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those people who could write really, really fast didn't thrive in the age of the typewriter, However good you are at that skill that you have mastered.
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AI can now do instead.
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Doing it better, faster, it, you're not gonna win.
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The people who can master the typewriter, they're the ones who win.
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we believe that the, limit of learning in organizations is going to be set by the individuals in those organizations.
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LQ can be taught, it can be learned.
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And it is going to be absolutely essential to every single worker, I think, in the new economy.
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for any entrepreneur, this is just a huge opportunity.
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For anybody.
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so I just think, ultimately That, that's got to be the kind of final thought,
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Hello and welcome to Altogether's Three Things and our latest in our Ask the Experts series.
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Today's an exciting one for me because it's a return visit to, to the hot seat, for Claudia Harris.
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Welcome, Claudia.
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Hello, to be back.
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Claudia engaged me hugely in our podcast, what was it, a year, two years ago?
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A year and a half ago?
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a while ago.
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Talking quite a lot of ethics, quite a lot of undiscovered talent issues, blind recruiting how people should hire bravely and It was thoroughly enjoyable.
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And you've contributed to so much of Altogether as one of our volunteer advisors.
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You spoke at our very first summit.
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And you're going to speak at our next summit.
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Which is coming up soon on AI.
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And the reason we're here is because Makers is thinking a lot.
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About AI and how it is going to transform the world of work, I guess, But can I ask the first question?
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How do you personally use it?
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so very clearly massively time of everything that in your using And I figuring how to do so AI writes my speeches for me.
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Does it?
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So when you, when you speak to
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uh,
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when you speak at the event it'll be Yeah, unfortunately, I do, you know, I will, I will tune the response, but if want to create any kind content at any kind scale, I'll always use chat GPT start me off on that.
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And I will then refine and improve it.
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I do think that we have to kind of move away from writing and towards prompting and terms of content creation.
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Whether that's speech creation, presentation creation, email creation, GPT both creates fed along form and can provide summaries content, and I think it needs to be done, used for that.
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But just understanding stuff, right?
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If there's anything I understand that I need to understand quickly for my job, I will use GPT to me that.
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I will ask to explain, re explain, use analogies, whatever is kind of most useful persona.
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We, the reason we're doing this event, as you know, because you are now partnering with us on it.
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Thank you very much, makers.
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Basically, for most CEOs and founders, I think the, the hype that is out there makes them think they may be behind the curve.
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And certainly when I first started talking to you about it, I was going, Oh, are we too late with this event?
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And it didn't take long to realize actually we may not be quite that far advanced in terms of how business is applying generative AI into its day to day operations.
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What's your view?
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Where are we on the journey moment?
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there's this phrase from Ernest Hemingway about bankruptcy, not about AI I should say, in which he it happened in two ways.
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Gradually and then suddenly.
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And think a really useful phrase thinking about what's going to happen really, and I'm really particularly the advent LLMs because LLMs is a kind you know, part a continuum decades of work in terms of AI and machine learning.
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But do think they have hit the world in a way was at scale much faster than people prepared for to take an individual government's companies.
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caught them unprepared.
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And I that's big shift that we're talking about particular.
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But think, yeah, I think gradually and then suddenly, I think what's happening right now is that there are sort of three reasons why companies struggling to make use of of it One concerns around IP privacy, but even that debate is moving so quickly, right?
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With the new kind of enterprise versions of a lot of these tools, some of those concerns have already started to evaporate, but And just so we are clear, this is a concern that whatever I put into, say, chat G B T, but there are many other LLMs out there.
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Becomes part of the model and could be spat out back.
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Yeah.
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And that is true.
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mean, true, I think, you know, the extent to which it's a super high risk, depends on what we're talking from a content You of
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kind of, you put your
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interview notes about an individual and that individual kind chat GPT themselves and finds themselves.
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I think that there's, you know, more or less risk with this.
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it's an incredibly complicated system, but that,
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And there are no, I've heard no examples yet of someone who's talking to chat GPT and they've been told some highly confidential piece of information, which given that the whole planet is using it is surprising.
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But, but I think with that, but that's a fundamental and the enterprise solution will cost me, but it, it basically allows me to keep my data separate from the the model.
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Yeah, so the model's not trained on what you put into it.
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And then the other concern, of course, is that you're going to be breaking IP.
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by using content that's ripped off other people's content.
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And that's the kind of second concern and the kind of concern about could you end up with sort of huge liabilities that you don't know you're creating?
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So IP and privacy kind of one bucket of reasons.
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I think that companies are.
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Cautious to engage.
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I think a second reason is, is just tool mastery, like simply, do we understand what the tools are and how to use them?
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That's kind of simple Apart from the fact that every two minutes there's a new application built on top of the LLMs.
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So how do you master something that is changing so which we will, we'll talk a little bit about in a second.
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And then the third thing, I think this is a really interesting one is people struggling to connect the tools to the use case.
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Yes, right.
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Which, I mean, I spent, as you know...
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We spent a long time trying to figure out what use cases to, to sort of highlight for this event, and it's quite tricky.
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And so I think, you know, kind of obviously with anything that you ever do.
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In life, in business, in any situation, what matters is the outcome, what you're trying to achieve, what's your goal, and the tool is only useful in as far as it supports you with the goals and outcomes that you're aiming to achieve.
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And so, to be kind of tool oriented doesn't make sense.
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You've got to be outcome oriented, and then you've got to figure out how the tools support the outcomes.
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And I think lots of companies struggle with that.
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So, you know, people can go and write a poem with GPT, but can they really use it, as we've discussed, to compress their kind of normal workflow?
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a gap Now, we're not going to spend a lot of time on use cases today, because that's...
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What the event we're putting on is doing and we are showcasing some genuine use cases.
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We've already announced that Greg Jackson is speaking alongside you to talk about how generative AI has transformed customer services at octopus, which given how good their customer services was anyways.
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It's pretty exciting, but we've got, we'll have lots of conversations about use cases at the event, I'm really interested though in this idea that you should start with the problem, which, you know, all the CTOs we've spoken to have been very firm on.
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Yeah.
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Isn't there also just a point to play?
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To learn?
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I mean, I have, I'm not trying to solve anything at the moment.
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I'm, you know, I'm just figuring out what I can do.
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Having believed it wasn't possible to build a chatbot on my own because it was quite technical and it needed, no, there's plenty of businesses out there who say, what do you want to train your chatbot on?
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You feed it documents and away you go.
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So I've created all sorts of weird chatbots, but not for any goal here.
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so I do think that's the problem.
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I think that's what people do challenge these tools on.
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And I think when we think about the kind of connection of tool to use case, We think there are two ways of thinking about that.
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So we think there are existing outcomes that you already, like, need to deliver for your work.
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and the way to think about this is, you know, how do you spend your week?
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What is the majority of your time spent on?
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And how do we use GPT to kind of compress the time it takes?
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Or, one of the large language models, sorry, really obviously not GPT every time we say GPT, everybody should just hear, or any of the other large language models.
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Yes, and I should really say that, but the, but the first question is, how do you use these models to compress the time it takes to deliver the same outcomes or indeed improve it?
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And we'll talk about that in a second because I think they do both.
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But that's something that, you know, everyone should be working through.
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Like how do you, their own personal yes.
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And this is a lot of what we're thinking about at Makers.
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And this is a lot of what our training is dedicated to, which is how do you basically make your workflows more.
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efficient?
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so that's about delivering the same outcomes with fewer hours of input.
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The second kind of use case is that we think that there are new use cases that you are now able to deliver that you couldn't deliver before.
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And for me, change the world now.
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well, and I think this is also about an individual's, you know, it's just an extraordinary thing, right, that you can kind of master a skill that perhaps, you know, For 25 years, you have felt intimidated to try, and you had some bad experiences with Excel, and you don't feel confident in terms of, you know, data management, data creation, and code interpreters, a completely different kind of process.
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and suddenly you are confident managing large data sets, delivering complicated data outcomes.
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You know my view on this one though.
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It takes a little bit of time.
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No, I don't think it works.
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Do you love it.
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No, I don't think Code Interpreter, which is the old word for just ChatGPT now because they don't call it Code Interpreter.
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But basically you can upload an Excel spreadsheet into ChatGPT 4 and you can start manipulating data and analyzing it.
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But I liken it to hiring a double first from Google.
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Cambridge engineering degree, brilliant smarts, but no business sense because the stupid mistakes that get made along the way that you can't see because there's a black box involved.
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I, I just, I do have too much time on my hands, right?
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Cause I, I had a problem and I chose the wrong solution.
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My problem was I needed to analyze some data and.
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My Excel on Mac license had run out or something and I thought, well, you know what, rather than build a pivot table myself, I'll get chat bt to do it a month later.
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I still haven't got it to, to work.
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so I think, and I think this, this is a tool used, right?
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And some of these tools are still emerging and kind of not, not, yet.
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but you can feel right from that, that that is going to be a very powerful, different way of delivering results that people...
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It's going to change within months.
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And, you know, the same with creative output, right?
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People for whom they can visualize a creative output, but they've not, you know, fine.
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how to use videos, don't know how to, you know, don't know how to create I mean, this video I'm taking of you right now won't have a nice white brick, won't have a nice white brick background.
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There's all sorts of Avatar.
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Right, exactly.
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Yeah, I'll be unrecognizable, that's what I'm hoping for.
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But the, but the second kind of use cases, the things that you felt you couldn't do, which over time you were going to be able to do.
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And that the things that perhaps you asked your colleagues for help with, or you outsourced to colleagues or you outsourced across departments that individuals are going to be able to do, which is going to have an interesting effect on how companies work, you know, reduce complexity, maybe require less kind of.
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Cross functional working.
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It's going to be interesting when you are able to do things that maybe you, you wish you could do, haven't quite trained yourself to do, can suddenly do yourself easily.
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So these are the two.
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So when you think about these sort of three things that we need kind of companies to master.
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Getting rid of the concerns about IP and privacy.
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Putting the guardrails around it.
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Figuring out how you're going to manage that.
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Tool mastery, but then ultimately the use cases both compressing the amount of time it takes to deliver existing use cases and figuring out on an individual basis how to deliver new use cases.
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That, That, that for us is a kind of roadmap for companies to start to really get some, some really interesting mastery among their people.
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And this, you know, you said, they're changing all the time, how are organizations going to keep pace?
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Yes.
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So at Makers, we believe that the kind of.
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the, limit of learning in organizations is going to be set by the individuals in those organizations.
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That companies are going to struggle to interpret the different, you know, figure out what's going on across the different tool sets and translate that into learning programs and disseminate that to their teams will not be able to move.
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It won't be able to move fast enough.
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So you're going to rely on people to learn fast.
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And so we think that from a kind of, one of the most important characteristics of this new revolution is going to be the degree to which people have learning quotient, right?
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So we've always talked about Intelligence quotient then it was emotional intelligence.
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Yeah, IQ EQ for us LQ Is LQ, have you made it up, or is it actually a thing, LQ so, so quantum black, I think, is it back where we got this idea from, which is the McKinsey's Sort of group.
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group.
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Sounds such an evil name, like it's a Bond It's a great name, But the, but the, so, but what does this mean for individual, for companies?
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If companies, what does this mean for individuals?
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Individuals now need to be right at the edge of learning.
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Make learning one of their most kind of kind coveted characteristics.
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Companies need to recruit people who have high LQ.
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People need resilience because that pace of change is going to be...
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where And so resilience and LQ are going to be key.
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And then we need to help equip people with the ability to understand how to manage the IP and privacy, use the tools, and then deliver the tools to deliver use cases.
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And for us, that combination of things, LQ and resilience, and then the ability to understand how to use the tools and deploy them against use cases.
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will make somebody a truly effective user of this new technology And the way we think about this is that that person will then become what we're describing as a centaur so a person who is which is a half half machine, Half you.
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So the original kind of, so the center, obviously, originally from kind of mythology is a part creature, part human combination.
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In 1998, Kasparov coined it to describe part human, part machine, the combination that could beat all others at chess.
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And we think that that kind of, and so it's a kind of notion of the integration of human and artificial intelligence.
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And I think that is what will make people thrive in this new economy.
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And that if people are thinking about how to themselves thrive in this quite uncertain world.
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It is to do with building the LQ, building the resilience, feeling confidence in the IP privacy issues, feeling confidence in tool mastery, and then figuring out how to deploy these tools against these cases.
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Both existing ones to do their work faster and potential ones to unleash a whole bunch of capabilities that today are unattainable.
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And that for us is what the central worker will look like and does look like.
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And we think we're now entering the age of...
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The center economy when really that combination of characteristics is what will define success at an individual level and an organization so that have people like that in them are going to be the ones that will succeed.
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So, that is the clearest, I mean you've talked to me a little bit about this before and you got me at hello frankly, I think, with just the first two points about LQ and resilience.
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But, let's dig into this a little bit if we can.
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we
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First of all, what are you saying here?
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That.
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If you as an individual or you as a organization want to compete in this new economy, succeed, whatever the definition, not be left behind there's actually five things then, right?
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Develop your LQ, which is, I don't know.
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I don't know how I'm built.
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It is.
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We'll come back to that.
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Develop your resilience, come back to that.
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This then IP learn the tools and effectively, can I use the word innovate for the last one, the use cases one, because that's really what I'm getting excited about, which is changing, you know, using all of that then to, to innovate the way you do things personally, or the way that the business does things.
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I got the LQ bit.
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Can you improve your own?
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LQ?
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100%.
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I mean, really the makers program for 10 years has been built on the idea of helping people learn how to learn.
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Could you remind people, or tell people what the Makers core product is?
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Because I think we missed that at the Yes, and I should know how this links to what we've been talking about.
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Of course, so makers we have for 10 years Helped diverse career switches to retrain to become software engineers.
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In fact, we we turn them into all kinds of tech areas today But that's been our kind of core proposition We believe that Talent is distributed much more evenly in society than opportunity is and the more that you believe that the more that you believe that the British Education system is not particularly fair the more that you believe that there are thousands millions of people out there who could be software engineers who just aren't in the right place, aren't in the right job and are stuck.
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And we're about finding those people, the exceptional talent and helping them to retrain and get into this incredibly exciting industry.
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And we feel really proud of that, really successfully got some, fantastic clients from Deloitte Digital to Google and and some amazing results.
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You know, people go on to become tech leaders across the, across the British tech scene.
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They have, they get promoted really, really fast.
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That's one of our kind of key characteristics.
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And you have developed in as part of this, just for people who want to go back and listen to our old podcast or do other research, it truly inspiring work around CV free recruitment or whatever we call it, these days, blind recruitment, and you know, lots and lots of good things.
00:17:04.709 --> 00:17:12.209
I don't know how far you've got on it, but you are pushing at the boundaries of truly trying to not judge people by what they've done.
00:17:12.273 --> 00:17:13.564
But what they're capable of.
00:17:13.568 --> 00:17:16.538
I mean, the way you get onto a maker's program is based on your potential.
00:17:16.578 --> 00:17:17.398
We don't look at background.
00:17:17.409 --> 00:17:31.669
It is about your attitude, your aptitude, and the ability to pick up the kind of new concepts that we help people to, like, learn about as part of their kind of, and you were teaching software engineering effectively, predominantly Software, data, cloud, quality.
00:17:31.673 --> 00:17:32.134
all the same.
00:17:32.134 --> 00:17:33.689
To me, it's like Yeah.
00:17:33.933 --> 00:17:34.983
not marketing.
00:17:35.239 --> 00:17:35.878
marketing.
00:17:36.273 --> 00:17:37.804
So what's.
00:17:38.804 --> 00:17:45.253
I mean, apart from the fact that AI is going to transform how software engineers work that's not what the Centaur program is, though.
00:17:45.473 --> 00:17:48.013
So why this shift into the Centaur program?
00:17:48.334 --> 00:17:51.753
So our thing has been transformative tech education, right?
00:17:51.763 --> 00:17:57.433
Transforming people's lives through tech education to give them a kind of different quality of different experience in life.
00:17:57.433 --> 00:18:03.074
And for the first 10 years, you know, we started, we really focused on helping people within the tech space.
00:18:03.608 --> 00:18:05.818
Becomes junior engineers, but that was a thing.
00:18:06.409 --> 00:18:10.979
In fact, three years ago, we introduced a new product, which has been really successful and with one of our clients.
00:18:10.979 --> 00:18:14.209
And that has been about helping junior engineers transform.
00:18:14.644 --> 00:18:16.384
To become engineering leaders.
00:18:16.453 --> 00:18:22.772
So, we take people who are sort of expert engineers themselves, and want to figure out how to become leaders, and we've helped them to go through a new transformation journey to become a leader.
00:18:22.773 --> 00:18:27.648
So, within the engineering space, you're already in sort of softer skills at that point anyway.
00:18:28.364 --> 00:18:43.432
And they're both, they're both, really about individual transformation, like the transformation to become a junior engineer, the transformation to become a leader, and for that we use the case method that kind of pioneered in the business schools, all about bringing to life real examples from Fellow engineers of, you know, how do you lead quality at scale?
00:18:43.442 --> 00:18:48.532
Like what does it look like to solve those sorts of problems, which is different from the problems of a junior engineer?
00:18:48.742 --> 00:18:56.413
So within the engineering space, we already feel like our absolute expertise is on transformative educational tech education journeys.
00:18:57.127 --> 00:19:05.188
Now, in the world of LLMs, the entire population needs to go through a transformative technical education journey.
00:19:05.387 --> 00:19:05.718
right?
00:19:06.557 --> 00:19:08.587
Everybody now needs to become a centaur.
00:19:10.228 --> 00:19:20.238
The sort of simplistic but I think startling thought is, those people who could write really, really fast didn't thrive in the age of the typewriter, right?
00:19:20.268 --> 00:19:22.778
However good you are at that skill that you have mastered.
00:19:23.762 --> 00:19:25.182
AI can now do instead.
00:19:25.532 --> 00:19:27.923
Doing it better, faster, it, you're not gonna win.
00:19:28.462 --> 00:19:31.423
The people who can master the typewriter, they're the ones who win.
00:19:31.432 --> 00:19:33.682
And it's, the same logic now applies.
00:19:33.942 --> 00:19:40.923
In fact, skills from the past may be an encumbrance to you if you try and hold on to things that you've learned, that you feel protective of, if you can't.
00:19:41.005 --> 00:19:48.333
get rid of those skills, you know, that's, that could be, that could actually hold you back compared to someone who comes at this fresh, and this is the, and this is where people will leapfrog, right?
00:19:48.373 --> 00:19:50.942
They'll have like massive, we've always spoken about leapfrogging technologies.
00:19:51.232 --> 00:19:52.272
Individuals can now leapfrog.
00:19:52.659 --> 00:20:00.888
The reason it links to the Maker's Core mission, right, is that individuals now have to go through this transformative technical education journey to become a centaur.
00:20:01.068 --> 00:20:11.368
And so for us it is simply applying the kind of Maker's philosophy that we've always applied within the technical space and the software engineering space and the engineering space to the broader British economy.
00:20:11.594 --> 00:20:16.124
Well, it needs to be in every single school, university, technical college.
00:20:16.213 --> 00:20:20.023
I mean, how are you gonna, nevermind we're not here to talk about how you're gonna deliver
00:20:20.239 --> 00:20:20.489
no
00:20:20.713 --> 00:20:23.461
no global impact but it relates to the LQ point as well.
00:20:23.461 --> 00:20:28.092
So our whole thing has been transformative technical education, but absolutely the core of it.
00:20:28.152 --> 00:20:32.791
The thing that has made our makers succeed is LQ and it is learnable and we teach it.
00:20:33.142 --> 00:20:35.721
And it's all about how do you deal with.
00:20:36.001 --> 00:20:40.801
Problems, ambiguity, things that you have to learn when you encounter them at work.
00:20:41.201 --> 00:20:53.344
And it, the whole the whole thing that we focus on at Makers is in those moments of ambiguity and challenge, how do you manage your own well being mindset and emotions as regards that experience?
00:20:53.344 --> 00:20:55.433
Do you have a kind of flight response to it, or do you have a...
00:20:55.923 --> 00:21:00.364
You know, curious, calm, relaxed engagement with it.
00:21:00.983 --> 00:21:04.074
How do you think about solving that problem if it's not a problem that you've seen before?
00:21:04.074 --> 00:21:07.124
Like, what are the tools at your disposal to sort of self educate?
00:21:07.153 --> 00:21:13.564
And the entire course is about solving the problem yourself, which can feel very uncomfortable.
00:21:13.574 --> 00:21:18.913
You know, if you've got a coach there who just keeps saying, well, try again, think again, have another go, it can be frustrating.
00:21:18.913 --> 00:21:23.003
But the point of it is that in the real world, you don't have a coach giving you the answers.
00:21:23.394 --> 00:21:47.864
You need your to be your own coach saying you've got this you can figure this out find a way So it's this combination of like knowing where to go to try and self educate to find the answers and having the resilience And the emotional well being and the kind of emotional tools to manage your own response to ambiguity And not knowing how to move forward the combination of those two things is at the heart of the makers curriculum It's the growth mindset logic And it is what our clients love about makers.
00:21:47.953 --> 00:21:49.884
Curious, collaborative problem solvers.
00:21:50.074 --> 00:21:52.364
You give them a difficult problem, they find a solution.
00:21:52.374 --> 00:21:55.273
And they, and they cherish, they cherish that opportunity.
00:21:56.193 --> 00:21:57.453
Feedback's at the heart of how we work.
00:21:57.473 --> 00:21:58.743
People are always looking to improve.
00:21:58.743 --> 00:22:01.973
So, LQ can be taught, it can be learned.
00:22:02.003 --> 00:22:07.753
And it is going to be absolutely essential to every single worker, I think, in the new economy.
00:22:08.317 --> 00:22:12.655
I'm gonna come back to your five things that jars with my three things world.
00:22:12.655 --> 00:22:21.546
But anyway, but in terms of I'm gonna come to a second in terms of how you transform bigger organizations and, and by that I mean sort of mediums size and above.
00:22:21.789 --> 00:22:30.119
But, in these entrepreneurial businesses where we have already built LQ, because that's what's created this entrepreneurial business.
00:22:30.119 --> 00:22:33.140
There's LQ abundance in an entrepreneur, I'm talking.
00:22:33.539 --> 00:22:35.049
resilience, abundance.
00:22:35.144 --> 00:22:48.085
This was the mean, this was the rationale for having our event, was to make sure that our members are up to speed on the tools and the use cases and starting their journey so that they're not left behind.
00:22:48.424 --> 00:22:59.994
And I think it's, you know, the entrepreneurs, frankly, Have an advantage at the moment in the entrepreneurial organizations have an advantage over big businesses, but let's talk about sort of larger companies.
00:22:59.994 --> 00:23:06.204
And I've got some in mind that you know, just 150 people rather than even the thousands and thousands of your clients.
00:23:06.905 --> 00:23:11.205
The central program isn't suggesting or your makers approach CEO.
00:23:11.270 --> 00:23:13.310
every single person from the CEO down or the
00:23:13.740 --> 00:23:21.691
Down or the board down needs to go through the central program to enable an organization to become more innovative in a I or are you?
00:23:21.721 --> 00:23:23.165
Is that the only way to do No.
00:23:23.226 --> 00:23:30.625
So I think that, you know, as always with these sorts of big transformation programs, there are layers of change that you implement in an organization.
00:23:30.631 --> 00:23:35.935
You need to start ultimately with a kind of alignment at the most senior levels around some of the more difficult or.
00:23:36.240 --> 00:23:37.861
Or naughty questions, right?
00:23:38.030 --> 00:23:43.730
So so things like privacy, things like security things like the sorts of capabilities that you do want to unleash.
00:23:43.730 --> 00:23:45.820
You need to have a kind of organizational framework for it.
00:23:45.901 --> 00:23:47.540
Agreed at the most senior level.
00:23:47.911 --> 00:23:50.911
I do think that senior leadership should go through the central program.
00:23:50.911 --> 00:23:56.155
I think with any good program when I, you know, mean, you know I'm knocking on the door saying, can I please, can I please, but.
00:23:56.471 --> 00:24:02.721
you know, some of the best clients I work when I used to do a lot of transformation work at McKinsey and the best CEOs.
00:24:03.010 --> 00:24:08.010
If it's for the front line, they go through it themselves because ultimately that's the way you role model it and the way that you know what you're trying.
00:24:08.421 --> 00:24:11.861
You check that you're delivering the program that you want to deliver for your organization.
00:24:11.861 --> 00:24:16.240
But ultimately, you know, we would see senior leaders going through it and then we would see change leaders going through it.
00:24:16.250 --> 00:24:18.441
And this is a train the trainer kind of program, right?
00:24:18.441 --> 00:24:26.151
You need to have key people throughout the organization who are then enablers of the people who work with them for them and across their peers.
00:24:26.431 --> 00:24:27.280
to to do this.
00:24:27.280 --> 00:24:38.351
And of course, what's kind of wild now with, with LLMs is that you know, you can use prompts to make incredibly tailored versions of this program for rollout in the organization, if you think about it.
00:24:38.421 --> 00:24:40.250
Because, you know, How Well, How are you going to protect your IP?
00:24:40.330 --> 00:24:41.371
Let's not worry about that just yet.
00:24:41.371 --> 00:24:41.641
We love online.
00:24:41.661 --> 00:24:41.990
IP?
00:24:42.181 --> 00:24:42.411
That's not where it's at.
00:24:42.411 --> 00:25:02.836
well, we, so there'll be a lot of online Resources for this is that always are in our experience this sort of thing the reason that it's really powerful to do it as a kind of change program where it's Interactive when it's really engaged when it's kind of in cohorts going through certain sort of and Programs together as we do it makers is you just get huge levels of completion and engagement, right?
00:25:02.836 --> 00:25:10.881
You know, we get everyone's free makers everyone and it's a completely different thing when you're trying to do this on your own I mean, I True of a lot of, of online education.
00:25:11.050 --> 00:25:29.651
I'm, I'm aware of time and I'm just going to come back to my question though, which is if you are running a larger organization and I'm not even that bothered by the big corporate, so a medium sized organization, it can't wait, surely, for every single member of my organization to have gone through this program.
00:25:29.651 --> 00:25:39.266
So who am I choosing to put through it first and how are the, how are we actually innovating change in our You want to start with the sort of management team as your starting point.
00:25:39.506 --> 00:25:43.945
And then, as always, it's your change leaders and people who are skeptical.
00:25:44.155 --> 00:25:51.076
You know, it's kind of, as with any change program, you want to get the kind of the train the trainer approach.
00:25:51.441 --> 00:25:59.851
Focused on the people who are going to you want, you want, the ones who are already showing, they've got the LQ and resilience along with the most cynical people.
00:26:00.320 --> 00:26:01.090
cynical people.
00:26:01.090 --> 00:26:01.371
yeah.
00:26:01.661 --> 00:26:06.280
And you know, I, I, it's always in them that you get the real champions in the end.
00:26:06.800 --> 00:26:08.115
I mean, your day one on this.
00:26:08.115 --> 00:26:08.816
You're you're out.
00:26:09.185 --> 00:26:10.726
You're out implementing this.
00:26:10.726 --> 00:26:13.645
I think everybody in your office is currently doing the central program, right?
00:26:13.675 --> 00:26:17.215
And I'm sure you've got your first clients booked in hungry for this.
00:26:17.546 --> 00:26:24.576
I'm I'm really going to be intrigued as to how change happens in organizations who have been trained around centers and who haven't.
00:26:25.185 --> 00:26:29.615
I just think it's mad in terms of how fast everything is Yeah.
00:26:29.615 --> 00:26:34.135
but I do think then again you do have this graduating suddenly thing, right, which is, I think what, You know, whereas we might...
00:26:34.996 --> 00:26:41.296
I think it's I think whereas, you know, in the first three months we all sort of went into like, my God, you know, the world as we know it is over in like six months time.
00:26:41.726 --> 00:26:45.796
It's, it's sort of not, I think what's really interesting about it is it's like a kind of global...
00:26:45.942 --> 00:26:47.173
Race, right?
00:26:47.292 --> 00:26:52.692
Like we've all been given this thing and then everyone's been told like go compete and let's see who's going to win now.
00:26:52.702 --> 00:27:05.542
And And it's something really pure about that and every kind of company everywhere is trying to I, I think it's quite scary and at times I sit there and go, maybe I'm just too old for this one, I'm gonna watch it Yeah, but you, that's not an option and that's the problem, right?
00:27:05.542 --> 00:27:10.393
And I think that is why a lot of people sort of went whoa, you know, all this change coming so fast, am I ready for it?
00:27:10.833 --> 00:27:17.403
but the, but I think the gradual and sudden thing is that, you know, The future is being written in a million workplaces right now.
00:27:17.893 --> 00:27:24.452
And across the world, like, somewhere someone is doing the thing that it's ever will be doing in 3, 6, 9 months time.
00:27:25.887 --> 00:27:35.424
I think one of the things that will happen is that, probably Octopus is a great example of this, there are companies that are really pushing the limits of this technology, and they're trying to work out what they can do.
00:27:35.424 --> 00:27:37.734
I mean, customer service is definitely one, marketing is one.
00:27:38.144 --> 00:27:46.325
You know, how far you can take this, what are the risks, what are the opportunities, and I think there will be a moment, and I almost thought it had happened actually when we had the announcement from Octopus and BT in the same weekend, do you remember?
00:27:46.704 --> 00:27:47.214
About jobs.
00:27:47.565 --> 00:27:49.598
There'll be a moment when sort of a firing gun will be started.
00:27:49.736 --> 00:27:53.846
sounded by a couple of companies that say like, this is now how we're doing customer service or marketing.
00:27:53.996 --> 00:27:54.355
Yes.
00:27:54.625 --> 00:27:58.173
And then, everybody will be really rushing to follow, right?
00:27:58.185 --> 00:28:02.605
But I think in customer service it's almost, has happened, because if you look at all of the...
00:28:02.893 --> 00:28:30.637
Providers of software for customer services, they've all built the AI copilot and okay, there'll be different levels of skills and capabilities of those, that tech and all the rest of it, but it's, it's, it's there and this is part of the bit that, you know, we still got to work out how much is the everyday user going to see this change other than in a different way of working in and the tools that they use you know, You don't need everyone in the organisation to innovate.
00:28:30.982 --> 00:28:32.022
How things are done.
00:28:32.022 --> 00:28:50.272
I mean, the applications are getting better and better so that you don't take, take my problem with chat GPT and Excel analysis and now look at Excel with copilot, which I haven't been able to play with yet, but I've seen videos of it and it solves my problem right there because I can see everything that's going on and suddenly it doesn't.
00:28:50.505 --> 00:28:56.134
You know, it doesn't feel like such a big jump for someone to become AI proficient and analyzing data.
00:28:56.345 --> 00:28:58.255
the tools themselves are so intuitive.
00:28:58.555 --> 00:28:59.914
And I think, you know, and that is right.
00:28:59.914 --> 00:29:09.250
I mean, I think, you know, my sort of final thought on this is, you know, it is, we have a whole bunch of sort of visiting professors who work with us on this, and one of them a, a brilliant founder who's just set up a, a, a real estate AI company.
00:29:09.560 --> 00:29:17.560
And what she kind of brings to life is that, you know, if you think about, kind of, previous technological revolutions, what they do is they require us to kind of adopt structured data entry, right?
00:29:17.560 --> 00:29:20.500
You know, you're like putting information into cells or into kind of particular format.
00:29:20.750 --> 00:29:23.971
In a way, it's quite a sort of dehumanizing process to work with that technology, arguably.
00:29:24.191 --> 00:29:25.201
Whereas this...
00:29:25.881 --> 00:29:29.480
It's unstructured natural language, it responds to the most capricious human behavior.
00:29:29.601 --> 00:29:33.740
And I think that is a kinda extraordinary thing is that in a way it's kind of ultimately humanizing technology.
00:29:33.740 --> 00:29:35.240
It's so intuitive, it's so easy.
00:29:35.661 --> 00:29:43.461
And so there is a truth to that, what you're saying, which is that ultimately, you know, it's this is this, you won't even notice it's going to become so sort of ubiquitous.
00:29:44.030 --> 00:29:55.642
Um, But this is where I come back to our Altogether members in particular, which is, why everybody is now, needs to be a tech person, because everybody can be a tech person, because the barrier used to be, do you know how to code?
00:29:56.642 --> 00:29:57.352
And it won't be.
00:29:58.011 --> 00:29:59.801
It still is a little bit, unless, you know.
00:29:59.961 --> 00:30:04.771
You know, you use Zapier and these kind of no code platforms and, you know, then you'll be limited.
00:30:04.771 --> 00:30:15.162
But in time, the point about this natural language interaction is it can make you do, it can enable you and your business to do Well, but I would, I would put a slightly different spin on what you just said.
00:30:15.162 --> 00:30:16.451
So I don't think that's quite right.
00:30:16.451 --> 00:30:21.192
I think what happens is that this is going to become, I do, you know, I do believe that everybody's going to work in a different way.
00:30:21.811 --> 00:30:29.741
I think that to say everyone's going to become a tech person isn't right, because I think what will happen with tech is that tech itself will be reinvented based on the enablement of this technology.
00:30:30.061 --> 00:30:40.701
And you know, for this I kind of I believe in this sort of Ben Evans analysis, a kind of Jevons paradox, which is something with, with, with software engineering is it becomes 10 X more effective and efficient.
00:30:40.971 --> 00:30:42.231
You don't end up doing less of it.
00:30:42.231 --> 00:30:50.912
You do more of it, because fact of world just demands more and more of you, you know, in the same way that, you know, as you end up with, if you build Excel, you didn't end up with like less analysis, right?
00:30:50.932 --> 00:30:52.231
You end up with like more complicated.
00:30:52.527 --> 00:30:53.487
You know, interesting analysis.
00:30:54.096 --> 00:30:56.067
Accounting machines don't get rid of accountancy.
00:30:56.406 --> 00:30:58.987
They, they, they sort of demand more from the profession.
00:30:58.987 --> 00:31:02.967
And I think that's what you're gonna see with tech, which is more will be demanded from it.
00:31:03.297 --> 00:31:09.547
And the kinds of skills that people want to build will be slightly different ones, as certain pieces of the role become more compressed.
00:31:10.217 --> 00:31:28.896
think it will reduce the gap between people who do tech and people who don't, but I do think that for this, for the vast population, this kind of technical transformation, this technical sort of shift in mindset, this shift towards a different way of working, writing fast is no longer the solution, is something that everyone will have to go through.
00:31:29.896 --> 00:31:35.987
Last question, Let's talk directly to the CEOs and founders of, of scale ups and small businesses.
00:31:36.547 --> 00:31:38.336
Let's set the scene, which is okay.
00:31:38.737 --> 00:31:39.527
It's hyped.
00:31:40.037 --> 00:31:48.247
There's not as much application of it as you think there is out there based on everything you're reading, but it is being applied and it is being used.
00:31:48.757 --> 00:31:51.567
What's the advice to those CEOs and founders?
00:31:51.606 --> 00:31:58.896
There's a lot of them and a lot of tech CEOs and founders I've spoken to who are still sitting on the sidelines watching and waiting.
00:31:59.253 --> 00:32:00.814
They think that's the sensible strategy.
00:32:01.538 --> 00:32:16.028
And then there are others that, that many of them speaking at our event who are all in and using it in every, which way they possibly can at the moment, even if the way they're using it is going to be completely different in three weeks because the technology moves so fast.
00:32:16.398 --> 00:32:17.088
What's your advice?
00:32:17.357 --> 00:32:28.304
I think form the habit now in yourself and in your organization, even if you feel like it's not driving, you know, more than the 10 percent gain, you know, get everybody.
00:32:28.344 --> 00:32:28.973
And this is essential.
00:32:29.425 --> 00:32:30.026
mindset.
00:32:30.026 --> 00:32:31.796
You get everybody using it.
00:32:31.936 --> 00:32:37.977
Get everyone trying to compress how long it takes to do things and to find new things that they can do that they wish they could that would make their world better.
00:32:38.297 --> 00:32:44.997
Do it yourself because forming habits now will mean that as you know as we move from gradually to suddenly that's not going to overwhelm your organization.
00:32:45.007 --> 00:32:49.126
So I think organizational resilience comes from forming the right habits now.
00:32:49.396 --> 00:32:51.426
I think it's important to form networks of learning.
00:32:51.426 --> 00:32:54.696
I think that you know the reality of this is that it's not being created by textbooks.
00:32:54.696 --> 00:32:56.217
You can't go and Read about it.
00:32:56.227 --> 00:32:59.307
You're kind of it's being invented live in a million workplaces.
00:32:59.416 --> 00:33:01.027
Every leader is now a learner.
00:33:01.557 --> 00:33:07.586
Go and find the networks of peers who you can learn with and think about building organizational resilience.
00:33:07.586 --> 00:33:09.946
You know, I think that this is not gonna be so easy.
00:33:09.946 --> 00:33:11.076
It cost of living crisis.
00:33:11.561 --> 00:33:17.791
Yeah, this is gonna be a journey for everyone, but what I would say is you know, ultimately, this is a leapfrogging opportunity, right?
00:33:17.791 --> 00:33:21.580
It's just, for any entrepreneur, this is just A huge opportunity.
00:33:21.810 --> 00:33:22.580
For anybody.
00:33:22.621 --> 00:33:27.976
I mean, it's just, you know, so I just think, ultimately That, that's got to be the kind of final thought, hasn't it?
00:33:28.032 --> 00:33:28.996
I, I, I agree.
00:33:29.026 --> 00:33:33.605
And, and that's where I am and we'll make that the overarching to your three things.
00:33:34.135 --> 00:33:39.175
I, I want to, we're going to continue this discussion at the summit on the 2nd of November for sure.
00:33:39.516 --> 00:33:39.875
Claudia.
00:33:39.875 --> 00:33:40.556
Thank you.
00:33:40.736 --> 00:33:50.046
I have found, as you know preparing for this summit and talking to people has just been an excuse for me to learn about a I completely because I knew nothing coming into it.
00:33:50.215 --> 00:33:52.855
Nothing other than the fact it could help me write some song lyrics.
00:33:53.118 --> 00:33:53.568
Badly.
00:33:54.150 --> 00:33:55.670
Because I wasn't prompting very well.
00:33:55.940 --> 00:33:58.539
So Jamie, before we wrap up then, how do you feel now?
00:33:59.140 --> 00:34:00.220
Oh, that's interesting.
00:34:00.390 --> 00:34:01.799
It is, because it is six months later.
00:34:02.140 --> 00:34:11.119
I feel, I'm afraid I still switch every now and again to I beyond this next wave of technology?
00:34:11.800 --> 00:34:15.594
Is it something where I should just sit back now and say this is the young, the youngsters
00:34:15.751 --> 00:34:16.260
world
00:34:16.800 --> 00:34:18.141
or do I go all in?
00:34:18.161 --> 00:34:20.481
And I'm black and white, I'm afraid.
00:34:20.481 --> 00:34:26.610
So, Actually the truth is I'm a, I'm a long way down the journey And I just don't believe that's true, but it is true.
00:34:26.971 --> 00:34:32.371
And I'm already Far more knowledgeable than I probably need to be about some of this stuff.
00:34:32.851 --> 00:34:33.851
And that's good for me.
00:34:34.570 --> 00:34:38.090
just so encouraging this is an achievable...
00:34:38.376 --> 00:34:43.655
than I always remember someone talking about tech and saying, It's like, you know, I really am interested in tech, But I feel like I've missed the first three seasons.
00:34:44.956 --> 00:34:47.045
You know, and I just can't quite catch up now.
00:34:47.045 --> 00:34:56.260
I mean, I was tech PC for the first dot com, but I used to go, don't understand tech! Well, you've just Now everyone's here on episode one, so you're here on episode one, so you you should...
00:34:56.260 --> 00:34:56.940
You can catch up.
00:34:57.371 --> 00:34:59.320
With the first season before it.
00:34:59.320 --> 00:35:00.311
Yeah, I love that.
00:35:00.311 --> 00:35:01.181
I love that.
00:35:01.181 --> 00:35:02.530
Thank you so much for your time.
00:35:02.570 --> 00:35:03.440
See you on the second
00:35:03.760 --> 00:35:03.780
you
00:00:00.363 --> 00:00:07.315
those people who could write really, really fast didn't thrive in the age of the typewriter, However good you are at that skill that you have mastered.
00:00:07.881 --> 00:00:09.301
AI can now do instead.
00:00:09.650 --> 00:00:12.041
Doing it better, faster, it, you're not gonna win.
00:00:12.230 --> 00:00:15.006
The people who can master the typewriter, they're the ones who win.
00:00:15.446 --> 00:00:22.143
we believe that the, limit of learning in organizations is going to be set by the individuals in those organizations.
00:00:22.251 --> 00:00:24.782
LQ can be taught, it can be learned.
00:00:24.812 --> 00:00:30.562
And it is going to be absolutely essential to every single worker, I think, in the new economy.
00:00:31.198 --> 00:00:34.417
for any entrepreneur, this is just a huge opportunity.
00:00:34.646 --> 00:00:35.417
For anybody.
00:00:35.476 --> 00:00:39.421
so I just think, ultimately That, that's got to be the kind of final thought,
00:00:55.813 --> 00:01:03.280
Hello and welcome to Altogether's Three Things and our latest in our Ask the Experts series.
00:01:04.060 --> 00:01:09.385
Today's an exciting one for me because it's a return visit to, to the hot seat, for Claudia Harris.
00:01:09.415 --> 00:01:10.355
Welcome, Claudia.
00:01:10.685 --> 00:01:11.765
Hello, to be back.
00:01:12.215 --> 00:01:16.685
Claudia engaged me hugely in our podcast, what was it, a year, two years ago?
00:01:16.694 --> 00:01:17.954
A year and a half ago?
00:01:18.156 --> 00:01:18.765
a while ago.
00:01:18.844 --> 00:01:29.423
Talking quite a lot of ethics, quite a lot of undiscovered talent issues, blind recruiting how people should hire bravely and It was thoroughly enjoyable.
00:01:29.802 --> 00:01:33.412
And you've contributed to so much of Altogether as one of our volunteer advisors.
00:01:33.412 --> 00:01:35.263
You spoke at our very first summit.
00:01:35.322 --> 00:01:37.483
And you're going to speak at our next summit.
00:01:38.102 --> 00:01:40.793
Which is coming up soon on AI.
00:01:41.242 --> 00:01:46.453
And the reason we're here is because Makers is thinking a lot.
00:01:46.802 --> 00:01:54.022
About AI and how it is going to transform the world of work, I guess, But can I ask the first question?
00:01:54.388 --> 00:01:56.099
How do you personally use it?
00:01:56.599 --> 00:02:07.626
so very clearly massively time of everything that in your using And I figuring how to do so AI writes my speeches for me.
00:02:08.132 --> 00:02:09.092
Does it?
00:02:09.092 --> 00:02:10.741
So when you, when you speak to
00:02:10.741 --> 00:02:11.012
uh,
00:02:11.062 --> 00:02:22.335
when you speak at the event it'll be Yeah, unfortunately, I do, you know, I will, I will tune the response, but if want to create any kind content at any kind scale, I'll always use chat GPT start me off on that.
00:02:22.715 --> 00:02:24.504
And I will then refine and improve it.
00:02:24.504 --> 00:02:29.344
I do think that we have to kind of move away from writing and towards prompting and terms of content creation.
00:02:29.344 --> 00:02:37.735
Whether that's speech creation, presentation creation, email creation, GPT both creates fed along form and can provide summaries content, and I think it needs to be done, used for that.
00:02:38.245 --> 00:02:39.955
But just understanding stuff, right?
00:02:40.044 --> 00:02:46.675
If there's anything I understand that I need to understand quickly for my job, I will use GPT to me that.
00:02:46.675 --> 00:02:52.014
I will ask to explain, re explain, use analogies, whatever is kind of most useful persona.
00:02:53.014 --> 00:02:58.034
We, the reason we're doing this event, as you know, because you are now partnering with us on it.
00:02:58.034 --> 00:02:59.085
Thank you very much, makers.
00:02:59.645 --> 00:03:09.955
Basically, for most CEOs and founders, I think the, the hype that is out there makes them think they may be behind the curve.
00:03:10.057 --> 00:03:15.478
And certainly when I first started talking to you about it, I was going, Oh, are we too late with this event?
00:03:15.557 --> 00:03:25.980
And it didn't take long to realize actually we may not be quite that far advanced in terms of how business is applying generative AI into its day to day operations.
00:03:26.621 --> 00:03:27.471
What's your view?
00:03:27.471 --> 00:03:29.890
Where are we on the journey moment?
00:03:30.727 --> 00:03:38.461
there's this phrase from Ernest Hemingway about bankruptcy, not about AI I should say, in which he it happened in two ways.
00:03:38.812 --> 00:03:40.632
Gradually and then suddenly.
00:03:40.961 --> 00:03:53.075
And think a really useful phrase thinking about what's going to happen really, and I'm really particularly the advent LLMs because LLMs is a kind you know, part a continuum decades of work in terms of AI and machine learning.
00:03:53.545 --> 00:04:01.917
But do think they have hit the world in a way was at scale much faster than people prepared for to take an individual government's companies.
00:04:02.343 --> 00:04:02.723
caught them unprepared.
00:04:03.033 --> 00:04:07.794
And I that's big shift that we're talking about particular.
00:04:08.334 --> 00:04:21.124
But think, yeah, I think gradually and then suddenly, I think what's happening right now is that there are sort of three reasons why companies struggling to make use of of it One concerns around IP privacy, but even that debate is moving so quickly, right?
00:04:21.124 --> 00:04:34.495
With the new kind of enterprise versions of a lot of these tools, some of those concerns have already started to evaporate, but And just so we are clear, this is a concern that whatever I put into, say, chat G B T, but there are many other LLMs out there.
00:04:34.875 --> 00:04:38.834
Becomes part of the model and could be spat out back.
00:04:38.834 --> 00:04:38.894
Yeah.
00:04:39.834 --> 00:04:40.286
And that is true.
00:04:40.774 --> 00:04:46.514
mean, true, I think, you know, the extent to which it's a super high risk, depends on what we're talking from a content You of
00:04:46.514 --> 00:04:47.514
kind of, you put your
00:04:47.514 --> 00:04:51.514
interview notes about an individual and that individual kind chat GPT themselves and finds themselves.
00:04:51.704 --> 00:04:54.134
I think that there's, you know, more or less risk with this.
00:04:54.144 --> 00:04:56.735
it's an incredibly complicated system, but that,
00:04:56.740 --> 00:05:07.490
And there are no, I've heard no examples yet of someone who's talking to chat GPT and they've been told some highly confidential piece of information, which given that the whole planet is using it is surprising.
00:05:07.555 --> 00:05:16.221
But, but I think with that, but that's a fundamental and the enterprise solution will cost me, but it, it basically allows me to keep my data separate from the the model.
00:05:16.232 --> 00:05:17.982
Yeah, so the model's not trained on what you put into it.
00:05:18.031 --> 00:05:20.211
And then the other concern, of course, is that you're going to be breaking IP.
00:05:21.211 --> 00:05:24.822
by using content that's ripped off other people's content.
00:05:24.882 --> 00:05:30.971
And that's the kind of second concern and the kind of concern about could you end up with sort of huge liabilities that you don't know you're creating?
00:05:30.992 --> 00:05:33.911
So IP and privacy kind of one bucket of reasons.
00:05:33.911 --> 00:05:34.992
I think that companies are.
00:05:35.367 --> 00:05:36.117
Cautious to engage.
00:05:36.127 --> 00:05:41.896
I think a second reason is, is just tool mastery, like simply, do we understand what the tools are and how to use them?
00:05:41.896 --> 00:05:48.026
That's kind of simple Apart from the fact that every two minutes there's a new application built on top of the LLMs.
00:05:48.117 --> 00:05:53.041
So how do you master something that is changing so which we will, we'll talk a little bit about in a second.
00:05:53.041 --> 00:05:57.432
And then the third thing, I think this is a really interesting one is people struggling to connect the tools to the use case.
00:05:57.701 --> 00:05:58.781
Yes, right.
00:05:58.810 --> 00:06:01.110
Which, I mean, I spent, as you know...
00:06:01.264 --> 00:06:09.663
We spent a long time trying to figure out what use cases to, to sort of highlight for this event, and it's quite tricky.
00:06:10.204 --> 00:06:13.377
And so I think, you know, kind of obviously with anything that you ever do.
00:06:13.509 --> 00:06:22.608
In life, in business, in any situation, what matters is the outcome, what you're trying to achieve, what's your goal, and the tool is only useful in as far as it supports you with the goals and outcomes that you're aiming to achieve.
00:06:22.608 --> 00:06:24.778
And so, to be kind of tool oriented doesn't make sense.
00:06:24.788 --> 00:06:27.788
You've got to be outcome oriented, and then you've got to figure out how the tools support the outcomes.
00:06:27.788 --> 00:06:29.738
And I think lots of companies struggle with that.
00:06:29.749 --> 00:06:36.598
So, you know, people can go and write a poem with GPT, but can they really use it, as we've discussed, to compress their kind of normal workflow?
00:06:37.843 --> 00:06:41.694
a gap Now, we're not going to spend a lot of time on use cases today, because that's...
00:06:42.694 --> 00:06:48.303
What the event we're putting on is doing and we are showcasing some genuine use cases.
00:06:48.303 --> 00:06:59.908
We've already announced that Greg Jackson is speaking alongside you to talk about how generative AI has transformed customer services at octopus, which given how good their customer services was anyways.
00:07:00.050 --> 00:07:13.586
It's pretty exciting, but we've got, we'll have lots of conversations about use cases at the event, I'm really interested though in this idea that you should start with the problem, which, you know, all the CTOs we've spoken to have been very firm on.
00:07:13.822 --> 00:07:14.182
Yeah.
00:07:14.494 --> 00:07:16.774
Isn't there also just a point to play?
00:07:16.831 --> 00:07:17.560
To learn?
00:07:17.841 --> 00:07:20.221
I mean, I have, I'm not trying to solve anything at the moment.
00:07:20.230 --> 00:07:22.380
I'm, you know, I'm just figuring out what I can do.
00:07:22.870 --> 00:07:33.399
Having believed it wasn't possible to build a chatbot on my own because it was quite technical and it needed, no, there's plenty of businesses out there who say, what do you want to train your chatbot on?
00:07:33.540 --> 00:07:35.339
You feed it documents and away you go.
00:07:35.339 --> 00:07:39.399
So I've created all sorts of weird chatbots, but not for any goal here.
00:07:39.697 --> 00:07:40.668
so I do think that's the problem.
00:07:40.668 --> 00:07:42.728
I think that's what people do challenge these tools on.
00:07:42.728 --> 00:07:47.617
And I think when we think about the kind of connection of tool to use case, We think there are two ways of thinking about that.
00:07:48.017 --> 00:07:52.137
So we think there are existing outcomes that you already, like, need to deliver for your work.
00:07:52.317 --> 00:07:54.937
and the way to think about this is, you know, how do you spend your week?
00:07:55.060 --> 00:07:57.000
What is the majority of your time spent on?
00:07:57.000 --> 00:07:59.630
And how do we use GPT to kind of compress the time it takes?
00:07:59.641 --> 00:08:06.490
Or, one of the large language models, sorry, really obviously not GPT every time we say GPT, everybody should just hear, or any of the other large language models.
00:08:06.644 --> 00:08:16.694
Yes, and I should really say that, but the, but the first question is, how do you use these models to compress the time it takes to deliver the same outcomes or indeed improve it?
00:08:16.694 --> 00:08:19.834
And we'll talk about that in a second because I think they do both.
00:08:19.923 --> 00:08:22.012
But that's something that, you know, everyone should be working through.
00:08:22.033 --> 00:08:24.723
Like how do you, their own personal yes.
00:08:24.752 --> 00:08:26.723
And this is a lot of what we're thinking about at Makers.
00:08:26.723 --> 00:08:31.213
And this is a lot of what our training is dedicated to, which is how do you basically make your workflows more.
00:08:31.589 --> 00:08:32.240
efficient?
00:08:32.284 --> 00:08:37.085
so that's about delivering the same outcomes with fewer hours of input.
00:08:37.293 --> 00:08:43.513
The second kind of use case is that we think that there are new use cases that you are now able to deliver that you couldn't deliver before.
00:08:43.903 --> 00:08:45.427
And for me, change the world now.
00:08:45.482 --> 00:09:04.639
well, and I think this is also about an individual's, you know, it's just an extraordinary thing, right, that you can kind of master a skill that perhaps, you know, For 25 years, you have felt intimidated to try, and you had some bad experiences with Excel, and you don't feel confident in terms of, you know, data management, data creation, and code interpreters, a completely different kind of process.
00:09:04.749 --> 00:09:11.058
and suddenly you are confident managing large data sets, delivering complicated data outcomes.
00:09:11.438 --> 00:09:12.469
You know my view on this one though.
00:09:12.964 --> 00:09:14.224
It takes a little bit of time.
00:09:14.278 --> 00:09:15.214
No, I don't think it works.
00:09:15.214 --> 00:09:15.749
Do you love it.
00:09:15.749 --> 00:09:22.188
No, I don't think Code Interpreter, which is the old word for just ChatGPT now because they don't call it Code Interpreter.
00:09:22.188 --> 00:09:28.869
But basically you can upload an Excel spreadsheet into ChatGPT 4 and you can start manipulating data and analyzing it.
00:09:29.318 --> 00:09:33.009
But I liken it to hiring a double first from Google.
00:09:33.504 --> 00:09:45.214
Cambridge engineering degree, brilliant smarts, but no business sense because the stupid mistakes that get made along the way that you can't see because there's a black box involved.
00:09:45.673 --> 00:09:49.130
I, I just, I do have too much time on my hands, right?
00:09:49.171 --> 00:09:52.880
Cause I, I had a problem and I chose the wrong solution.
00:09:52.880 --> 00:09:55.260
My problem was I needed to analyze some data and.
00:09:56.086 --> 00:10:05.476
My Excel on Mac license had run out or something and I thought, well, you know what, rather than build a pivot table myself, I'll get chat bt to do it a month later.
00:10:05.476 --> 00:10:07.366
I still haven't got it to, to work.
00:10:07.514 --> 00:10:09.984
so I think, and I think this, this is a tool used, right?
00:10:09.984 --> 00:10:12.604
And some of these tools are still emerging and kind of not, not, yet.
00:10:13.193 --> 00:10:20.417
but you can feel right from that, that that is going to be a very powerful, different way of delivering results that people...
00:10:20.437 --> 00:10:22.933
It's going to change within months.
00:10:23.698 --> 00:10:25.438
And, you know, the same with creative output, right?
00:10:25.438 --> 00:10:28.923
People for whom they can visualize a creative output, but they've not, you know, fine.
00:10:29.126 --> 00:10:37.886
how to use videos, don't know how to, you know, don't know how to create I mean, this video I'm taking of you right now won't have a nice white brick, won't have a nice white brick background.
00:10:38.317 --> 00:10:39.241
There's all sorts of Avatar.
00:10:39.371 --> 00:10:40.701
Right, exactly.
00:10:41.246 --> 00:10:43.307
Yeah, I'll be unrecognizable, that's what I'm hoping for.
00:10:43.307 --> 00:10:49.476
But the, but the second kind of use cases, the things that you felt you couldn't do, which over time you were going to be able to do.
00:10:49.506 --> 00:11:01.817
And that the things that perhaps you asked your colleagues for help with, or you outsourced to colleagues or you outsourced across departments that individuals are going to be able to do, which is going to have an interesting effect on how companies work, you know, reduce complexity, maybe require less kind of.
00:11:01.995 --> 00:11:03.076
Cross functional working.
00:11:03.076 --> 00:11:11.405
It's going to be interesting when you are able to do things that maybe you, you wish you could do, haven't quite trained yourself to do, can suddenly do yourself easily.
00:11:11.596 --> 00:11:12.296
So these are the two.
00:11:12.296 --> 00:11:15.956
So when you think about these sort of three things that we need kind of companies to master.
00:11:16.115 --> 00:11:18.225
Getting rid of the concerns about IP and privacy.
00:11:18.476 --> 00:11:19.626
Putting the guardrails around it.
00:11:19.736 --> 00:11:20.986
Figuring out how you're going to manage that.
00:11:21.562 --> 00:11:30.182
Tool mastery, but then ultimately the use cases both compressing the amount of time it takes to deliver existing use cases and figuring out on an individual basis how to deliver new use cases.
00:11:30.652 --> 00:11:38.511
That, That, that for us is a kind of roadmap for companies to start to really get some, some really interesting mastery among their people.
00:11:38.991 --> 00:11:43.971
And this, you know, you said, they're changing all the time, how are organizations going to keep pace?
00:11:43.981 --> 00:11:44.011
Yes.
00:11:44.042 --> 00:11:47.866
So at Makers, we believe that the kind of.
00:11:48.159 --> 00:11:53.220
the, limit of learning in organizations is going to be set by the individuals in those organizations.
00:11:53.649 --> 00:12:05.424
That companies are going to struggle to interpret the different, you know, figure out what's going on across the different tool sets and translate that into learning programs and disseminate that to their teams will not be able to move.
00:12:05.457 --> 00:12:06.529
It won't be able to move fast enough.
00:12:06.529 --> 00:12:09.179
So you're going to rely on people to learn fast.
00:12:09.669 --> 00:12:19.715
And so we think that from a kind of, one of the most important characteristics of this new revolution is going to be the degree to which people have learning quotient, right?
00:12:19.725 --> 00:12:24.804
So we've always talked about Intelligence quotient then it was emotional intelligence.
00:12:24.855 --> 00:12:36.596
Yeah, IQ EQ for us LQ Is LQ, have you made it up, or is it actually a thing, LQ so, so quantum black, I think, is it back where we got this idea from, which is the McKinsey's Sort of group.
00:12:36.782 --> 00:12:36.912
group.
00:12:37.356 --> 00:12:45.537
Sounds such an evil name, like it's a Bond It's a great name, But the, but the, so, but what does this mean for individual, for companies?
00:12:45.537 --> 00:12:47.206
If companies, what does this mean for individuals?
00:12:47.431 --> 00:12:51.167
Individuals now need to be right at the edge of learning.
00:12:51.216 --> 00:12:54.230
Make learning one of their most kind of kind coveted characteristics.
00:12:54.230 --> 00:12:56.821
Companies need to recruit people who have high LQ.
00:12:57.725 --> 00:13:00.130
People need resilience because that pace of change is going to be...
00:13:00.660 --> 00:13:03.500
where And so resilience and LQ are going to be key.
00:13:03.890 --> 00:13:12.461
And then we need to help equip people with the ability to understand how to manage the IP and privacy, use the tools, and then deliver the tools to deliver use cases.
00:13:12.660 --> 00:13:20.971
And for us, that combination of things, LQ and resilience, and then the ability to understand how to use the tools and deploy them against use cases.
00:13:21.400 --> 00:13:35.405
will make somebody a truly effective user of this new technology And the way we think about this is that that person will then become what we're describing as a centaur so a person who is which is a half half machine, Half you.
00:13:35.405 --> 00:13:43.056
So the original kind of, so the center, obviously, originally from kind of mythology is a part creature, part human combination.
00:13:43.416 --> 00:13:51.265
In 1998, Kasparov coined it to describe part human, part machine, the combination that could beat all others at chess.
00:13:51.360 --> 00:13:56.640
And we think that that kind of, and so it's a kind of notion of the integration of human and artificial intelligence.
00:13:56.971 --> 00:14:01.110
And I think that is what will make people thrive in this new economy.
00:14:01.380 --> 00:14:05.490
And that if people are thinking about how to themselves thrive in this quite uncertain world.
00:14:05.808 --> 00:14:17.328
It is to do with building the LQ, building the resilience, feeling confidence in the IP privacy issues, feeling confidence in tool mastery, and then figuring out how to deploy these tools against these cases.
00:14:17.328 --> 00:14:24.818
Both existing ones to do their work faster and potential ones to unleash a whole bunch of capabilities that today are unattainable.
00:14:25.308 --> 00:14:28.528
And that for us is what the central worker will look like and does look like.
00:14:28.749 --> 00:14:30.178
And we think we're now entering the age of...
00:14:30.389 --> 00:14:41.989
The center economy when really that combination of characteristics is what will define success at an individual level and an organization so that have people like that in them are going to be the ones that will succeed.
00:14:42.989 --> 00:14:53.879
So, that is the clearest, I mean you've talked to me a little bit about this before and you got me at hello frankly, I think, with just the first two points about LQ and resilience.
00:14:53.899 --> 00:14:56.178
But, let's dig into this a little bit if we can.
00:14:56.514 --> 00:14:56.854
we
00:14:57.178 --> 00:14:58.938
First of all, what are you saying here?
00:14:59.438 --> 00:15:00.009
That.
00:15:00.533 --> 00:15:15.501
If you as an individual or you as a organization want to compete in this new economy, succeed, whatever the definition, not be left behind there's actually five things then, right?
00:15:16.501 --> 00:15:18.741
Develop your LQ, which is, I don't know.
00:15:18.741 --> 00:15:20.081
I don't know how I'm built.
00:15:20.091 --> 00:15:20.282
It is.
00:15:20.282 --> 00:15:21.001
We'll come back to that.
00:15:21.461 --> 00:15:23.461
Develop your resilience, come back to that.
00:15:24.001 --> 00:15:39.442
This then IP learn the tools and effectively, can I use the word innovate for the last one, the use cases one, because that's really what I'm getting excited about, which is changing, you know, using all of that then to, to innovate the way you do things personally, or the way that the business does things.
00:15:40.142 --> 00:15:41.741
I got the LQ bit.
00:15:41.802 --> 00:15:43.427
Can you improve your own?
00:15:43.553 --> 00:15:44.114
LQ?
00:15:44.364 --> 00:15:44.953
100%.
00:15:44.994 --> 00:15:49.673
I mean, really the makers program for 10 years has been built on the idea of helping people learn how to learn.
00:15:49.764 --> 00:15:54.918
Could you remind people, or tell people what the Makers core product is?
00:15:54.948 --> 00:15:58.999
Because I think we missed that at the Yes, and I should know how this links to what we've been talking about.
00:15:59.009 --> 00:16:05.519
Of course, so makers we have for 10 years Helped diverse career switches to retrain to become software engineers.
00:16:05.548 --> 00:16:26.274
In fact, we we turn them into all kinds of tech areas today But that's been our kind of core proposition We believe that Talent is distributed much more evenly in society than opportunity is and the more that you believe that the more that you believe that the British Education system is not particularly fair the more that you believe that there are thousands millions of people out there who could be software engineers who just aren't in the right place, aren't in the right job and are stuck.
00:16:26.658 --> 00:16:32.389
And we're about finding those people, the exceptional talent and helping them to retrain and get into this incredibly exciting industry.
00:16:32.418 --> 00:16:39.078
And we feel really proud of that, really successfully got some, fantastic clients from Deloitte Digital to Google and and some amazing results.
00:16:39.078 --> 00:16:43.749
You know, people go on to become tech leaders across the, across the British tech scene.
00:16:44.089 --> 00:16:46.708
They have, they get promoted really, really fast.
00:16:46.708 --> 00:16:47.778
That's one of our kind of key characteristics.
00:16:47.979 --> 00:17:04.699
And you have developed in as part of this, just for people who want to go back and listen to our old podcast or do other research, it truly inspiring work around CV free recruitment or whatever we call it, these days, blind recruitment, and you know, lots and lots of good things.
00:17:04.709 --> 00:17:12.209
I don't know how far you've got on it, but you are pushing at the boundaries of truly trying to not judge people by what they've done.
00:17:12.273 --> 00:17:13.564
But what they're capable of.
00:17:13.568 --> 00:17:16.538
I mean, the way you get onto a maker's program is based on your potential.
00:17:16.578 --> 00:17:17.398
We don't look at background.
00:17:17.409 --> 00:17:31.669
It is about your attitude, your aptitude, and the ability to pick up the kind of new concepts that we help people to, like, learn about as part of their kind of, and you were teaching software engineering effectively, predominantly Software, data, cloud, quality.
00:17:31.673 --> 00:17:32.134
all the same.
00:17:32.134 --> 00:17:33.689
To me, it's like Yeah.
00:17:33.933 --> 00:17:34.983
not marketing.
00:17:35.239 --> 00:17:35.878
marketing.
00:17:36.273 --> 00:17:37.804
So what's.
00:17:38.804 --> 00:17:45.253
I mean, apart from the fact that AI is going to transform how software engineers work that's not what the Centaur program is, though.
00:17:45.473 --> 00:17:48.013
So why this shift into the Centaur program?
00:17:48.334 --> 00:17:51.753
So our thing has been transformative tech education, right?
00:17:51.763 --> 00:17:57.433
Transforming people's lives through tech education to give them a kind of different quality of different experience in life.
00:17:57.433 --> 00:18:03.074
And for the first 10 years, you know, we started, we really focused on helping people within the tech space.
00:18:03.608 --> 00:18:05.818
Becomes junior engineers, but that was a thing.
00:18:06.409 --> 00:18:10.979
In fact, three years ago, we introduced a new product, which has been really successful and with one of our clients.
00:18:10.979 --> 00:18:14.209
And that has been about helping junior engineers transform.
00:18:14.644 --> 00:18:16.384
To become engineering leaders.
00:18:16.453 --> 00:18:22.772
So, we take people who are sort of expert engineers themselves, and want to figure out how to become leaders, and we've helped them to go through a new transformation journey to become a leader.
00:18:22.773 --> 00:18:27.648
So, within the engineering space, you're already in sort of softer skills at that point anyway.
00:18:28.364 --> 00:18:43.432
And they're both, they're both, really about individual transformation, like the transformation to become a junior engineer, the transformation to become a leader, and for that we use the case method that kind of pioneered in the business schools, all about bringing to life real examples from Fellow engineers of, you know, how do you lead quality at scale?
00:18:43.442 --> 00:18:48.532
Like what does it look like to solve those sorts of problems, which is different from the problems of a junior engineer?
00:18:48.742 --> 00:18:56.413
So within the engineering space, we already feel like our absolute expertise is on transformative educational tech education journeys.
00:18:57.127 --> 00:19:05.188
Now, in the world of LLMs, the entire population needs to go through a transformative technical education journey.
00:19:05.387 --> 00:19:05.718
right?
00:19:06.557 --> 00:19:08.587
Everybody now needs to become a centaur.
00:19:10.228 --> 00:19:20.238
The sort of simplistic but I think startling thought is, those people who could write really, really fast didn't thrive in the age of the typewriter, right?
00:19:20.268 --> 00:19:22.778
However good you are at that skill that you have mastered.
00:19:23.762 --> 00:19:25.182
AI can now do instead.
00:19:25.532 --> 00:19:27.923
Doing it better, faster, it, you're not gonna win.
00:19:28.462 --> 00:19:31.423
The people who can master the typewriter, they're the ones who win.
00:19:31.432 --> 00:19:33.682
And it's, the same logic now applies.
00:19:33.942 --> 00:19:40.923
In fact, skills from the past may be an encumbrance to you if you try and hold on to things that you've learned, that you feel protective of, if you can't.
00:19:41.005 --> 00:19:48.333
get rid of those skills, you know, that's, that could be, that could actually hold you back compared to someone who comes at this fresh, and this is the, and this is where people will leapfrog, right?
00:19:48.373 --> 00:19:50.942
They'll have like massive, we've always spoken about leapfrogging technologies.
00:19:51.232 --> 00:19:52.272
Individuals can now leapfrog.
00:19:52.659 --> 00:20:00.888
The reason it links to the Maker's Core mission, right, is that individuals now have to go through this transformative technical education journey to become a centaur.
00:20:01.068 --> 00:20:11.368
And so for us it is simply applying the kind of Maker's philosophy that we've always applied within the technical space and the software engineering space and the engineering space to the broader British economy.
00:20:11.594 --> 00:20:16.124
Well, it needs to be in every single school, university, technical college.
00:20:16.213 --> 00:20:20.023
I mean, how are you gonna, nevermind we're not here to talk about how you're gonna deliver
00:20:20.239 --> 00:20:20.489
no
00:20:20.713 --> 00:20:23.461
no global impact but it relates to the LQ point as well.
00:20:23.461 --> 00:20:28.092
So our whole thing has been transformative technical education, but absolutely the core of it.
00:20:28.152 --> 00:20:32.791
The thing that has made our makers succeed is LQ and it is learnable and we teach it.
00:20:33.142 --> 00:20:35.721
And it's all about how do you deal with.
00:20:36.001 --> 00:20:40.801
Problems, ambiguity, things that you have to learn when you encounter them at work.
00:20:41.201 --> 00:20:53.344
And it, the whole the whole thing that we focus on at Makers is in those moments of ambiguity and challenge, how do you manage your own well being mindset and emotions as regards that experience?
00:20:53.344 --> 00:20:55.433
Do you have a kind of flight response to it, or do you have a...
00:20:55.923 --> 00:21:00.364
You know, curious, calm, relaxed engagement with it.
00:21:00.983 --> 00:21:04.074
How do you think about solving that problem if it's not a problem that you've seen before?
00:21:04.074 --> 00:21:07.124
Like, what are the tools at your disposal to sort of self educate?
00:21:07.153 --> 00:21:13.564
And the entire course is about solving the problem yourself, which can feel very uncomfortable.
00:21:13.574 --> 00:21:18.913
You know, if you've got a coach there who just keeps saying, well, try again, think again, have another go, it can be frustrating.
00:21:18.913 --> 00:21:23.003
But the point of it is that in the real world, you don't have a coach giving you the answers.
00:21:23.394 --> 00:21:47.864
You need your to be your own coach saying you've got this you can figure this out find a way So it's this combination of like knowing where to go to try and self educate to find the answers and having the resilience And the emotional well being and the kind of emotional tools to manage your own response to ambiguity And not knowing how to move forward the combination of those two things is at the heart of the makers curriculum It's the growth mindset logic And it is what our clients love about makers.
00:21:47.953 --> 00:21:49.884
Curious, collaborative problem solvers.
00:21:50.074 --> 00:21:52.364
You give them a difficult problem, they find a solution.
00:21:52.374 --> 00:21:55.273
And they, and they cherish, they cherish that opportunity.
00:21:56.193 --> 00:21:57.453
Feedback's at the heart of how we work.
00:21:57.473 --> 00:21:58.743
People are always looking to improve.
00:21:58.743 --> 00:22:01.973
So, LQ can be taught, it can be learned.
00:22:02.003 --> 00:22:07.753
And it is going to be absolutely essential to every single worker, I think, in the new economy.
00:22:08.317 --> 00:22:12.655
I'm gonna come back to your five things that jars with my three things world.
00:22:12.655 --> 00:22:21.546
But anyway, but in terms of I'm gonna come to a second in terms of how you transform bigger organizations and, and by that I mean sort of mediums size and above.
00:22:21.789 --> 00:22:30.119
But, in these entrepreneurial businesses where we have already built LQ, because that's what's created this entrepreneurial business.
00:22:30.119 --> 00:22:33.140
There's LQ abundance in an entrepreneur, I'm talking.
00:22:33.539 --> 00:22:35.049
resilience, abundance.
00:22:35.144 --> 00:22:48.085
This was the mean, this was the rationale for having our event, was to make sure that our members are up to speed on the tools and the use cases and starting their journey so that they're not left behind.
00:22:48.424 --> 00:22:59.994
And I think it's, you know, the entrepreneurs, frankly, Have an advantage at the moment in the entrepreneurial organizations have an advantage over big businesses, but let's talk about sort of larger companies.
00:22:59.994 --> 00:23:06.204
And I've got some in mind that you know, just 150 people rather than even the thousands and thousands of your clients.
00:23:06.905 --> 00:23:11.205
The central program isn't suggesting or your makers approach CEO.
00:23:11.270 --> 00:23:13.310
every single person from the CEO down or the
00:23:13.740 --> 00:23:21.691
Down or the board down needs to go through the central program to enable an organization to become more innovative in a I or are you?
00:23:21.721 --> 00:23:23.165
Is that the only way to do No.
00:23:23.226 --> 00:23:30.625
So I think that, you know, as always with these sorts of big transformation programs, there are layers of change that you implement in an organization.
00:23:30.631 --> 00:23:35.935
You need to start ultimately with a kind of alignment at the most senior levels around some of the more difficult or.
00:23:36.240 --> 00:23:37.861
Or naughty questions, right?
00:23:38.030 --> 00:23:43.730
So so things like privacy, things like security things like the sorts of capabilities that you do want to unleash.
00:23:43.730 --> 00:23:45.820
You need to have a kind of organizational framework for it.
00:23:45.901 --> 00:23:47.540
Agreed at the most senior level.
00:23:47.911 --> 00:23:50.911
I do think that senior leadership should go through the central program.
00:23:50.911 --> 00:23:56.155
I think with any good program when I, you know, mean, you know I'm knocking on the door saying, can I please, can I please, but.
00:23:56.471 --> 00:24:02.721
you know, some of the best clients I work when I used to do a lot of transformation work at McKinsey and the best CEOs.
00:24:03.010 --> 00:24:08.010
If it's for the front line, they go through it themselves because ultimately that's the way you role model it and the way that you know what you're trying.
00:24:08.421 --> 00:24:11.861
You check that you're delivering the program that you want to deliver for your organization.
00:24:11.861 --> 00:24:16.240
But ultimately, you know, we would see senior leaders going through it and then we would see change leaders going through it.
00:24:16.250 --> 00:24:18.441
And this is a train the trainer kind of program, right?
00:24:18.441 --> 00:24:26.151
You need to have key people throughout the organization who are then enablers of the people who work with them for them and across their peers.
00:24:26.431 --> 00:24:27.280
to to do this.
00:24:27.280 --> 00:24:38.351
And of course, what's kind of wild now with, with LLMs is that you know, you can use prompts to make incredibly tailored versions of this program for rollout in the organization, if you think about it.
00:24:38.421 --> 00:24:40.250
Because, you know, How Well, How are you going to protect your IP?
00:24:40.330 --> 00:24:41.371
Let's not worry about that just yet.
00:24:41.371 --> 00:24:41.641
We love online.
00:24:41.661 --> 00:24:41.990
IP?
00:24:42.181 --> 00:24:42.411
That's not where it's at.
00:24:42.411 --> 00:25:02.836
well, we, so there'll be a lot of online Resources for this is that always are in our experience this sort of thing the reason that it's really powerful to do it as a kind of change program where it's Interactive when it's really engaged when it's kind of in cohorts going through certain sort of and Programs together as we do it makers is you just get huge levels of completion and engagement, right?
00:25:02.836 --> 00:25:10.881
You know, we get everyone's free makers everyone and it's a completely different thing when you're trying to do this on your own I mean, I True of a lot of, of online education.
00:25:11.050 --> 00:25:29.651
I'm, I'm aware of time and I'm just going to come back to my question though, which is if you are running a larger organization and I'm not even that bothered by the big corporate, so a medium sized organization, it can't wait, surely, for every single member of my organization to have gone through this program.
00:25:29.651 --> 00:25:39.266
So who am I choosing to put through it first and how are the, how are we actually innovating change in our You want to start with the sort of management team as your starting point.
00:25:39.506 --> 00:25:43.945
And then, as always, it's your change leaders and people who are skeptical.
00:25:44.155 --> 00:25:51.076
You know, it's kind of, as with any change program, you want to get the kind of the train the trainer approach.
00:25:51.441 --> 00:25:59.851
Focused on the people who are going to you want, you want, the ones who are already showing, they've got the LQ and resilience along with the most cynical people.
00:26:00.320 --> 00:26:01.090
cynical people.
00:26:01.090 --> 00:26:01.371
yeah.
00:26:01.661 --> 00:26:06.280
And you know, I, I, it's always in them that you get the real champions in the end.
00:26:06.800 --> 00:26:08.115
I mean, your day one on this.
00:26:08.115 --> 00:26:08.816
You're you're out.
00:26:09.185 --> 00:26:10.726
You're out implementing this.
00:26:10.726 --> 00:26:13.645
I think everybody in your office is currently doing the central program, right?
00:26:13.675 --> 00:26:17.215
And I'm sure you've got your first clients booked in hungry for this.
00:26:17.546 --> 00:26:24.576
I'm I'm really going to be intrigued as to how change happens in organizations who have been trained around centers and who haven't.
00:26:25.185 --> 00:26:29.615
I just think it's mad in terms of how fast everything is Yeah.
00:26:29.615 --> 00:26:34.135
but I do think then again you do have this graduating suddenly thing, right, which is, I think what, You know, whereas we might...
00:26:34.996 --> 00:26:41.296
I think it's I think whereas, you know, in the first three months we all sort of went into like, my God, you know, the world as we know it is over in like six months time.
00:26:41.726 --> 00:26:45.796
It's, it's sort of not, I think what's really interesting about it is it's like a kind of global...
00:26:45.942 --> 00:26:47.173
Race, right?
00:26:47.292 --> 00:26:52.692
Like we've all been given this thing and then everyone's been told like go compete and let's see who's going to win now.
00:26:52.702 --> 00:27:05.542
And And it's something really pure about that and every kind of company everywhere is trying to I, I think it's quite scary and at times I sit there and go, maybe I'm just too old for this one, I'm gonna watch it Yeah, but you, that's not an option and that's the problem, right?
00:27:05.542 --> 00:27:10.393
And I think that is why a lot of people sort of went whoa, you know, all this change coming so fast, am I ready for it?
00:27:10.833 --> 00:27:17.403
but the, but I think the gradual and sudden thing is that, you know, The future is being written in a million workplaces right now.
00:27:17.893 --> 00:27:24.452
And across the world, like, somewhere someone is doing the thing that it's ever will be doing in 3, 6, 9 months time.
00:27:25.887 --> 00:27:35.424
I think one of the things that will happen is that, probably Octopus is a great example of this, there are companies that are really pushing the limits of this technology, and they're trying to work out what they can do.
00:27:35.424 --> 00:27:37.734
I mean, customer service is definitely one, marketing is one.
00:27:38.144 --> 00:27:46.325
You know, how far you can take this, what are the risks, what are the opportunities, and I think there will be a moment, and I almost thought it had happened actually when we had the announcement from Octopus and BT in the same weekend, do you remember?
00:27:46.704 --> 00:27:47.214
About jobs.
00:27:47.565 --> 00:27:49.598
There'll be a moment when sort of a firing gun will be started.
00:27:49.736 --> 00:27:53.846
sounded by a couple of companies that say like, this is now how we're doing customer service or marketing.
00:27:53.996 --> 00:27:54.355
Yes.
00:27:54.625 --> 00:27:58.173
And then, everybody will be really rushing to follow, right?
00:27:58.185 --> 00:28:02.605
But I think in customer service it's almost, has happened, because if you look at all of the...
00:28:02.893 --> 00:28:30.637
Providers of software for customer services, they've all built the AI copilot and okay, there'll be different levels of skills and capabilities of those, that tech and all the rest of it, but it's, it's, it's there and this is part of the bit that, you know, we still got to work out how much is the everyday user going to see this change other than in a different way of working in and the tools that they use you know, You don't need everyone in the organisation to innovate.
00:28:30.982 --> 00:28:32.022
How things are done.
00:28:32.022 --> 00:28:50.272
I mean, the applications are getting better and better so that you don't take, take my problem with chat GPT and Excel analysis and now look at Excel with copilot, which I haven't been able to play with yet, but I've seen videos of it and it solves my problem right there because I can see everything that's going on and suddenly it doesn't.
00:28:50.505 --> 00:28:56.134
You know, it doesn't feel like such a big jump for someone to become AI proficient and analyzing data.
00:28:56.345 --> 00:28:58.255
the tools themselves are so intuitive.
00:28:58.555 --> 00:28:59.914
And I think, you know, and that is right.
00:28:59.914 --> 00:29:09.250
I mean, I think, you know, my sort of final thought on this is, you know, it is, we have a whole bunch of sort of visiting professors who work with us on this, and one of them a, a brilliant founder who's just set up a, a, a real estate AI company.
00:29:09.560 --> 00:29:17.560
And what she kind of brings to life is that, you know, if you think about, kind of, previous technological revolutions, what they do is they require us to kind of adopt structured data entry, right?
00:29:17.560 --> 00:29:20.500
You know, you're like putting information into cells or into kind of particular format.
00:29:20.750 --> 00:29:23.971
In a way, it's quite a sort of dehumanizing process to work with that technology, arguably.
00:29:24.191 --> 00:29:25.201
Whereas this...
00:29:25.881 --> 00:29:29.480
It's unstructured natural language, it responds to the most capricious human behavior.
00:29:29.601 --> 00:29:33.740
And I think that is a kinda extraordinary thing is that in a way it's kind of ultimately humanizing technology.
00:29:33.740 --> 00:29:35.240
It's so intuitive, it's so easy.
00:29:35.661 --> 00:29:43.461
And so there is a truth to that, what you're saying, which is that ultimately, you know, it's this is this, you won't even notice it's going to become so sort of ubiquitous.
00:29:44.030 --> 00:29:55.642
Um, But this is where I come back to our Altogether members in particular, which is, why everybody is now, needs to be a tech person, because everybody can be a tech person, because the barrier used to be, do you know how to code?
00:29:56.642 --> 00:29:57.352
And it won't be.
00:29:58.011 --> 00:29:59.801
It still is a little bit, unless, you know.
00:29:59.961 --> 00:30:04.771
You know, you use Zapier and these kind of no code platforms and, you know, then you'll be limited.
00:30:04.771 --> 00:30:15.162
But in time, the point about this natural language interaction is it can make you do, it can enable you and your business to do Well, but I would, I would put a slightly different spin on what you just said.
00:30:15.162 --> 00:30:16.451
So I don't think that's quite right.
00:30:16.451 --> 00:30:21.192
I think what happens is that this is going to become, I do, you know, I do believe that everybody's going to work in a different way.
00:30:21.811 --> 00:30:29.741
I think that to say everyone's going to become a tech person isn't right, because I think what will happen with tech is that tech itself will be reinvented based on the enablement of this technology.
00:30:30.061 --> 00:30:40.701
And you know, for this I kind of I believe in this sort of Ben Evans analysis, a kind of Jevons paradox, which is something with, with, with software engineering is it becomes 10 X more effective and efficient.
00:30:40.971 --> 00:30:42.231
You don't end up doing less of it.
00:30:42.231 --> 00:30:50.912
You do more of it, because fact of world just demands more and more of you, you know, in the same way that, you know, as you end up with, if you build Excel, you didn't end up with like less analysis, right?
00:30:50.932 --> 00:30:52.231
You end up with like more complicated.
00:30:52.527 --> 00:30:53.487
You know, interesting analysis.
00:30:54.096 --> 00:30:56.067
Accounting machines don't get rid of accountancy.
00:30:56.406 --> 00:30:58.987
They, they, they sort of demand more from the profession.
00:30:58.987 --> 00:31:02.967
And I think that's what you're gonna see with tech, which is more will be demanded from it.
00:31:03.297 --> 00:31:09.547
And the kinds of skills that people want to build will be slightly different ones, as certain pieces of the role become more compressed.
00:31:10.217 --> 00:31:28.896
think it will reduce the gap between people who do tech and people who don't, but I do think that for this, for the vast population, this kind of technical transformation, this technical sort of shift in mindset, this shift towards a different way of working, writing fast is no longer the solution, is something that everyone will have to go through.
00:31:29.896 --> 00:31:35.987
Last question, Let's talk directly to the CEOs and founders of, of scale ups and small businesses.
00:31:36.547 --> 00:31:38.336
Let's set the scene, which is okay.
00:31:38.737 --> 00:31:39.527
It's hyped.
00:31:40.037 --> 00:31:48.247
There's not as much application of it as you think there is out there based on everything you're reading, but it is being applied and it is being used.
00:31:48.757 --> 00:31:51.567
What's the advice to those CEOs and founders?
00:31:51.606 --> 00:31:58.896
There's a lot of them and a lot of tech CEOs and founders I've spoken to who are still sitting on the sidelines watching and waiting.
00:31:59.253 --> 00:32:00.814
They think that's the sensible strategy.
00:32:01.538 --> 00:32:16.028
And then there are others that, that many of them speaking at our event who are all in and using it in every, which way they possibly can at the moment, even if the way they're using it is going to be completely different in three weeks because the technology moves so fast.
00:32:16.398 --> 00:32:17.088
What's your advice?
00:32:17.357 --> 00:32:28.304
I think form the habit now in yourself and in your organization, even if you feel like it's not driving, you know, more than the 10 percent gain, you know, get everybody.
00:32:28.344 --> 00:32:28.973
And this is essential.
00:32:29.425 --> 00:32:30.026
mindset.
00:32:30.026 --> 00:32:31.796
You get everybody using it.
00:32:31.936 --> 00:32:37.977
Get everyone trying to compress how long it takes to do things and to find new things that they can do that they wish they could that would make their world better.
00:32:38.297 --> 00:32:44.997
Do it yourself because forming habits now will mean that as you know as we move from gradually to suddenly that's not going to overwhelm your organization.
00:32:45.007 --> 00:32:49.126
So I think organizational resilience comes from forming the right habits now.
00:32:49.396 --> 00:32:51.426
I think it's important to form networks of learning.
00:32:51.426 --> 00:32:54.696
I think that you know the reality of this is that it's not being created by textbooks.
00:32:54.696 --> 00:32:56.217
You can't go and Read about it.
00:32:56.227 --> 00:32:59.307
You're kind of it's being invented live in a million workplaces.
00:32:59.416 --> 00:33:01.027
Every leader is now a learner.
00:33:01.557 --> 00:33:07.586
Go and find the networks of peers who you can learn with and think about building organizational resilience.
00:33:07.586 --> 00:33:09.946
You know, I think that this is not gonna be so easy.
00:33:09.946 --> 00:33:11.076
It cost of living crisis.
00:33:11.561 --> 00:33:17.791
Yeah, this is gonna be a journey for everyone, but what I would say is you know, ultimately, this is a leapfrogging opportunity, right?
00:33:17.791 --> 00:33:21.580
It's just, for any entrepreneur, this is just A huge opportunity.
00:33:21.810 --> 00:33:22.580
For anybody.
00:33:22.621 --> 00:33:27.976
I mean, it's just, you know, so I just think, ultimately That, that's got to be the kind of final thought, hasn't it?
00:33:28.032 --> 00:33:28.996
I, I, I agree.
00:33:29.026 --> 00:33:33.605
And, and that's where I am and we'll make that the overarching to your three things.
00:33:34.135 --> 00:33:39.175
I, I want to, we're going to continue this discussion at the summit on the 2nd of November for sure.
00:33:39.516 --> 00:33:39.875
Claudia.
00:33:39.875 --> 00:33:40.556
Thank you.
00:33:40.736 --> 00:33:50.046
I have found, as you know preparing for this summit and talking to people has just been an excuse for me to learn about a I completely because I knew nothing coming into it.
00:33:50.215 --> 00:33:52.855
Nothing other than the fact it could help me write some song lyrics.
00:33:53.118 --> 00:33:53.568
Badly.
00:33:54.150 --> 00:33:55.670
Because I wasn't prompting very well.
00:33:55.940 --> 00:33:58.539
So Jamie, before we wrap up then, how do you feel now?
00:33:59.140 --> 00:34:00.220
Oh, that's interesting.
00:34:00.390 --> 00:34:01.799
It is, because it is six months later.
00:34:02.140 --> 00:34:11.119
I feel, I'm afraid I still switch every now and again to I beyond this next wave of technology?
00:34:11.800 --> 00:34:15.594
Is it something where I should just sit back now and say this is the young, the youngsters
00:34:15.751 --> 00:34:16.260
world
00:34:16.800 --> 00:34:18.141
or do I go all in?
00:34:18.161 --> 00:34:20.481
And I'm black and white, I'm afraid.
00:34:20.481 --> 00:34:26.610
So, Actually the truth is I'm a, I'm a long way down the journey And I just don't believe that's true, but it is true.
00:34:26.971 --> 00:34:32.371
And I'm already Far more knowledgeable than I probably need to be about some of this stuff.
00:34:32.851 --> 00:34:33.851
And that's good for me.
00:34:34.570 --> 00:34:38.090
just so encouraging this is an achievable...
00:34:38.376 --> 00:34:43.655
than I always remember someone talking about tech and saying, It's like, you know, I really am interested in tech, But I feel like I've missed the first three seasons.
00:34:44.956 --> 00:34:47.045
You know, and I just can't quite catch up now.
00:34:47.045 --> 00:34:56.260
I mean, I was tech PC for the first dot com, but I used to go, don't understand tech! Well, you've just Now everyone's here on episode one, so you're here on episode one, so you you should...
00:34:56.260 --> 00:34:56.940
You can catch up.
00:34:57.371 --> 00:34:59.320
With the first season before it.
00:34:59.320 --> 00:35:00.311
Yeah, I love that.
00:35:00.311 --> 00:35:01.181
I love that.
00:35:01.181 --> 00:35:02.530
Thank you so much for your time.
00:35:02.570 --> 00:35:03.440
See you on the second
00:35:03.760 --> 00:35:03.780
you
