Joshua Wöhle: Turn AI Into Your Competitive Advantage and 50X Your Productivity | Artificial Intelligence | E393

24:40You tell it, do X, Y, and Z every time I tell you to execute the skill. it is a set of examples so that the ai understands what does good look like when i am asking for a proposal or whatever the thing is and then sometimes and this gets a little bit more advanced sometimes a skill can include some scripts which is basically some deterministic steps some things that always that it can double check for itself to make sure that it can consistently execute on the skill as you go through. So for Excel, this is one of the things because it's managing an Excel sheet is a very complex set of actions.

25:21And sometimes it has some kind of underlying programs, if you want, that help the skill execute exactly what it's supposed to.

25:27Hala Taha:I found this skill so helpful. I created like a lead prospecting skill and Rebel is able to like scrape emails. It can, I say all the things like the qualifications, Like for me, I'm trying to recruit podcasters. So how many downloads do they get? How many reviews do they have? Links to their social. Then it will even go as far as crafting a custom email, grabbing the emails and then drafting them in my inbox. It is insanity. It's literally like having a chief of staff that actually has full context of your entire work life history, as long as you were able to like provide that memory for it. Yeah, so to your point, actually, it's a very good point.

26:06the skills can be executed when you want them to and also automated, right? To your point, the automations. And so one of the skills I think that I built live on the weekend, which I'm now using every day, was this, it was a lost deals evaluator skill. So this was just one of the ones that I hadn't gotten around to building yet, but just something that looked at my Slacks, my emails, my WhatsApps, and looked at deals that were in our hop spot, that didn't have activity for a while and then draft an email to revive the deal that I had forgotten about or I had let go for too long. And I remember I did, there was one of the people that was on the weekend that was actually part of the emails that it wrote live, I think, whilst we were there, which was a fun bit.

26:55But that is indeed a good example of a skill.

26:58Hala Taha:I mean, I've been using it so much to the point where I'm like, okay, this is supposed to save me time, but I'm actually working a lot more now because I just feel like, oh my gosh, this could be a skill and I can be a better leader by using Rebel in this way. And so I found myself after the weekend, I think I got home on a Saturday. Sunday, I was supposed to have like a day off, but I found myself working the entire day on Rebel because it was just so exciting to me. So what kind of boundaries are you putting in place? Like, how are you ensuring that you're learning AI? And of course, I know it's your main thing, but for like the normal person, how should they ensure that they build in time to learn AI?

27:38Hala Taha:And how can they also put boundaries if they find themselves like me, staying up really late and working through the weekends because it's just very exciting. Something that we have recently become more aware of and we're spending more time on. Actually, the end of the weekend was exactly about that, right? where you have all this newfound ability, where do you actively want to deploy it? Because most companies don't actively think about that. They go down the productivity line and they get the extra time, but then they're not as conscious of where that time gets deployed. And that is important both at a company level and at a personal level.

28:23Now, there are a few things to look at here. And I think part of this is an individual answer for everyone, because not everyone will find the same balance. This whole thing about work-life balance is different for whoever you talk to. But the thing that is most important is that you consciously go in. And I think Jeremy, who was my co-host on the weekend, he puts this fairly well, which is thinking about the person you want to be and being clear about what that person is, who that person is, and then using that as you get introduced to AI, as you start to find different optimizations, as you find more time back, so that you're clear about where you want to deploy that time.

29:12A very active bit of that right now is, I mean, I'm trying to live part of it at the moment. So I've got, we're here in Austin, I've got my wife and kid here as well. And for the first time ever, I'm basically trying to combine, he's got three, four more months left before he's starting school. So this was the last time that we could go and get some travel in it. And just trying to do it all really, which is running the business, being in the US more, most of our clients are US, but also being able to travel a little bit going through. And so in six hours a day at the moment, I think I'm able to do, would have taken a full week before, almost forcing myself to live that future so that I'm not setting the bad example either, which is that, because it is very easy to get drawn into this being 24 seven.

30:01Because it's very addictive once you're able to do so much stuff. I mean, we all want, ultimately, we all want to be, productive is maybe the wrong word. We all want to be good at what we're doing. So when you suddenly feel that you can be twice as good at it, three times as good at it, four times as good at it, that feels really good. And it's actually very addictive.

30:25Hala Taha:It is addictive. I feel like we need to make sure that we're building the right things and not just building to build. The other way that I've been thinking about it is like, so when I first, I've been an entrepreneur now for like six years. The first four years, I worked myself to the bone. I'd stay up till 2 a.m. every morning. I worked through every weekend. And then suddenly, like, I built all this capacity in a team and trained everybody where now I can do whatever I want. You know what I mean? Like, you know, I still work hard, but I can take a week off. I can do it. I built a business that runs without me.

30:55Hala Taha:And so I think of it as this, like, you got to, like, set everything up. And now is the time to, like, focus and figure it out and think about, like, what can I automate? me, how can I redesign my team where like these low priority things that we used to spend a lot of time on now, we use AI to do them. And how can I open up my team from more capacity? And it's kind of feels this like this new like reset of I need to set my team up for success. And this might take some focus time now. But I imagine in a year after I've set a lot of these things up, that it would free up capacity. So it's kind of like this like sacrifice, work hard now so that you can free up your time later on is that the right way to think about it yeah for those for those that want to create that opportunity for themselves absolutely i mean that's definitely what what i am doing as well so the um putting in place that basis and it was i think for me there was a tipping point somewhere when was it i think it was october of last year um up until that point i think i probably i don't i have never worked more in my life and so i was doing whatever like 18 19 hours a day every day seven days a week because i was in that loop yeah um and so i was like okay i'm twice as productive three times as productive four times what i'm 10 times as productive shit like and literally was going through how far can i go yeah exactly and then i think there was yeah so in october um there was a very conscious moment where i realized for the first time i was like actually i'm gonna next week i'm going to consciously start to do less So I felt, I mean, I'm in a different place as well because I'm on that cutting edge.

32:34So I kind of felt that it's okay to only be 10 times more productive than what I was before. Nobody else is there yet. So I can take a bit of a breather in a way.

32:44Hala Taha:Yeah, help us all along get to where you're at. You're a very successful entrepreneur. You've had multiple companies. So you had Super Awesome that you sold to Epic Games. and at that point you could have just retired a little bit or taken a break but you jumped straight into starting Mindstone. So what was the genesis of starting Mindstone and talk to us about why you pivoted into AI? My view of a great life is not one of sitting on the beach and not doing much. That's just not who I am and so the biggest thing is I knew I wanted to do something that would make a difference. Literally the number one way that I think about measuring my life is leaving a legacy in one way or another.

33:28And then I hesitated between a few industries and the one that I, I think it took about two months or so of kind of thinking through. The one that I thought I could really make a difference in was education. Because, I mean, it is entirely broken. There's so many things that need to be different or even already needed to be different six years ago about education itself. And I have a bit of a weird past with education. I always loved learning. I hated education, thought there was a better way to go and do that. And so really the first bet was just, okay, I can see myself spending 30 years tackling problems in education and try and be as helpful as I possibly can.

34:09And then about three years in, well, Chachi PT happened. And it also happens to be actually just before starting Super Awesome. And this is, I think this is actually something very few people know about me yet but I was I was supposed to go and do a master's in AI in London I'd been accepted there to go and do the thing and that was that was going to start in September and then I think we had conversations with Dylan in April May of that same year about starting Super Awesome and so ultimately I decided to go and start Super Awesome but I've always had this inkling of AI. I've always been really passionate about AI to begin with.

34:49And so somehow when then ChantGPG happened and suddenly everything in learning changed, both in terms of what we could build, but also in terms of the skills that would be useful in the future, it's kind of like every single thing that I really like doing in life came together.

35:04Hala Taha:That's amazing. And it's a good thing you didn't take that AI program because probably would be completely irrelevant today. But to that point, what are the things about AI that you learn that continue to be relevant? Like, so for example, you've got this MindStone AI training. I assume if people take this training, it's not going to be irrelevant in a year because there are foundational things that you need to learn in terms of how to use AI. So talk to us about some of those things. We've touched on a few of them, which is talk to it like you would talk to a person. I think that's the number one.

35:38The second one is ask it to ask you questions. Don't just ask it for answers. It's not terrible to ask it for answers, but actually the majority of your interactions should be getting it to ask you questions instead. Help it help you think. Don't let it take the thinking away. If you're a manager, there are things you can apply of how great managers work that you can also apply to AI with a slight edge. So one of my other favorite ways of using AI is getting it to rate itself. when you're building companies, you're building teams. If you're successful at what you're doing, hopefully you're hiring people that are better at their respective jobs than you are, right?

36:14That's why you're hiring them to do those jobs. So it's really hard sometimes to then give them great feedback because actually they know their job better than you do. And so one of the main techniques of a manager ends up being person comes back with a piece of work. It's great. How would you improve on this particular piece of work? They go and line out all the things that could be better on that particular bet. Okay, great, I agree with you. Now go and do all the things that you just said you could do to make this even better than what it already is. In a human context, you have to think about how does that land with the person?

36:51They just spent a week doing this piece of work. I'm now asking them to spend another week. How are they going to enjoy this? They have a whole bunch of other things they need to get done. So you have to think about that emotional component. With AI, you do not. but you can apply the same technique, which is ask the AI, okay, you just did this piece of work for me. On a scale from zero to 100, how would you rate that you just did that job? It comes back. I think I did a 78 out of 100. It's great. What is wrong with it? How would you get it to 100 out of 100? Well, I would do all these things. Okay, now go and do it.

37:22Hala Taha:It really is like managing someone. Exactly. Yeah. That's another really big one. And I think those few ones are already things that everyone today can apply because they're simple, but extremely powerful. And then once you start to get into the habit of using it in that way, you're then starting to get to the edges of agentic AI and like getting it, you've got these custom GPTs or projects on Cloud or skills are actually not too dissimilar from like a custom GPT or a Cloud project, but just the agent decides to execute them when they can. And there I'd say this is the encapsulation of certain units of work.

38:06So once you start using it more regularly, then you have to start thinking a little bit more inward, which is what are the things that I am doing that I'm doing fairly frequently and that take a decent amount of work or the things I should be doing frequently that I never get to or that I always do to a low standard when they should be a high standard. Actually, that second bit is the thing that people often forget because it's a treasure trove of potential AI enhancement. So what are all the things that if I had the time to do, I could go do and that would make a big difference on my job or on the quality of my work?

38:43Well, get AI to do them. If you don't have the time to do it, get AI to do them well.

38:47Hala Taha:It's so interesting that you bring that up. I remember one of the questions that you guys asked on the AI weekend is that you say AI is like an intern that doesn't sleep, right? and you're like, if you had to give an intern something to do for 24 hours a day or even 12 hours a day, would you even know what to give it? So how can we start to understand like what we actually need to build? Yeah, this is where people that have managed people before do have an advantage. And people that haven't quickly have to figure out what that means because we are all basically becoming managers in one way or another.

39:29And I would also argue that the analogy of the intern is very quickly becoming the mid-level employee and the senior employee. Yeah, I agree. So the, depending on the quality of your rebel installation, I am now, like when I look at our proposal skill, it does better proposals than I do. No question. And I would consider myself a very good salesperson in one way or another. I do good proposals. It's a skill that builds up over time. And this is the, both the good part and the bad part, which is that it's actually very easy to get going. Luckily enough, the technology is not the problem. We often talk to customers when we start working with the organization, we say five to 10 % of what we do is helping people use the tools.

40:1990 to 95 percent of what we end up doing is helping people with the mindset shift of thinking differently about the way that they approach work to begin with and that is where you get the real return on generative ai and it's actually the thing that people forget they think that they can just roll out chat gpt and people will just figure it out it's as if you think okay well we're going to give every to your point we're going to give everyone an intern and they'll just figure out how to make that intern really useful, let alone if you're giving them actually capable, like really capable employees, like they wouldn't know what to ask them to do to begin with.

40:56And so the real work is helping people understand how they can take advantage of that technology.

41:03Hala Taha:There's so many ways I can take this, but I think the next point that I want to talk about is the ability for like the workforce to be able to code now, essentially, and build apps. So I was totally blown away by the fact that on this AI Breakthrough Weekend with MindStone, I was able to basically create an app in 15 minutes. It basically took a podcast episode. I asked, you know, it was ChatGPT. I asked it to uncover my process and to help me come up with a prompt that I then put in Riplet, which you guys taught me about, to create the app. And then now I have something where I can pop in my episode transcript link to YouTube.

41:42Hala Taha:It pulls out the hooks, the clips that we should use, the best quotes, like all this kind of stuff. I also created a new app right after the weekend to help me create research briefs. And honestly, the output of that app is so much better than what my team was giving me, what I was doing with Chajibity. Like it is just so much better. and I was talking to, I met this girl who works at one of my sponsors, actually their company. So I'm not going to say the name, but it's a very big tech company and she's in sales. And this company is very AI forward. And she told me that they have an AI quota. Okay.

42:21Hala Taha:They actually get judged by how much AI they use. She's a sales person. She said she's coding now and that they actually will fire people who if they find out that they're doing stuff that AI could have done. Yeah. And it's basically she's like, she feels actually scared because she's really excited that she's learning all this AI. She knows that if for some reason she loses her job, she's so much, when I was talking, I was like, damn, you're really like, they're preparing you for the future. So either way, it's a good thing. Yeah. But she's also scared because she said that part of it is like she gets AI generated emails like in her inbox before she responds to an email.

43:02Hala Taha:The email is already drafted. And then she actually edits it before she sends it out. So she's actually training the AI. And she basically said, I'm kind of training the AI to take my job. So there's a couple of questions I have in this whole breakdown is like, how do you imagine the workforce in terms of their ability to code? What does that mean for software engineers now? Like, what is the software engineer role turn into in the future? And then also, like, how should knowledge workers think about the fact that they might be training AI to take their jobs and now, like, they're suddenly judged on how well they use AI?

43:36Hala Taha:Like, how should they be navigating all this? Yeah, this is where the real questions start, right? So the interesting part is we're coming back to the analogy of what does a great manager do? It's been the case for years and years that the number one role of a great manager is to make themselves obsolete. It's to build a team that can function without them. And actually the same is true here. Yeah, you are building your AIs. Your job becomes building a system around you that can do the job you're currently doing without you so that you can go and do the next thing. And we'll get through to what that next thing then becomes soon.

44:12But when you think back from a software engineering perspective to the first question you had there, um i think it's really useful for people to look at what is happening with software engineering and it's good it's hard because people have not emotionally been most people in the world are not emotionally connected to software engineering in one way or another that the it's actually been like software engineers had a really good life um we're getting paid a lot of money to go and do things that they actually loved doing but in some ways they're absolutely living the future And when I say that, if you are still manually coding something by hand today, as a software engineer, you are already behind.

44:56Nothing we do in MindStone is manually coded anymore. Actually, we're now at the point where almost everything doesn't even get seen by a human anymore from a code perspective. And that seems outlandish. um but it is definitely what is happening everywhere and so as a software engineer your job used to be coding say 10 years ago now having said that last year or two years ago already a great software engineer their job wasn't just to code you can maybe think 30 40 percent of their job was to code and the 60 or 70 percent was to figure out what to code to begin with. So a lot of even software engineers then took what is happening at the moment in somewhat of a bad way, or at least they weren't extrapolating, where they were looking at, okay, the coding part of my job is now getting automated.

45:52Great. I can do other things, which is exactly the attitude you should do. So do more of the other bits. But what is happening this year is also the bit of figuring out what to build is now also getting automated. Figuring out how to build the spec, figuring out the architecture, all of these pieces that were higher level software engineering that a senior software engineer or an architect would do, they're also now getting automated. And where this is so useful as a paradigm for everyone else is to think through what is the equivalent of coding for a software engineer, but for someone in finance or for a lawyer or for an HR professional.

46:31or a marketer. The equivalent of coding for someone in finance might be managing an Excel sheet. That's disappearing this year. Probably by the end of this year, maybe even the middle of this year, you shouldn't be manually updating your Excel sheets. That means that you can live one level higher. And that one level higher, the strategic financial picture and everything, maybe the supply the way that you deal with suppliers the way that you look at the financing structure of the business that will still have a year or two extra on top before that also starts to get touched in different ways so taking that bit really seriously i think is probably the most important bit because people keep discounting this as if it is fairy talk it is not my cto greg recently did, it was literally two days ago, did a talk at a CTO conference.

47:30It was very interesting because this is a really forward-leaning audience. You would expect them to really know their stuff. And so he had prepared this talk thinking, okay, I'm going to go into a whole bunch of people that are very on top of their stuff here. He had prepared the starting point of his presentation to figure out where is the room at from an AI adoption perspective. The first question he asked was how many of you are still writing code by hand all the time? So without, yeah. And he had expected, okay, that's going to be very few.

48:03Hala Taha:Yeah. Most of the room had their hand up. Oh, God. And he was like, okay, how many of you are using at least agents to do part of what you're doing? Like barely any hands. And he had like three, four levels behind that, which was how many of you have an automated process to deploy what the agent has built? How many of you are still looking at the code? How many of you are still looking at the reviews of the code? Yeah, but he couldn't even ask them because even in that room, people are putting their head in the sand. It is the reality of where things are at is moving much faster than how people are able to catch up.

48:44And I think the biggest thing that people can do to prepare is to take note of what is happening there in software engineering and figure out what that means for their own job. Don't wait. at least for a little bit of time live in a world where you're thinking what if sure make up your own mind based on what you think is real and what is not but the number one thing is try on a regular basis to check back in if the technology can do a thing and also if you do it once and it doesn't quite give you the thing and you're like oh i can't it can't really help me in this thing it was kind of there, but not quite what I was looking for.

49:23Try it again in a month.

49:25Hala Taha:Yeah, things change so fast. And I think that is the really important bit is getting people to understand this. So figure out what is the equivalent of coding for your own job. And then start to figure out how AI can do more and more of that. Try to figure out where you can then spend the additional time. And this is where we come back to you being deliberate in where you want to spend that time and where it is most effective. Don't let that happen to you. Be an active participant in that change.

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53:55Hala Taha:And now there's a limited time offer. Get Huel today with my exclusive offer of 15 % off online with my code profiting. So that's code profiting, Huel.com slash profiting. new customers only. You get 15 % off. Again, that's Huel.com slash profiting. And thank you to Huel for partnering and supporting our show. As we're thinking about careers and navigating careers, some of the things that I'm kind of absorbing from this is if you can try to be in a company that's actually very AI forward, like that's going to be great for your future, even if it feels painful in the moment, like being forced to use AI.

54:29Hala Taha:I know you do something similar at your company. we can talk about that. But having a company that's very AI forward is actually a really good thing for your career. Even if it means you get laid off in the future, you're going to be way ahead from the other people who weren't put in that position to learn AI. So it's like, and then also, if that's not possible, I would say go find a company that's where that's possible. If that's not possible, learn it on your own. Okay, do the steps that you need. You have a four-week training that anybody can sign up for. It doesn't have to be through a company.

54:56Hala Taha:So learn AI on your own if you have to. And then lastly, it feels like entrepreneurship and being a founder is the safest route. I was, there was literally just as I was coming here today, there was an ex-interaction where someone was asking, if everyone becomes a founder, who are all the employees? And my answer to it was, well, agents. Agents are the new employees. but I wanted to focus on one bit that you you talked about which was this the fear around the adoption piece and like making myself obsolete in one way or another I think that is really important because there are multiple aspects in this and there are I fully agree with you that if you are in a job right now and a company that is not fully embracing this I would say that is the number one warning sign It's like, if you can, get out of that job.

55:54Hala Taha:Because that company is going to go out of business. Yes. Even if they're not going to let you off, that company is not going to. Well, and they're going to let you. Basically, you're not going to have the job because the company is going to be out of business. Exactly. And you will not be in a position to easily find a job anymore because you've lost the skills. You're behind. Yeah. Yeah. So that is a really important piece, I think. then within that one of the things that i um i must say i i struggled with um is that when we started mindstone i thought our mission our entire purpose was to light a fire in every single person in the world and somehow help them figure out how they could enjoy learning love learning i love learning.

56:42And I thought for a while that was what we needed to do. Because if you love learning, everything becomes much easier. I realized about halfway through, a little bit less, I think it was the first two years or so, that that was actually a very self-centered way of going through life. Somehow I thought that was something that everyone would like. But actually, learning is like many other things in life, which is that some people love it, Some people hate it. And I realized, and it was a real epiphany for me, when I realized that actually most people are scared of learning, are scared of change, it became so obvious.

57:22And some people must be listening to this as like, well, obviously. So this was not obvious to me. When I realized that most people just don't enjoy that process, it really changed the way that I thought about learning to begin with. And then when AI hit, it became obvious that a lot of company leaders are, I would say, actually negligent today. When you have a team that you are responsible for. And you might think that you're doing them a favor by not being clear or not giving them what you would consider the extra load of asking them to learn how to use AI in their job. You might think, okay, I can't.

58:05They're already stretched. They're telling me they don't want to. Actually, the kind thing is to tell them to do it. They will thank you for it afterwards. And a good leader is not just doing what their employees ask them to do. They are trying to get them to the best possible outcome. And there is a real dereliction of duty at the moment. There's a real failure of leadership, I think, in many organizations where they, because learning has been, for the last 20 years, most companies look at learning as a retention tool. They basically did learning budgets so that you feel you have some progression and you wouldn't churn as an employee.

58:44You would not leave the company because you felt the company took care of you in one way or another. but it was optional and it was a thing you could opt into. And too many companies are approaching this in the same way when actually they now have a responsibility. They have a responsibility to the employee. And that is what I can see actually to the person you were talking about. I can see how that can suddenly when the leader's trying to lead and is doing it maybe slightly too aggressively can lead to some fear of exactly like, okay, now I'm being asked to like, absolutely do this. My job might depend on it.

59:15And that isn't, I'm not saying that is a good thing at all. I'm saying that is definitely something that needs to be managed better. But between the two fears, I would want to be in the position where I'm being forced to use it more and being set up to be successful in the future. Yeah.

59:31Hala Taha:Giving access to all the tools, having the tools paid for you, all those things, learning on the company's dime, essentially. 100 percent. And I think that is so important. The real problem is the leaders that are not currently making this clear. They are actually the ones that are setting their team up for failure over the next few years. And it is a responsibility. And I don't think enough leaders are taking that responsibility seriously at the moment. So let's talk about how to actually implement AI in our organizations. You actually say it's not really up to IT only to implement AI. It's actually an HR problem.

1:00:06Hala Taha:Talk to us about that. Yeah, it's actually not even just only. This comes back to this idea that only five or 10 % of what we do is help people use the tools. The tools are easy. Deciding to use ChatGPT or Claude or Rebel, okay, there is a technology discussion at some point. But what you do afterwards is what really matters. If you just roll out the tools, you can't be surprised that you're getting very little back. The tools don't adopt themselves. There was a friend that told me the other day, it's kind of like giving someone a Boeing 737 and expecting them to be able to pilot the plane without any guidance.

1:00:49It's like, sure, it's like a really advanced machine. You can do a bunch of things, but if you don't tell the person how to use it, they can't do anything. One of the more important signals and the important things that we try to help the company with is to help them realize and move the responsibility of AI from the CTO to the CHRO, or at least someone who is looking at the people side of things so that they understand that this is not a technology question. And that is the number one thing. They shouldn't be looking. This is hard. And I say this, I am a software engineer by background. I was CTO at Super Awesome.

1:01:25This is counter to a lot of what I would have said before, but generative AI is a technology unlike anything we have had before. And the reason this is so difficult is that it is technology, which means that all of our pattern matching puts it with the CTO, puts it in the technology bucket. And so by default, it is the CTO's responsibility. But the impact is on the people. And so once the technology is rolled out, the real work starts. And that real work is people work, it's process work, it's business work, and it's no longer the responsibility of the CTO. And the biggest signal we see is when we are able to shift that responsibility from the CTO to the CHRO, we know we have at least had a real impact on the business.

1:02:16At that point, we know that the business will, everyone will have different pace of development going through, but that's the number one signal that we would look to. When AI first, you know, came out more broadly where like companies started to really use it, there was a trend of kind of using AI to actually cut workforce and to lay people off

1:02:41Hala Taha:and basically replace workers. And a lot of companies like Klarna, for example, were kind of first to lead that. And it actually failed. Whereas other companies like IBM decided to reskill and upskill their employees instead using training similar to what MindStone does, I imagine, right? So talk to us about the right way and the wrong way to think about rolling AI out to your organization. And what are some of the key things that we need to, like, key challenges or obstacles that we need to look out for? So it's a very, very good question. And I think even outside of IBM, IKEA was a really good one.

1:03:18So it actually comes back to a very similar starting point, which is when AI is the responsibility of the CTO, technology has been for years and years and years about automation. And AI has been about automation for years. When it is the responsibility of the CTO, the focus ends up being on automating work away. and a side effect of automating the work away if you're not being conscious about what the results are afterwards is that the work disappears and you haven't figured out what other work needs to happen which means redundancies it also happens at board level and this is actually one of the biggest things we are not doing enough of yet we get to work with the executive teams a lot we don't do enough work with boards yet and the problem with that is that you still have the same thing which is that we'll work with the executive team.

1:04:09The executive team understands there is a whole other side to generative AI. And I forgot to mention this, like the flip side of automation is augmentation. Is how do you think about the enhancement, the improvement in quality, moving the top line, helping the company grow faster, helping it make more revenue, do better work, all of those things. That is actually where a lot of the value in generative AI lies, but it is not historically where technology has had the biggest lever. So we often work with an executive team. And even when the executive team gets it after a while, and I had one of the more memorable experiences I've had this year is training the executive team of one of the Fortune 50s and really feeling that we pierced through.

1:05:04They really got it. was like three hours into a session. They were really excited, all of the stuff we could do. And then the CEO stands up and said, great. I've been told to find a billion dollars to cut out of our budget. Where do we get it? Which was good. I mean, it's a win for the business, but it was exactly the opposite of where I was trying to put the emphasis. Like, don't just think about where you're going to gain the costs. Think about how this can double your growth rate. How can you find$3 billion in additional revenue in order to maintain where you're at or move people around so you don't end up always focusing on the cost reduction?

1:05:47This is a real competence problem at the moment. People don't know what they don't know. So they focus on cost optimization instead of augmentation. This is where this drives to Klarna. that they when and i'm i don't and clarna are doing some awesome stuff right so this is

1:06:07Hala Taha:the reality is yeah no shade on clarna exactly people get first movers get things wrong we got so many things wrong like honestly i have this this really if if you look back at especially in ai if you look back at how you were operating a year ago yeah and you're not ashamed two weeks ago. Exactly. If you're not ashamed of like how you were operating six months, a year ago, two weeks ago, then you're not moving fast enough. And so they were one of the first ones to move. They moved maybe a little bit too quickly. And I think the thing I do think that was maybe a failure of the way they could have led is that they led with the redundancies.

1:06:49And so they they decided to automate customer support and a whole bunch of people lost their jobs. And what I do think, and what I would love people to walk away with is the case that IKEA made, which was completely the opposite. IKEA took their customer support employees and basically decided to put them through training to make them all interior design consultants. So what they did is they looked at what does customer support or customer success look like for IKEA? And they said, we now have this technology that can make everything better. What does customer success look like if it were twice as good?

1:07:27In the case of Ikea, that meant everyone now has an interior design consultant. And so they thought, we're going to elevate this experience. And I think this is the thing that people need to take away, which is you can think about a problem two ways at any point. You can try and figure out how do I get to the same level at half the cost? Or how do I keep my cost, but make it twice as good? And I want more people to focus on that second bit for two reasons. One is because it actually leads to people keeping their jobs and everyone getting a better outcome. Two, because it's underinvested in and people would be surprised how much easier it is to get to that point.

1:08:13It's just that we're not used to thinking about it.

1:08:16Hala Taha:And the companies that are going to stay and grow and thrive are going to be thinking about how to actually make their stuff better. 100%. Yeah. So what about the fact that AI is not free? It costs money. Me and Kate were kind of doing the math because I was, Kate's my business partner, because I was working so much on Rebel and I was like, man, this is going to reduce the cost so much. And she's like, well, according to like how much we spent, it's about$1 ,000 a week right now. And I was like, well, that's kind of worth it for everything that I'm building, you know, for me as the CEO, but we need to kind of put guardrails on other employees because we can't have everybody spending, you know, let's say 500 bucks a week or whatever it ends up being.

1:08:59Hala Taha:So talk to us about how we can navigate kind of how much spend AI costs and like how we should be thinking about that. Yeah, so this is a very live topic for us as well. For context, right now on the software engineering side, we spend$5 ,000 a month per developer. And on the non-software engineering side, it depends on the employee. Right now, we're spending about$1 ,000 or$1 ,500 a month, but that is because we are not yet as effective as we want to be. I think it is really important to look at where are we at right now and say, over the next six to nine months and what long-term is going to be where we end up.

1:09:45So right now, I would look at the API spend as a KPI, weirdly enough, to optimize for. I would say as a business, and we actually tell this to all of the customers we work with, when your API bill goes up, you should celebrate that across the organization. You should have an incentive system where the person that racks up$500 in a week should be put on a pedestal because they have been leaning forward. They have been trying things. And the results that you will get as a business from the fact your employees are trying it and really leaning in are going to be so much more valuable than what that costs that right now it's actually a thing you really should be optimizing for.

1:10:33Internally, we have a target and we're going to think about it the other way around as well. Actually, when you do$500 a week, you're probably, it'll be interesting to see how much you can push that. Most people will naturally, once they've got kind of Rebel in place in different ways, they will naturally top out at about$20 to$30 a day at a maximum. And that's when you start to really use it. So you're using it really well.

1:10:58Hala Taha:Yeah, I think I misspoke actually. I think in a week, I did like about$300 or something. And then it was like, she was like, it's about$1 ,000 a month. And actually it was like, that's really good. I mean, for how much I did,$1 ,000. So I misspoke on that. It was about 200 or it was over$200 for the week. And she was like, it's about, she was saying like, it's probably going to be like$1 ,000 a month. Okay. Yeah. So that is, that is, then you're at that level of doing it, doing it really well. And so short term, that is actually what people that get there tend to get a dramatically higher return.

1:11:34Now, you do want to, when you start rolling this out for 100 ,000 people, obviously you want to start looking at, okay, there might be a few people that end up spending much more than what they're making back, but that's the exception rather than the rule. So short term, I'd say, optimize for it.

1:11:50Hala Taha:And then also, if you know how to use it well, you don't waste the credits, you know what I mean? And some of it can be pretty cost effective. Like I was looking at, because I was building all these apps on Ripley and then I didn't know that it was charging us. And so again, I told Kate, I'm building those apps. She's like, well, be careful because it's charging us. And I was like, oh shoot. And I go and look and it was like, I built two apps and it was like$10 or something. And I was like, oh, this is fine. I can make as many apps as I want, you know? So it's not that expensive, but to your point, rolling it out to 100 ,000 people.

1:12:25Yeah, so to give you a direct example, the other day, So I am having a conversation with a few investors here and there. And so as they were starting to become more serious, I thought, okay, let's be a little bit more thoughtful about this. Let's figure out who would be the 10 investors in the world that I really need to go and have a chat with rather than just randomly waiting for the few that I happen to just talk to. normally previously in super awesome like the process would have been manually researching like 200 investors and or actually manually researching 500 of them so then whittle it down to 200 that might be interesting to speak to and then the 100 that you actually get a path into and then like basically try and have a whole bunch of conversation to go through like that would be one to two weeks worth of work of just doing the research, making sure you're prepared, going through things and figuring out who goes and introduces you.

1:13:27I did this last week with Rebel. And I think the conversation cost me about something. That one conversation cost me about$25. And Rebel actually shows you per conversation what it costs you to go through. But in that time, it had researched a thousand different investors, put everything into an Excel sheet, rated every single one of the investors based on how Mindstone operates, what their thesis is, crawled through all my own emails, figured out how many of those people have I already talked to? Do I know? Am I connected to them on LinkedIn? Reranked them based on thesis overlap and proximity to being able to get either already knowing them or having a direct introduction and then just gave me the top 10 that I should talk to.

1:14:10Honestly, two weeks of my work, weirdly enough is worth more than$25. Yeah, that's crazy.

1:14:15Hala Taha:Or like, you know, that would have been a$30 ,000 consultant who wouldn't have had the context or written it in your voice or, you know, so that's incredible. And so that's kind of short term. So I think that is a really important thing for companies to understand, which is short term, if your problem is you're spending too much on the API, actually, let me revert that. It is easy to think your problem is going to be that you're going to spend too much money on the API. I have only seen that by some CEO or CTO that knows what they're doing. They let it loose. They're like, oh, I just spent$200 in a week.

1:14:52And then they extrapolate thinking, okay, if I roll this out across my company, every person is going to now do$200 a week. They are not going to be doing$200 a week because they're not you. They have to go through their own AI adoption journey. They will start with spending$1 a day. And actually your problem is going to be that you're going to have to show them how to make much more, how to take much more advantage of it. That is your real problem. If you ever get to the point where you have that API bill that's so high, it just means you're the most AI forward organization in the world and you will have double, tripled your numbers.

1:15:29Now, longer term, I have actually recently changed my mind on how this will play out. So I used to think that for a very long time, it would make sense to just use the frontier models, the best models that exist, the most expensive ones, which are the ones that we'd be using in Rebel as well. And well, that frontier keeps going up, actually. The most expensive models, they get better and better, but they're also getting more expensive. Now, when you start looking at the trend at a per intelligence level, So for the same quality intelligence today, you're paying about a hundredth of the price of what you would have paid last year.

1:16:08Like a hundredth. And what is happening is right now, literally the period we're in right now, we are for the first time at a point where many of the frontier models are at the same, if not higher level. than intellectually than most human beings. So what that means is the reality is that rebel often knows better than I do. And I have to really double check myself every time that it comes to a conclusion that's different to my own. I really have to figure out, wait, how did you get there? Explain it. Let's walk through this step by step. Let's see it. And most of the time it was right and I got something wrong.

1:16:57Now, the reason this is important is that actually we're about to get to a point where, and it'd be interesting to see just the next generation of models, and we're talking two months from now.

1:17:09Hala Taha:Oh, gosh. I know, it's going so fast. The next generation of models, I think for the first time, will get to a point where most people won't notice the difference anymore. because unless you have for the last three years built up systems that go beyond your own intellectual ability you won't see the difference between those two levels of intelligence because the model is just more intelligent than we are and so you you no longer absorb the difference you won't be able to take advantage of it ultimately you have a question you reason it through it gives you an answer if you don't have the systems in place to try and figure out was it right answer was it not how do i think about using this intellectual capability you just can't use it with which then means that for the majority of people this approximate level of intelligence of where we are now and it's going to become the harnesses around it the agents around it are going to get better but the intelligence level underneath in a year from now is going to be at a hundredth of the price so right now you might for this level of intelligence you might be spending two hundred a week.

1:18:13Great. That means that in a year from now, you'll spend$2 per week for this level of intelligence. Now, you might be able, as you now, because you're starting earlier than most, you're definitely on the early adopter curve. In a year from now, you will have built systems that will allow you to take advantage of a higher level model. So you might not be spending$2 a week, you might be spending$20 a week,$50 a week. It's unlikely that you'll still be spending $200 a week. If you do, however, you'll be the most AI powered, AI first podcast network in the world and you'll have taken over everything.

1:18:53Hala Taha:Yeah. Let's talk about right now. I know things are moving really fast, but right now we still need humans in the loop. We can't just let AI run wild. It's the reason why in Rebel, you know, it doesn't automatically send emails, it drafts, and then there's a human in the loop. So what would you say in 2026 are the things that you won't be automating with AI? It's a good question. And I'd love to just revert to the human in the loop bit, because actually the framework that we prefer is human at the helm, which is a different thing. But I think it's a really important nuance difference, which is that human in the loop makes the human the bottleneck.

1:19:36Because it somehow means that it's kind of like the manager that asks the employees to run everything through them. You're always becoming the bottleneck, which means that the maximum level you can get to is always how much is going through you. It's the same of autonomous cars. Actually, the autonomous car analogy here is not a bad one at all, which is that if you still need to be in the driver's seat and you're still responsible for, and you still have to have your hands on the wheel and do everything. There's only so much benefit you're going to get from an autonomous car. Now, the reason human at the helm is different is the idea that you as the human take responsibility and you're accountable for what happens with the AIs that you put in motion.

1:20:22And then you are the one that decides what level of autonomy do you give them? You tell the, you set the context in which your employees understand what they're allowed to do and what they're not allowed to do. In some cases, you might tell them, I'm happy with you sending emails. In some cases, you're not. Email sending is an interesting one because it's a hard one to get past. Yeah, it's you. Yeah, exactly. I'm starting, like there are now one or two scenarios where I'm starting to get to the point and I'm explicitly telling it, you can send this email.

1:21:00Hala Taha:I do it from my internal Slack messages. Yes, exactly. I'm like, tell Ebi what to do. Tell so-and-so what to do. This is, yeah, it's so interesting. Internal Slack messages, I'm fine. Just do it. Yeah, so I have the same thing. Literally just coming over here, actually, I had a big piece and I had to come here, but my agent was still working and I kind of had just like, okay, well, when you're done with this work, send the result to Hannah and do it in whatever way. And then I just walked away from the machine. And so the way that we're trying to instruct this now is that if you're very explicit with Rebel, it will go into it.

1:21:40If you tell it, send the Slack message or send the email, then it will go and send the email. If you tell it draft, and then somehow, and this is the thing where it's hard, somehow the AI then decides, oh, well, it asked me to draft, but I'm going to send it anyways, which actually, this is what has happened with like Open Claw and other things. And every time that you hear this horror story, it's like, well, you told me to do this thing. And I just decided to wipe your whole hard disk. Your computer is gone. Oh, wait, you didn't want everything? That was terrible. I shouldn't have done that. That's the bit where we come in, where Rebel as a system should take over.

1:22:18It's like, hey, the user asked this thing, asked to send an email. Wiping your hard disk doesn't seem like an action that should happen when the user is trying to send an email. We might want to ask the user if they're okay with this. The same if you're saying, draft me an email, and the AI tries to send the email, it should ask you, hey, okay, they asked to draft the email, not to send it. So the way we're thinking about it is you need to have multiple systems around, this is where the AI operating system comes in, where Rebel really, I'd say this is probably one of the cores of Rebel is that it doesn't just leave fully autonomously the agent to go and do, which is when it can really mess up, but it has multiple loops around it to verify based on the action you asked it, is this actually an appropriate action to take?

1:23:07But ultimately the responsibility is on the human. When you tell it to send a Slack message and that Slack message is off, the thing that I am really keen and I keep hammering with our own team, the thing that I absolutely do not want to see is people blaming Rebel, blaming the agent. It's like, well, Rebel wrote this message in a bad way, sorry. It's like, no, you told it to send the message. You didn't check the message. You take responsibility for it.

1:23:38Hala Taha:A human at the helm. Exactly. The same for an employee. If you have an employee that does something bad, if you're anyone familiar with building companies, the last thing you want is this kind of blame culture where you say, oh, well, sorry, really sorry for what happened there. It's like, I had this employee in my team and they just really messed that one up. It's like, no. It's like you as a leader are responsible for what happens in that team. And if you don't take that responsibility, your team will always be limited to routing everything through you. And that's why I think it's such an important bit, both in terms of how we teach people to interact with AI.

1:24:14It's they are accountable for it. And also to make sure they're not becoming the bottleneck. And this is when we think about setting people up for success in the future, constantly thinking through what is the system I want to build that makes me comfortable giving the AI as much leeway as I am willing to give it. That's probably one of the biggest things that we try and help people understand. And not everyone will draw the limit in the same way, which is fine.

1:24:42Hala Taha:Is there anything in 2026 right now that you absolutely will not delegate to AI? The human connection is a really, really big piece. There's a reason why we're doing this in person. Yeah. There's a reason why almost every single executive briefing session that we do is in person. It's because a lot of this AI transformation is actually emotional. And emotional is not something that AI is. I mean, it can put the words in place, but it can't really make someone feel better about it. Or at least it's harder. It's a fundamental human experience that we're going through. And then the other bit is agency.

1:25:20I won't let AI just self-execute on plans within the business without me. So there are ways technically that I could now go and set it up to autonomously start executing on basically whatever things needs to get done. I am spending my time figuring out where do I apply my own agency and how do I build the system in a way that I maintain agency over what happens and then take the most advantage of the ai from within that but so not letting it act without me having asked and then second having that human connection and that human experience is where i would put all of my time and hopefully i mean this is an interesting one because it's probably counter to definitely counter to how people would perceive me externally it's so interesting because I'm so absorbed in some of the technology.

1:26:15One of the things that shocked me at the time when we were building Super Awesome was interesting. People sometimes think of me as somewhat robotic because I spend a lot of time with the technology and I'm very logical, but I care a lot about the people that I work with. And so one of the things that using AI allows me to do is try and spend more time actively with people and making sure that I make more time for exactly that piece. So human connection.

1:26:51Hala Taha:Okay, so as we close out this interview, because we've been talking for a long time, honestly, I feel like we need a round two because as you saw the prep brief, I have 50 more questions to ask you, more detailed. I think that belongs more in like a part two. So we'll definitely have to set that up. But I wanna talk about tool tourism, right? So this is something I think you might have coined where people are just trying every tool. What's the problem with tool tourism and how should we think about picking tools that we work with? I wouldn't quite frame it as a problem. It's a situation. Exactly.

1:27:27It's definitely things that you need to watch out for. So I'd say on balance, tool tourism, meaning that you're actually interacting with the tools, already puts you ahead of most people who are not even interacting with them. So that's what I mean with it's not necessarily a problem. It is definitely, it would prevent you from getting to the real return on the investment of the time that you're putting in. And I think this has also changed in the last year, which is that the technology in the last year has really turned a corner where it is now able to produce real work. if you just sit at the level of tourism you're just superficially trying at all you don't really try and go deeper you run the risk of never going deep with any of the tools and then never actually getting to the behavior change and if you're superficially looking at chant gbt and then claude and then copilot and gemini and you're kind of thinking oh yeah i try all of them out and i kind of do these things and i compared them between each other great but if you didn't go deep with any of them, you actually never got to the result or the return with any of them.

1:28:35So what is important is that you go deep with a few. Now, that doesn't mean it's bad to try the others. It's always good sometimes to compare and contrast, but don't let it take away from you being able to go deep with one because otherwise you just won't understand what's possible. It's kind of like if you had 10 different operating systems and you tried all of them, like, I mean, right now, Now we really only have Mac, Windows, and Linux, but imagine you had 10 of them. If you change that operating system every week, you would never feel comfortable with your machine.

1:29:07Hala Taha:Yeah, that's true. And at some point, you just need the machine to sit in the background. It's there to help you do work. So whether it's ChantyBT or Claude or something else, or Rebel becomes the operating system that you live in, it is important that you give it enough time to really go deep. Well, you've toured a lot of tools. So I want to end with a quick fire segment on the best AI tools. Okay. So best AI tool for building presentations quickly. Gamma. Best AI tool for meeting notes. Fireflies at the moment. Best AI tool for research. Gemini's deep research. Best AI tool for brainstorming new ideas.

1:29:50Chanty BT.

1:29:51Hala Taha:Best AI tool for thinking and communicating clearly. Claude. Best AI tool for graphics or video clips? Tie between Kling and VO3 or 3.1. Best AI tool for building apps without coding skills? Replit. I agree. Best AI tool for coding with coding skills? Droid. Best AI tool for learning faster? ChantyBT. The AI tool that more people should know about? Rebel. I agree. the ai tool most people are currently using wrong all ai assistants all ai i was gonna say all ai assistants from copilot to chat gbt to claude to yeah number one problem is people use them as search engine replacements and they just don't work that way yeah okay so last bit is about claude versus chat gbt so what does claude do better and what does chat gbt do better so claude makes it easier to talk to it like a human in a way it actually talks to you in a more humane way it's it's writing is much less mechanical um it's more elegant in a way it is more human yeah i agree chan chubiti is really strong at reasoning though and so when you need to crunch through a logical set of steps, ChatGPT can be better at it.

1:31:21Also, ChatGPT was first, and their ecosystem is more evolved. Although Anthropic with Claude is starting to move the need. Yeah, it's kind of really, yeah. It's really getting there. But for a very long time, and still, like, one of the features that ChatGPT has that Claude does not, which is fundamental, which we didn't even get to on the weekend, and I just realized we should have done that, is the ability, so ChantyBT has a canvas, which allows you, when you're brainstorming, you can put it in a document and then you can annotate the document, but you can basically go back and forth with the AI in the document.

1:31:55It's almost like having a Google Doc, but with AI using change suggestions and comments as it goes along. And when you're thinking about brainstorming something, often my flow would be actually start some of it in ChantyBT, go through, prepare the document, and put it back into Claude when I want it to sound more human. But so that would be, yeah, another way that they compare and contrast.

1:32:18Hala Taha:If somebody is listening today, they haven't really started building, maybe they've used ChatGPT loosely because everybody has at this point, but maybe they haven't really like built any systems yet. Would you say ChatGPT or Claude? Claude today, yeah. Because Rebel uses Claude as one of the main, and I feel the difference in quality is like so much better that I have stopped using ChatGPT nearly as much. Okay, if you had to delete one forever, ChatGPT or Claude? Definitely ChatGPT. There we go. Claude is the winner. Joshua, this has been such an incredible interview. I end my show with two questions I ask all of my guests.

1:33:01Hala Taha:The first one is, what is one actionable thing our young and profiters can do today to become more profitable tomorrow? I mean, that is the perfect question right now based on this conversation is just whatever you do, lean in on giving yourself the tools to understand how to use AI. Whether you do that with us at Mindstone taking the competency program or do it yourself or talk to your company about what they can make available to give you the space, whatever you do, make sure that every week you spend some time figuring out how deep this rabbit hole really goes. And what would you say your secret is to profiting in life, especially with all these changes going on?

1:33:47Right now, it's genuinely that I feel for the first time in my life that I'm living the future, which is a very weird position to be in. but that's why we're having this conversation today is that I feel that what I'm able to do now most people in the world will be able to do in the next two or three years and everyone interesting enough everyone has a choice and they can do the same it's not even that I'm special in one way or another it's just that I leaned in before anybody else did And so that is the secret sauce today.

1:34:30Hala Taha:Yeah. I feel like just so lucky that I was able to go on the AI retreat. I told Kate, like, I feel like it was fate that we were there. And now we're going to take 60 employees on this journey with Mindstone to teach them how to use Rebel and to, you know, understand AI. And I just feel like it's really going to help my business stay competitive, thrive. it made me realize how at risk we are if we don't do this. And so I'm just so thankful that we've met. And I'm grateful that now my audience gets to hear everything about Mindstone. Where can everybody learn more about you and Mindstone and everything that you do?

1:35:09So very simple. Go to Mindstone.com. Easy. And so we have the AI competency program. Everyone can enroll, whether it's individuals, small teams. And if you're a company that is interested in kind of taking your whole company through it, there's a contact form. So we basically have it for individuals and for companies, and then we can have a conversation, figure out how far we can go.

1:35:32Hala Taha:Amazing. I'll put all those links in the show notes. Joshua, again, it was such a pleasure. Thank you very much for having me. A huge thank you to Joshua for pulling back the curtain on what's truly possible with AI right now. That was definitely the most practical and executable episode that I've ever had on AI. This conversation genuinely shifted something for me, and I hope it did for you too. One of my favorite insights is that most people are using AI completely wrong. They're using tools like Chachapiti and Claude, like search engines. Joshua challenged that mindset. Instead of asking AI for quick answers, treat it like a smart teammate.

1:36:08Hala Taha:Give it context. Ask it to ask you questions first before giving you an answer. When AI understands the full situation, the quality of your ideas, strategies, and decisions improve dramatically. Another big takeaway is finding the coding equivalent in your job. Every profession has a repetitive task that eats up time. It can be updating spreadsheets, doing research, drafting emails, or organizing information. Joshua's advice is simple. Identify that task and start experimenting with AI to handle it. When you automate the repetitive work, you free up time to think strategically and operate at a much higher level.

1:36:44Hala Taha:And finally, start building systems that work for you. Joshua talked about creating skills, which are repeatable workflows that AI can execute. Instead of doing the same task over and over, teach AI the process once. Whether it's research, follow-ups, or content prep, hours of work can suddenly just happen in minutes. That's when AI stops being a novelty and becomes a real competitive advantage. The opportunity with AI right now is massive, but it's not going to stay open forever. The entrepreneurs who embrace this fully are going to get a moat around them. They're going to be untouchable. I want that to be you guys.

1:37:20Hala Taha:You're already ahead of the curve by just listening to this episode. Now go take action. If this episode planted a seed in you and you feel more motivated to use AI than ever before, then water that seed by sharing it with somebody in your life who also should be interested in AI. Your only homework today is to pick one thing from this episode and actually try it this week. That can be talking to AI instead of chatting with AI. That can be trying to use a new tool like Claude or any of the other tools that we mentioned in the episode. And then come tell us how it went on Instagram at Yap with Hala or LinkedIn by searching for my name.

1:37:56Hala Taha:It's Hala Taha. And if this episode was worth your time, a five-star review on Apple Podcasts goes a long way. Those reviews help us reach more ambitious people just like you, and they mean the world to me. I personally go check to see my new reviews every single day. I'm obsessed with checking my new reviews. So please drop us a five-star review. And if you guys want to watch the full conversation, we did record this episode in person so you can find it on YouTube or Spotify video. Just search up Young and Profiting Podcast on YouTube and on Spotify, you can just watch it as a video. This is your host, Halataha, aka the Podcast Princess, signing off.