious about your thoughts first on are they just basically trying to train agents to do what the humans are doing and then get rid of the humans also like what do you think of the cuts and layoffs due to the capex and investments they have to make to stay current cuts and laughs expected i would expect more not just

57:21them that's obvious and um that's going to continue the uh the monitoring of employees i'll i mean it's not confident so this isn't new i'll up to that yeah um so there's another social media company um i did a talk two years ago and after i explained computer vision and the ability for things to be recorded and then

57:54analyzed and using training data i actually had an employee from that it was a different social network company come up and be like is that why they've been recording everything i've been on my computer so and then she explained to me how they were using the data she thought but she wasn't aware that this was even possible so this isn't new um you know it's not surprising at all uh i i think that at some point you know you have to think about the kind of organizations you want to run and the kind

58:28of talent you want to recruit and and retain and yeah at some point the best talent is going to have choices to make about where they go to work and if you you know if you're cool going to work for a company that you know is tracking literally everything you do and likely using it to train your replacement um is that is that motivating like it goes back to that thing i just said about you know google and saying like hey listen we're not nobody comes to google to work to be efficient like

58:59it's not like nobody wants to go work to like watch an agent do their job like i'm picturing like an assembly line and i'm just sitting here like just eight hours a day i'm just watching it click around and do things and that doesn't sound like a fun career so i don't know like i get what they're doing i understand this is i mean it's meta like they're gonna be on the edge of this and they're gonna do things that a lot of people are gonna hate and they're gonna get bad pr about it and gonna have pissed off employees and that's the story of their history like they've always

59:31done things that were people felt were beyond the line of acceptability and they seem comfortable with that and it's just part of who they are um but i think every other company is gonna have to make these same choices because what they're doing is possible like if you want to do a consulting firm or an agency or you want to pick operations or hr or finance in your own company this tech exists like you can train them up and you can build agents based on what people do there there's a startup last year i forget the name of it this is what they did like this is they sold this technology

1:00:05to enable you to do this yeah so yeah if this is new to you sorry like this has been going on for a couple years and it's gonna get tons of funding from vcs to do this it's gonna get ton of tons of payments to consulting companies to implement this and they will absolutely use it to reduce their workforces like there's no other reason to do it so yeah i mean and i'm not even trying to be hard on meta here like this it's just the reality like and that's so much of the time when we're doing things like

1:00:35this or having these like more hard conversations about the reality we're just trying to share with people like what the reality is and if you're working for a company that's doing this there is no other reason either it's either performance or to to train on what you do for your job right um i can't think of a third thing that you would do for that why why else you would do it um

1:01:00yeah so i think it's just it's just a i guess an awareness thing and you got to know the kind of company you're working for and what their intentions are with ai and ideally you want to like understand the responsibly i principles and whether or not they're human-centered company um that's why i think it's important just for people to have levels of awareness and then educate other people about these things because our you know listeners to our show are more likely to get this stuff like that they already knew some of this yeah um but all your peers your family your friends they don't know this stuff and so sometimes it's just us trying to do our part to share it so that you know other

1:01:34people can go and educate people about it yeah and to be clear the intention behind this segment is not to pile on meta specifically because it's not anything new that companies monitor what their employees do on their work machines often that has happened well before ai i think what is just really fascinating to me is like oh this isn't just for security purposes anymore they're just coming out and saying there's another to your point there's one of two reasons either employees following guidelines

1:02:04or performing i.e are you doing work on your computer are you doing anything wrong on your computer which has existed for a decade now major enterprises but there's this new lane where it's like oh okay this is training data yes for exactly for computer use agents that gets really murky really quick and if i'm not mistaken there i don't think we covered this but i'm pretty sure two or three weeks ago elon musk like changed the terms of employees at xai and they had to agree to have everything oh really yeah it's like yeah yeah for this purpose like it's all about training data

1:02:37for grok and and that's the thing is like they're not even necessarily using this just for their own purposes they're using this to train their models yeah like so yeah the work they do so imagine if you can collect every interaction that your marketing team your sales team your cs team whatever and you also happen to be a company that trains ai models you don't have to go license that data because what's happening in other instances is the training labs like a scaling ai are paying lawyers and consultants to sit there and have their stuff done like so not for a company they work for but saying

1:03:12hey we'll pay you 500 an hour to like track everything you do on your computer for a few days and then they're taking that to then train the models to do that the job of those people um so yes that is the new thing to your point mike it's like performance tracking and monitoring usage on that's not new using it as training data and data to then replace those people is new yeah and i didn't even connect the dots until you just said it like this has to have alexander wang fingerprints all over it well they've been totally doing this exactly what this is what they were doing at scale

1:03:43you're right yeah okay well our next topic this week um we actually well i guess it was technically this week because we recorded on monday we covered apple ceo transition um at the end of the last episode because that had um broken right before we started recording yeah um that john turnus was going to succeed tim cook on september 1st of this year um in the days since a bit more has come out especially on that kind of ai angle of what apple's doing with ai so cook and turnus had in all hands

1:04:14at the steve jobs theater cook interestingly addressed some health rumors head-on he told employees hey i'm healthy energy's high plan to be in the role for a long time turnus teased an incredible roadmap ahead he said ai is going to create almost unlimited potential for the company according to bloomberg turnus has already overhauled the hardware engineering organization around what he calls a new ai platform designed to speed up product development and improve device quality on the same day as the ceo announcement apple promoted john johnny shruji shruji to a newly created chief

1:04:49hardware officer role combining hardware engineering and hardware technologies into one organization um cnbc read this free shuffle as kind of a sprint to build in-house chips for devices with apple doubling down on silicon for on-device ai obviously we've talked about a bunch apple's new and improved ai powered siri uh which has been delayed a couple times is now expected to debut at wwdc in june of this year um they have a multi-year deal now with google reportedly worth around a billion a year to power the new siri on gemini uh so cnbc is kind of framing this true uh

1:05:26transition as you know turnus facing this defining challenge which is obviously apple does more than just ai but his job is kind of fix the company's ai strategy it sounds like and paul obviously it's so early here yeah but given the new details like what is the kind of your initial read on do you think he's the right guy for the job to fix apple's ai problems um where do you see this going yeah time will tell but everything i've heard about him from following online is just extremely positive sounds like everybody's known he was going to be the guy he everybody's saying he's the right guy

1:05:58i watched a crazy clip where he was doing an interview about like the cinema does the cinema display like the thing you know his first major project there and uh he was talking about when he was at the i think it was at the manufacturer or whatever they were piecing it together and they had designed the screws in the back of the display that no one ever is going to see to have like 21 grooves in them it was like a very specific number and he actually like took the screw out took a magnifying glass and found that they had 30 grooves instead of 21 and made him redo it like it's just like they were trying to

1:06:29stress how like what a perfectionist like a steve jobs type product guy he is so it seems like that's what they're getting and like i said probably in the last episode i i think like if they weren't comfortable with the roadmap they have to execute it wouldn't be the time so they're obviously very comfortable here interestingly uh at google next thomas kirian when he was doing his opening keynote on the actual first day of the conference he did mention apple they just put the apple logo up and everybody's like cheering and then he just said about them being a preferred provider for their

1:07:02models and that was it like there's no big thing he didn't go into a ton of detail he talked a little bit about siri but it was basically like that partnership that we've talked about previously on the show so i don't know like again as a long time apple user fan uh i'm excited it seems like wall street's liked it so far i don't i mean i think their stock's been doing pretty well since the transition which isn't always a given when you have a ceo change sure right so yeah i don't know everything seems positive and i i hope i've said many many times like i just i love working siri i'd love apple intelligence to really be intelligent like i think it you know it's billions of users that

1:07:38would get to experience ai in an entirely new way and i think a very positive and exciting way if apple solves how to do it the right way on the iphones and all their devices you know airpods and watches and glasses and everything else they've got yeah i was gonna say a very longer term but people you know we we included have talked about apple's like fall from grace and ai but like they're also half a chance away from cracking the code on ai wearables they're like the best people that do it and if they do that it's like game over like it's a whole different ball game right

1:08:10the data they have is insane like i don't there's so many things apple does where you don't because they don't feature it they have to like find these things and i was i was analyzing

1:08:23steps the other day like i love the health app in apple it's incredible and i i track everything i've shared my personal story about my heart and how it like you know kind of found something with that um but they track like things like distance between steps like it just like and it's like how like it's all it's either in my watch or my phone that they're getting the data from and the fact that it has this kind of data and like you just realize the depth of data they can capture from these wearables or from the you know the phone in your pocket whatever it may be and then you start to imagine like my

1:08:57goodness like what could they do with that data yeah if they have the intelligence baked in so if you're i'm serious like if you've never done it before go into the health app and just click like show all data and just look at the metrics they have on you it's wild and then uh an experiment i did which worked somewhat well as uh then have claude code go build some things to connect to that data and then tell you some stuff about it which is interesting fascinating um it's a lot of trial and error involved not perfect you probably just get the same thing you have apple watch but it was a fascinating

1:09:29experiment apple watches and if you've ever had like it i was a watch guy before like i collected watches like nice watches i stopped because like i really the utility of wearing an apple watch every day i hate when i would not have the data for a couple hours like you know you put a nice watch on whoever to go do a keynote or something and it's like oh damn i don't have my heart rate while i was talking and like sometimes you want to see that it's like does my heart rate go up when i'm on stage like i'm curious so yeah i just i love that it's so good all right so next up we have our you know now regular

1:10:02segment we're doing on our ai use case spotlights here at smarter x where every week we're trying to give you a quick look under the hood at some real uses for ai that we're exploring building or deploying in our own work and sometimes in our own personal lives so paul i just have a really quick use case to share this week if you have anything to share we can kind of talk through that too yeah go for it so for me actually i stole this one the use case is not mine but i don't think the personal mind may steal it because it's actually from taylor rady our director of research who's

1:10:35taking the lead this year on smarter x's state of ai for business reports so typically we have done for five years in a row a state of marketing ai report through marketing ai institute and smarter x um where we've surveyed hundreds and then thousands of marketers and business leaders on ai adoption and usage this year we decided to really expand that out to all functions of a business so we've got we just closed the survey we have basically almost i think over 2100 responses the most we've ever had spanning every function industry and company size so we are knee

1:11:07deep in creating the actual report and it's really interesting because taylor is taking the lead on this this year i'm kind of overseeing some stuff and reviewing it but you know i think i had shared last year or maybe early yeah last year that you know the report alone used to take hundreds of hours to do all the manual data analysis writing um understanding synthesis that you know years and years ago in 2024 and 2025 i cut that down to probably a few dozen hours which felt like an incredible win

1:11:42taylor did the report in like a day this year and i've looked at it a cursory fashion and it's really good and we're obviously going through the fine-toothed comb with human oversight for this and there's human complexity and tone and right rewriting and rewriting and reworking but like she was able to cut this down another order of magnitude and how long it took and the cool thing is it wasn't just about time this year because you know in past years i've been like oh my god thankfully it didn't take me this long i gotta run to the next thing this year like me and taylor have

1:12:16spent a huge amount of awesome time spent going really deep on two things one how can we ask even smarter questions of the data and go further and deeper on this stuff to create an even better report so we're not say we're reallocating the time we're not actually netting out with less time here but it's going to be 10 times better but also as part of kind of building out our research function at smarter x like how can we blow the doors off activating this report both internally for sales customer success everyone else academy and externally across a ton of different channels which is

1:12:52an area we've historically struggled with because it takes so long to do all this stuff so really it is night and day even i was blown away last year by what the models could do especially gemini and claude with both data analysis and writing this year it doesn't even come close they just smoked what we were able to do last year and it's just jaw dropping i mean just continually reminded like i know this i see this every day but then something like this is just so cool to see how good this stuff has gotten and it's really cool because like recurring use cases compound we've done this every year now

1:13:24that we've been able to for several years like using ai for parts of this it just gets more and more every year and the results just compound and compound and compound and it's it's incredible to see so super excited about that we're releasing this um in a few weeks here so we'll have more on that um and more announcements around that but we're really excited yes uh i can't wait to see it for one and two as someone who has personally spent hundreds of hours in pivot tables building that report i love to hear the stories of how we are solving for making it more efficient oh and i will i will

1:13:58just note too at our ai for writers summit that is coming up uh in a couple weeks uh if you can market seven may seven so if you go to marketing ai institute.com go to events you can see there's a free registration option taylor is actually giving a talk about exactly how she did this super tactical you could learn you know step by step how you can do this for yourself too so go check that out that's awesome yeah let's do a quick one this is i actually i forgot i ran this it's funny um so sometimes i'll

1:14:28just go into like chat gpt and see what are the recent prompts i gave so apparently like i said i forgot i did it um i think it was the last night or this morning i had seen a jason calcanis uh maybe tweeted about like how we were gonna how all these like new companies created and that was gonna create all these jobs and but not everybody's really made out to be an entrepreneur and so just that like spur of the moment like i'm like i'm not tired of this argument like i'm actually an advocate of this idea

1:14:59that entrepreneurship is is maybe the thing that balances out the job loss but i found myself wondering like are we seeing any signs of that yet like are we seeing an increase in startups um so i just literally went into deep research in chat gpt and i gave it the prompt i said one of the theories about how the economy will account for job losses driven by ai is that we will see a rapid increase in entrepreneurship and the number of startups created is there any data showing an increase in startup creation of the last 12 to 18 months so i i actually haven't gone through and read this whole thing

1:15:30yet but it went through 33 citations and 341 searches and took 23 minutes to write me a report on startup creation ai displacement and entrepreneurship since late 2024 and it has a bunch of charts and methodology and sources and so i guess i'll just use that as a reminder of like hey sometimes that's a great use for ai is like curiosity it's like i wonder and it can be at the most random moment and you can just like set i mean deep research is an agent like it's going and doing its own thing it's taking actions to like it builds a plan and then it goes and take actions

1:16:03this is a form of an agent and it just goes to work and it does it for 23 minutes and then i forget i did it until i come back into here um but yeah i mean sometimes those are the best use cases is just that spur the moment hey i wonder if i could do this thing or if i could come up with this idea or if i could like create this visualization and then just throw it in there and see what happens so yeah it'd be it'd be a fun one for me for the week and i gotta go read this right that's the key all right so one other recurring segment we've started doing is each week we spotlight one of the courses in the ai academy to give people kind of real actionable takeaways from the course

1:16:37whether or not you know you ever end up becoming an academy member just to give you some of the value for free that we're creating in ai academy so paul i'm going to go through this week um our ai for hr course series very briefly um and kind of share some takeaways there sounds good so what's really cool and interesting and also a little scary in ai for hr is that it is really at the front lines of how ai is changing traditional systems so and in our research and in creating this course i'm the one who taught this uh we found that you know it's ai is creating chaos across the core work of hr i mean

1:17:14not only is it creating huge opportunities for hr as a function but they're running into real issues where candidates and employees are using ai too and it's not necessarily bad to use ai in your job search but it leads to all sorts of like really messy question because we're seeing hiring signals get really compromised because candidates are using ai to not only game the system but also just really really uh kind of hack their way through the process and it's like you can't use these

1:17:45traditional signals anymore to see if someone actually knows what they're talking about so you know employees themselves even after hired are using ai to do their work in ways managers can't see this is affecting everything from resumes to performance reviews to just overall productivity and hr professionals have a really tough job right now and that's kind of the big macro trend and one of the practical takeaways that we teach in this course is for your average hr person this can feel

1:18:16deeply overwhelming um there's so much going on in ai there's so much to learn they're already dealing with the fallout in a negative way sometimes with how the hiring process has changed one way that we kind of teach and walk you through in this course is just a really simple framework to get started thinking about okay i know chat gpt does this i've heard about claude over here like how do i wrap my head around the opportunities for me and my job and we use this framework called just pretty simply the three a's and three a's are this like sequential order to think about ai automation

1:18:51augmentation and acceleration so first you want to start looking at things like where can ai handle low level low hanging fruit repeatable work that you can literally have it do for you in order to save time because that's where 99 knowledge workers and hr professionals especially are really stuck as they are drowning in like reactive admin work that is not the best and highest use of their time so automation is a key initial step and you know like back to that discussion productivity is not everything

1:19:23but freeing up some time so we can be more innovative can be really helpful and then second is augmentation so looking at we walk you through a series of questions on how to actually surface these opportunities um augmentation is using ai as a co-pilot so let's say you freed up time by automating some things with ai you then can start doing more of the work you're meant to do more strategic more high value stuff well ai can actually augment you there to supercharge and just accelerate the value you create

1:19:54there which benefits you and helps you do better work not just faster work and then finally over time after you are effectively automating and augmenting your function as the case may be acceleration is kind of the bigger picture stuff right the ai agents the more transformative projects that's where we then walk you through thinking about not just what ai can do for you or how ai can make you better but what ai can enable that just was not possible before so we're talking you know we go through a bunch of use cases and examples of that in the course one really interesting one is um

1:20:29is uh i believe shopify uses an internal talent marketplace completely driven by ai to match people internally to different roles that's kind of a really structural long-term almost sci-fi use of this technology that completely upends how the company actually works so that's kind of the practical starting point it's kind of running your work and asking yourself a series of questions through those three lenses to actually sequentially step by step without biting off more than you can

1:20:59chew actually see some real value from ai right out of the gate it's a lot of stuff we need to be applying to our hr exactly right right yeah i have to admit i mean some of the stories even in this course and the case studies and even just some of the research even stuff that didn't make it in you're just like i would not want to have to figure this out that the amount of ways candidates yeah right recently right you know there's a lot of that overwhelmed feeling yeah of trying to not only figure it out for yourself internally how are we going to use it but how do we manage and like recruit

1:21:34and hire people who are obviously using it in the process or yes that's a very dynamic space right now all right paul last but not least we've got a bunch of ai product and funding updates so i've got the a bunch of these teed up like last week there are a lot of things going on i'm going to run through these real quick and if there's anything that jumps out you let me go for it all right so first up open ai launched chat gpt images 2.0 it's first image model with native thinking capabilities it can search the web generate up to eight consistent images from one prompt and produce this

1:22:09is important produce readable text that is accurate at 2k resolution it is widely seen right now as like being number one image model out there and is making a lot of waves open ai also launched chat gpt for excel and google sheets this is a sidebar app that lets plus pro business and enterprise users build edit analyze spreadsheets in natural language and pull in connected chat gpt apps alongside their data open ai also announced codex labs plus partnerships with accenture pwc infosys and other global system

1:22:42integrators to deploy codex across large engineering organizations anthropic and amazon expanded their partnership with up to five gigawatts of new aws compute for claude a fresh five billion dollar investment from amazon there may be up to 20 billion more following on that and a 100 billion dollar 10-year commitment from anthropic to aws plus direct availability of the claude platform inside aws anthropic also added a memory feature to claude managed agents which is now in public beta that

1:23:14lets agents retain and build on learnings across sessions via file-based storage and anthropic is apparently running a live pricing test on a roughly two percent of new signups with existing pro and max subscribers unaffected as the company experiments with how claude code access is packaged across tiers so also figuring out that pricing problem we were talking about google rolled out an upgraded version of its deep research agent built on gemini 3.1 pro adding a new max tier for extended asynchronous

1:23:47reasoning mcp connections to proprietary data sources and native in report charts and graph infographics google also signed a new multi-billion dollar cloud deal with miramarati's thinking machines lab giving the startup access to google cloud infrastructure and microsoft as we talked about has made copilot's agentic capabilities generally available in word excel and powerpoint so this just a little more detail here and on the product side this allows copilot to take multi-step app native actions directly

1:24:19inside documents spreadsheets and decks for microsoft 365 copilot premium personal and family subscribers at adobe summit 2026 adobe rebranded experience cloud as cx enterprise and introduced cx enterprise co-worker and yet another trend of agents and agentic ai layer that orchestrates customer experience workflows across adobe's stack spacex struck a deal giving it the right to acquire ai coding startup cursor for 60 billion dollars later this year or pay 10 billion if it walks away

1:24:53from the acquisition while the two companies collaborate on model training using xai's colossus super that's a wild one that is a wild one right yeah i'm not going to get into it because we're running on time here but um that one might be worth unpacking there's there's a lot to that story yeah another time uh 10 cent and alibaba are in talks to invest in chinese ai lab deep seats first ever funding round at a valuation now of more than 20 billion dollars with 10 cent reportedly pushing to take as much as

1:25:26a 20 percent stake moonshot ai which we've talked about in the past released kimik 2.6 a new open source coding model that claims state-of-the-art scores on certain benchmarks and can run 4 000 plus tool calls across 12 point 12 plus hours of continuous execution and finally zapier launched zapier benchmarks a new ai evaluation suite anchored by automation bench that tests agents on end-to-end business workflows across sales marketing operations support finance and hr using deterministic scoring

1:26:03grounded in 2 billion plus monthly tasks from 3.7 million zapier customers maybe we'll have dan slag and talk about that at macon maybe that would be awesome i would love to pick his brain about that i know that's dan's domain but right zapier's got a lot going on right now we were talking about their with their internal literacy stuff not like a week or two ago right yep all right so paul that is it for this week one quick final announcement here like we said at the top of the episode this week's pulse survey will be live when you listen to this at smarterx.ai forward slash pulse we're going full

1:26:38on agent today this week just like the topic so we're going to ask about things about where's your organization at when it comes to deploying ai agents today and also what is holding your organization back from deploying ai agent more than you are already today so i'll be very interested to see that uh paul based on the answers from this week as well but thank you for breaking everything down for us another busy week i know we've done two episodes this week so i feel like i've got a pretty good pulse on what's going on yeah yeah and i was actually home for like two days in a row for

1:27:12first time right well yeah and so uh yeah next time we're together we'll we will uh actually be back in town so enjoy your travels good luck yes uh experience inbound and i'll be off to uh i think at the time this drops i'll be doing the aquio engage event and then we'll be back we'll be back in cleveland and i'll see you for our uh chat gpt agents lab next week they'll report on yeah on the next episode yeah i'm super anxious i hope it's everything i think it could be i i'm very excited all right

1:27:43everyone have a great week thanks for listening to the artificial intelligence show visit smarterx.ai to continue on your ai learning journey and join more than 100 000 professionals and business leaders who have subscribed to our weekly newsletters downloaded ai blueprints attended virtual and in-person events taken online ai courses and earned professional certificates from our ai academy and engaged in the smarterx slack community until next time stay curious and explore ai