00:00:01Exploring Software Estate Value and Innovation
00:09:53Diverse Perspectives on Business Cultures
00:14:56Navigating AI Strategy and Shadow AI
00:28:20Microsoft Co-Pilot and Azure Integration
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FULL SHOW NOTES
https://www.microsoftinnovationpodcast.com/629
Ever wondered how traditional software management can be transformed by innovative AI solutions? Join us as we navigate the exhilarating Ignite 2024 through the eyes of our field reporter, Chris Huntingford. With over 200 AI sessions and an emphasis on Contact Center advancements, Chris vividly captures the conference's electrifying atmosphere. Meanwhile, back at our studio, we reflect on the sheer joy of merging hands-on collaboration with cutting-edge AI capabilities, highlighting a rewarding return to the essentials like data modelling.
The conversation takes a fascinating turn as we dive into the complexities of on-demand licensing for Copilot studio, illuminating the challenges organizations face in financial forecasting. We also take you on a cultural journey through London's vibrant networking scene, where we share anecdotes from our 2017 move to the UK, shedding light on the distinct business drinking culture and the unique expressions that bring a touch of humor to serious business meetings. Our experiences paint a picture of a collaborative environment where professionals from the UK and the US come together to bridge cultural gaps and foster innovation.
Finally, we shed light on the rising phenomenon of "shadow AI" in the workplace and the pressing need for robust governance frameworks. Discover the latest developments in Microsoft's GitHub Copilot and the seamless integration between AI Foundry and AI Studio, promising a tailored and advanced experience for developers. As we bring this episode to a close, we reflect on the myriad of technological advancements and cultural insights, encouraging you to engage with the ongoing dialogue and explore the future of software innovation.
If you want to get in touch with me, you can message me here on Linkedin.
Thanks for listening 🚀 - Mark Smith
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WEBVTT
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Welcome to the Ecosystem Show.
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We're thrilled to have you with us here.
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We challenge traditional mindsets and explore innovative approaches to maximizing the value of your software estate.
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We don't expect you to agree with everything.
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Challenge us, share your thoughts and let's grow together.
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Now let's dive in.
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It's showtime.
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Welcome back, everybody.
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We're live on air.
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We have our reporter in the field, mr Huntingford, coming all the way from Ignite 2024.
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Chris, how's it there?
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So what I feel like we can summarize this week, as the four of us have worked like dogs while Chris has partied like it's 2019.
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Exactly.
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I'm sure it's been hectic for him, though.
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I love when you say been, I have been.
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Nice, nice.
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Do you guys think that's because Chris never went to bed?
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It's possible, let's just check Chris's expense app to see when.
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Chris stopped buying alcohol last night yeah.
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So there were a lot of announcements this week, of course, at Ignite.
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Yeah.
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Anything, stand out for anybody.
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Agents, agents, agents, a lot of AI sessions, which is like shocking, isn't it?
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Over 200 AI sessions at Ignite.
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Hick of a lot right.
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And Contact Center.
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You know the emphasis on.
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Ivr, etc.
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At the moment has been pretty impressive, I must admit.
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Actually, most of the news I've missed, and I think Anna and Andrew may be in the same boat, because Anna and Andrew and I have been hanging out with each other this week almost every day doing work.
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Will, anna and I actually were all co-located and did actual work together this week, which was fun actually.
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I loved it.
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I really did like it.
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It was so good, like, just like going back to basics and like creating, um, you know, a new project that we believe in so much, and, once again, like seeing the uh, the experience of doing projects upon projects upon projects, and yeah and also, do you know what actually it's?
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it's one thing that you you know at senior layer and it needs to go higher and higher.
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You get quite removed and people you know what actually it's one thing that you know at senior layer and it needs to go higher and higher.
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You get quite removed and people you know I don't think it's a prag, but people do say, oh, I haven't done a workshop for years and stuff like that.
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Well then, how are you sharpening your tools?
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And you know, I loved it.
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I was in a room with Anna today and I love working with Anna.
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I love working with Andrew, but he wasn't there today and I got to get out a whiteboard.
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You know, just get a pen onto a whiteboard drawing out architecture, discussing and debate.
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You can't beat that.
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That's why you got to exactly where you wanted to be and where you are in your career, because you loved doing the workshops, you loved doing the basics and you loved engaging and debating over, in this case, tech, and I just loved it.
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And getting to do it with andrew and anna, who have been friends of mine for years, but now actually getting to work with them and realize actually andrew is as good as he seems on paper.
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Well, uh, it was really good.
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Obviously, I've worked with anna for a long time.
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Well, some people look great on paper but are shocking when you engage with them.
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But in this case, I actually said this to andrew when he was on a room on his own with me.
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He did so we were, we were, we were in, we were in the room, just the of us.
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We were looking at this massive data model that I had put together and Will sort of pulls me close and I don't know what's about to happen and he says you know, andrew, some people that you expect to know what they're talking about end up being shit.
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And I thought that was about to be followed by and you're one of them.
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No, I was impressed.
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We're looking at a at data models.
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He designed it so elegantly, with best practices front of mind, and I was looking at this, this, this particular piece of it, which we know famously.
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Even microsoft have had scalability issues around in the past and andrew, just it was just fantastic.
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And I said, right, you know always nervous working with friends that you know might be good and turn out to be awful.
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I was like, and in this case I'm very happy because I knew you were going to be great, and you are Awesome, awesome, thanks, man.
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But it's really cool because we read, you know, all of the new capabilities and the ideas and you know and everything else, and how do we get started with AI and what sort of governance we need to put in place, what are the processes, how do we design, how do we build a practice?
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But we mustn't forget that once upon a time we used to like build databases and that's valuable, like that's really valuable.
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It's so crucial.
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Yeah, this thing and I promise we'll get, we'll get back to ignite.
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I made I I anticipated the question and made a list of things that were announced this week that I am excited about however, it was.
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It was really, um, one of my favorite, uh, technical tasks to do is data modeling and I I'm not talking about little models, but like really big, large scale data models.
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I learned, I learned, everything I know about data modeling from Dave Milton, who's the technical director for the Microsoft Global Blackbelts now for the Western Hemisphere, for the Americas, and you know back in, you know back in the day, americas, and you know back in, you know back in the day, and this, this thing that we're all working on together, has been so much fun because I've gotten to, you know, I've gotten to go do this thing that I actually find really enjoyable.
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And, yeah, it's, it's absolutely massive and it's in, it's in safe, it's in safe, safe hands with, with Anna taking the, taking the lead from here, I think.
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Oh, I think it's with with, actually, the implementation team, who are really really amazing and wonderful, and that's just so great.
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As you can tell, we're really passionate about this project because of the.
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It's also because of the cause.
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You know, it's like a feel good humanitarian project that we're really, really into.
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It's like the sort of thing that you've always dreamed to be able to do and you never thought you could, and now we have this opportunity.
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It's amazing.
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Absolutely All right.
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So the love fest between the three of us is over, mark, we're sorry.
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We're sorry, it's just getting going, mate, don't you worry.
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I was letting you guys go for it.
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The term circle jerk came to mind.
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But again, this is a podcast what's your favorite news?
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mark from from ignite.
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Uh, what do you?
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Think is most exciting uh, about what?
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the announcements of this week.
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Well, andrew has a list.
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Andrew, what's on your list?
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all right, all right, so so well deflected.
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Yeah, mark, mark couldn't, mark couldn't, mark couldn't get the the book of news to open.
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Is that?
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Is that what I'm hearing?
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Come on quickly.
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No, no, I didn't even attempt, as an animal was trying to get the book of news open.
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I haven't even touched the book of news.
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I have.
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I have it's open right now so I can check.
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I can fact check to see whether your list is correct.
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So here are the five things, in no particular order, that I would say.
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I'm going to hold off on whether I'm excited, but I am intrigued by uh transactional, uh databases built on, you know, built with azure sql, that you can now quickly spin up, spin down, build uh, build applications on top of in fabric.
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So actually I'll just read them off and then we can, we can dig into these if we want.
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So fabric databases, one lake catalog, a co-pilot studio embedded in power apps, which I think is intriguing, like the ability to build I'll call them mini agents inside of your app, which, of course, has brought to mind sort of flashbacks from how Microsoft has never really figured out a clean way to deal with in-app automation, as evidenced by the fact that some of us are still using classic workflows because there's nothing else that can do the job.
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So I think that's interesting.
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There's also supposedly You're going to be like crucified for that.
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I'm sure there's also supposedly deeper RAG capabilities in Copilot Studio, which I think is potentially representative of a broader blurring between Copilot Studio and Azure AI Foundry, formerly known as Azure AI Studio, but there's been a rebrand.
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We can't have Ignite without a rebrand.
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And then the final one that has piqued my interest is these managed security and managed operations capabilities in Power Platform, coming to the Power Platform Admin Center, I presume, from enterprise management via COE starter kit to actual enterprise management via an actual scalable set of tools.
00:09:34.100 --> 00:09:35.703
So I think that's interesting as well.
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Those are my five.
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I'm sure there's others that I've missed, but those are my five.
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Nice, very good, I think you're on point around the governance piece that's obviously coming out as part of the Power Platform, particularly on Copilot Studio and having that level of governance in there.
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I think a lot of people in customer land were really wanting that type of control over who's creating what.
00:10:01.091 --> 00:10:05.538
Also, for the first time, new licensing for co-pilot studio.
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A lot of people were like hang on a second.
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The licensing hadn't changed since when it was called power virtual agents, which was based on number of messages etc.
00:10:14.347 --> 00:10:16.613
And now it wasn't just a chatbot tool anymore.
00:10:16.613 --> 00:10:20.491
But there was kind of no iteration of that and of course now there is.
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You can go for, uh, on demand type licensing.
00:10:23.522 --> 00:10:32.486
It still raises a thing you organizations, as they start committing to these tools, have kind of got no understanding of how much it's going to cost them.
00:10:32.486 --> 00:10:49.091
In a way, it's almost like there needs to be some type of t-shirt sizing for well, if you're going to do this, it's going to consume about that rather than just suck it and see and see how much you clock up on your, your bill for the month, right, um, which can be crazy.
00:10:49.091 --> 00:10:54.225
The other, the other thing that I thought was interesting is andrew is laughing see, I'm sorry.
00:10:54.245 --> 00:10:56.229
Like, is that a kiwi phrase?
00:10:56.229 --> 00:10:58.373
No, no, that's a common phrase.
00:10:58.373 --> 00:11:07.152
No, we use that in the uk all the time you do, yeah, you do, suck it, yeah, it's very common I've lived here for four years and I've never heard someone say that.
00:11:07.393 --> 00:11:07.855
Have you not?
00:11:07.855 --> 00:11:09.605
You're hanging with the wrong crowds mate.
00:11:10.207 --> 00:11:11.380
Yeah, yeah, you know what Actually?
00:11:12.484 --> 00:11:15.251
so Will just sorry an aside.
00:11:15.251 --> 00:11:19.751
I want to talk about business drinking culture in the United Kingdom.
00:11:19.751 --> 00:11:22.345
Let's put a pit in that and come back to it after Mark.
00:11:22.365 --> 00:11:23.708
Let's not even turn over that rock.
00:11:23.708 --> 00:11:26.725
No one needs to look under there.
00:11:28.847 --> 00:11:30.320
I mean, I think we should turn that rock.
00:11:30.320 --> 00:11:35.768
I already turned over the classic workflows rock, which I feel like that needs a shout every six months or so.
00:11:36.269 --> 00:11:39.150
Suck it and see it's apparently British English in origin.
00:11:40.157 --> 00:11:40.639
Ah, there you go.
00:11:42.202 --> 00:11:46.131
So you used to suggest the only way to know something will work or be suitable is to try it.
00:11:46.131 --> 00:11:48.092
You know it's a coincidence.
00:11:48.134 --> 00:11:48.457
There you go.
00:11:49.259 --> 00:11:51.144
I tried to figure out who was the first to coin it.
00:11:51.144 --> 00:11:52.267
Probably Mark Smith.
00:11:52.628 --> 00:12:02.606
Ha ha Ha ha, I could go further in how we could expand on this, but I'm just going to reign it in.
00:12:05.140 --> 00:12:21.951
It's a very unique name as well as well, I mean typing that in on google this late at night was probably my first, my first issue, but but luckily it all stayed pg, so but talking about drinking culture, I was shocked my first day in london.
00:12:21.991 --> 00:12:24.866
When I moved to london I was living in the business district.
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I sorry I was.
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I was living in the city of London right in the financial district yeah.
00:12:28.500 --> 00:12:37.759
And I rock out of my apartment and it's like 1030 am on a Monday and the bar was.
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People were like right out the door, you know, like going for it, and this is like 1030 on a Monday morning.
00:12:44.864 --> 00:12:47.323
So so your apartment was above Ledenhall Market.
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Is that the idea?
00:12:49.563 --> 00:12:49.663
here.
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I couldn't believe it.
00:12:50.707 --> 00:12:51.923
No, it wasn't.
00:12:51.923 --> 00:12:55.826
It was over by what's the big dumb cathedral there?
00:12:56.500 --> 00:12:57.363
Did you say the?
00:12:57.363 --> 00:12:58.947
Big dumb cathedral.
00:12:59.749 --> 00:12:59.970
No no.
00:12:59.970 --> 00:13:01.860
I said what was the big cathedral over there?
00:13:02.808 --> 00:13:05.926
Sorry, you clicked out and I thought you said the big dumb cathedral.
00:13:05.926 --> 00:13:06.707
No, no.
00:13:07.109 --> 00:13:14.253
It's quite commonplace, so it's like I've never really walked past a Wetherspoons that doesn't have a queue before opening, you know, for people to get their ale and stuff.
00:13:14.253 --> 00:13:17.909
So, yeah, and it's probably the people out there, the ones that hate Mondays at half ten.
00:13:17.909 --> 00:13:19.245
So you know, just join them.
00:13:21.961 --> 00:13:35.900
Yeah, but working in either in insurance or in, but mostly like around Lloyd's Market, you know the insurers, brokers, stuff like that there's.
00:13:35.900 --> 00:13:43.062
No, you cannot get a sensible phrase out of anybody after lunch, Like it's just, it's a thing.
00:13:43.563 --> 00:13:53.422
But at the same time you also don't have visibility of any deals, any like.
00:13:53.903 --> 00:13:56.912
No transparency, no data, no nothing.
00:13:56.912 --> 00:14:00.208
So I would be very curious to see it right now.
00:14:00.208 --> 00:14:02.383
Because when was that Mark?
00:14:02.383 --> 00:14:04.206
When you moved to London?
00:14:04.246 --> 00:14:06.051
When was it yeah 2017.
00:14:06.051 --> 00:14:07.173
I think when was it yeah 2017.
00:14:07.173 --> 00:14:08.296
I think it was 2017.
00:14:08.296 --> 00:14:09.057
Yeah.
00:14:09.057 --> 00:14:16.169
The person I had a drink with there was in that area, because they were working in that area.
00:14:16.169 --> 00:14:19.033
Who Scott Durow?
00:14:20.076 --> 00:14:28.118
scott deroe yeah, he was working at metro bank at the time well, I mean, who wasn't, who wasn't working at metro bank at the time?
00:14:28.139 --> 00:14:43.548
yeah, yeah, yeah, yeah no, but the reason this came up, the reason this that I thought of this, was that so yesterday, as we, as we said, you know, there was this, there was this team, uh, that we had, you know, put together, uh, working on this, working on this thing together.
00:14:43.548 --> 00:14:56.240
Uh, anna and will and I were all there and it was kind of a mixed team of folks who had come from, who were based here in the UK and who had come from the US for these working sessions.
00:14:56.240 --> 00:15:32.207
And I was chatting with one of the Americans, not like myself, an American living in Britain, but an American living in the United States, and somehow, you know, it came up and I said you will find, if you hang out here long enough, that Britain has a drinks after work many days in London that you don't have in the US, because in the US you have to drive somewhere that's correct yeah gotcha.
00:15:32.635 --> 00:15:35.706
I think a lot of that goes back to a lack of right exactly.
00:15:37.278 --> 00:15:38.443
Business as usual, mate.
00:15:40.335 --> 00:15:42.985
But when I moved here, it was astonishing to me, right.
00:15:42.985 --> 00:15:47.506
It was like why are these people out all the time drinking?
00:15:47.506 --> 00:15:56.907
As if it's like this expectation that you work in the UK, therefore you will all be drinking together in a posse every night of the week.
00:15:56.907 --> 00:15:59.543
That was jarring for me when I came here.
00:15:59.894 --> 00:16:01.438
It's the only way to get over the weather.
00:16:01.458 --> 00:16:06.663
really, it's so true, I thought I didn't want to get out of bed today.
00:16:06.663 --> 00:16:18.895
One of the other things that came up at Ignite that I thought was interesting now that we've taken the pin out of that subject and dealt with it was.
00:16:18.895 --> 00:16:21.283
Windows 365 Link.
00:16:21.283 --> 00:16:24.039
Did you see that Windows 365 Link?
00:16:24.039 --> 00:16:25.143
I haven't seen that one.
00:16:25.143 --> 00:16:25.563
Tell us more.
00:16:25.583 --> 00:16:26.726
They reckon it's the first.
00:16:26.726 --> 00:16:29.803
It looks like an Apple computer.
00:16:29.803 --> 00:16:34.101
You know the little square computers that Apple have that are just you've got to plug in a screen, keyboard and stuff.
00:16:34.101 --> 00:16:54.009
So this here is a little box about the you know the size of two packs of fags, and it allows you to plug in, uh, your keyboard, mouse and the whole operating system is running from the cloud, so from running from an azure it's like a little apple.
00:16:55.298 --> 00:16:57.784
Yeah, it is sorry but it is.
00:16:57.784 --> 00:16:58.186
It is.
00:16:58.186 --> 00:17:00.371
Yeah, it's like a version of the mac mini.
00:17:00.491 --> 00:17:08.588
Yeah, yeah yeah, exactly yeah, mac mini, that's, that's the one and uh, they're claiming it's the first one out there where, kind of like, all the heavy lifting is done in the cloud.
00:17:08.588 --> 00:17:12.705
So it reminds me of back in the day, right where you had these things called thin clients.
00:17:13.056 --> 00:17:14.319
Well, virtual desktop.
00:17:14.319 --> 00:17:15.744
This is a dumb terminal.
00:17:16.204 --> 00:17:27.073
It's a dumb terminal where the back end is Azure rather than your server down the hallway type thing, which is how you know mainframes in a lot of organizations used to run in the old days.
00:17:27.954 --> 00:17:34.180
So it's just a cloud version of that and you can imagine right as in if you watch the video and stuff on it and warehousing and stuff like that.
00:17:34.180 --> 00:17:35.123
What a brilliant idea.
00:17:35.123 --> 00:17:37.134
You know you can have that little terminal.
00:17:37.134 --> 00:17:41.421
It does all the work around, you know, scanning, whatever they have to do.
00:17:41.421 --> 00:17:56.914
But you don't have to have a desktop computer sitting there for folks in the business where you need a computer, maybe connected to a printer, and can do a bunch of stuff, but the operating system at the end of the day is sitting in Azure.
00:17:57.414 --> 00:18:00.065
Yeah, and perfect for companies that just have virtual desktops.
00:18:00.065 --> 00:18:06.626
They just have that as the hardware sitting on the desk as well, and you know that's becoming more and more popular right.
00:18:06.646 --> 00:18:15.596
The security right would be would be off the richter because your security is going to be handled all in azure, not on device look at us talk about end user compute.
00:18:16.056 --> 00:18:22.519
Fair play to us yeah yes, yes, yes, the the the one thing that I liked.
00:18:22.519 --> 00:18:41.913
I have to admit I didn't see or read a lot of Ignite, but out of the news that I saw this morning going into work, the one thing that I find super interesting is the little interpreter bot in Teams.
00:18:41.913 --> 00:18:48.436
It's supposed to work real time and translate it into your language, and I don't know.
00:18:48.436 --> 00:18:48.959
I think there are.
00:18:49.019 --> 00:18:49.561
And your voice.
00:18:49.561 --> 00:18:57.405
So if you're talking Anna and you are speaking to a Japanese person, it still sounds like Anna speaking in Japanese in real time.
00:18:57.434 --> 00:19:01.807
But speaking in Japanese, can you imagine how that can break barriers?
00:19:01.807 --> 00:19:08.258
Because so far there was a barrier to technology, which is the english language.
00:19:08.258 --> 00:19:35.834
Right, no matter what we do, we need to uh, write code in the english language, the um, even the local platform, you know it's, it's, it's also in english, um, but now people who express themselves better in their own language, or rather people who understand better in their own language, have all these set of capabilities that they can surface.
00:19:35.834 --> 00:19:43.786
And how many of our projects actually fail because of a miscommunication somewhere?
00:19:44.557 --> 00:19:46.643
I mean most projects fail due to that.
00:19:46.682 --> 00:19:46.942
Yeah.
00:19:47.505 --> 00:19:47.665
Yeah.
00:19:47.665 --> 00:19:52.987
So here's another term that I heard a lot of, which is shadow AI.
00:19:52.987 --> 00:20:01.301
You know, just like shadow IT in the past, right, and one of the stats that they presented was 75% of people are already using AI at work.
00:20:01.301 --> 00:20:04.284
78% bring their own AI.
00:20:04.284 --> 00:20:09.164
So in other words, they're using their own tools Chat, gpt and other things.
00:20:09.164 --> 00:20:12.980
Yeah, yeah, oh, yeah, yeah, which is not sanctioned by you know.
00:20:12.980 --> 00:20:44.986
So you know the risk is, of course, you know they're training models or handing their data off to unsecure environments, but people are people, right, and they're like I'm just going to get a job done and they're not like concerned so much about the PDF you know that they're handing up, or the Word document, excel, et cetera might contain, you know, information that is proprietary to that organization, that they wouldn't want handed up to some random service so you can do your AI processing on it.
00:20:45.575 --> 00:21:08.762
I think that's so interesting because today I was talking to a friend and our friend, Chris, right, he's really into AI security and AI governance and how do we make a rule and how do we package it all in a box and ship it to people so that they can do this thing properly?
00:21:08.762 --> 00:21:12.075
We all know that he's like super interested in that.
00:21:12.075 --> 00:21:21.201
We were talking about companies who want to deliver an AI product and one needs to come with that, Like what are the safety policies?
00:21:21.201 --> 00:21:24.468
What's you know DSP in a box, right?
00:21:24.595 --> 00:21:26.381
Like digital safety board in a box.
00:21:26.982 --> 00:21:27.464
Exactly.
00:21:27.464 --> 00:21:38.887
It's interesting that you say that, mark, because today when we were talking, I was like, okay, cool with the products that this company is.
00:21:38.887 --> 00:21:43.181
You know presumably producing and shipping to a customer.
00:21:43.181 --> 00:21:50.607
Know presumably producing and shipping to a customer, but what about all of the end result of ai that people are using like every day and that goes unchecked?
00:21:50.607 --> 00:21:53.455
Yeah how about a safety board for that?
00:21:53.536 --> 00:21:59.896
exactly with what you're saying, shadow ai here's the thing, and this is where I think there's a lot for us to do.
00:21:59.896 --> 00:22:10.641
Um another and basically this is a survey of 4 000 companies done by our work trends index annual report 2024 microsoft and linkedin.
00:22:10.641 --> 00:22:19.961
60 of organizations say their organization lacks a plan and vision to implement ai 60.
00:22:19.961 --> 00:22:27.330
That is a crazy number when it comes to like your strategy, your vision and what you're going to do.
00:22:28.315 --> 00:22:29.420
But does it surprise us?
00:22:29.420 --> 00:22:42.463
Because actually, we could probably wrap that number around data, around low code, around cloud rationalization, around stuff that's been around for much longer than generative AI, because when we talk about AI, we're talking about generative AI at the moment, aren't we?
00:22:42.463 --> 00:22:43.940
Yes, yes, of course.
00:22:51.035 --> 00:22:52.218
Plug for the AI strategy framework.
00:22:52.218 --> 00:22:53.140
Right, the, this is your shortcut.
00:22:53.140 --> 00:22:58.011
Okay, absolutely, and and and cloud lighthouse will do the thing for you with you.
00:22:58.011 --> 00:23:10.564
Actually, that I've been running around doing this, you know, helping several big organizations build theirs, and you know a couple of things that have come out that I've seen here is that one?
00:23:10.564 --> 00:23:13.556
It's obviously really hard, right.
00:23:13.556 --> 00:23:20.087
So just having the strategy, the AI strategy framework, is not enough.
00:23:20.087 --> 00:23:20.989
It needs to be.
00:23:20.989 --> 00:23:31.189
You know, you need a framework like that in the hands of someone who is actually able to help you, you know, get the organization on that path.
00:23:31.189 --> 00:23:32.050
So that's one.
00:23:32.635 --> 00:23:39.755
Another point that I see here is that it's as with any strategy, it's not just about building the strategy.
00:23:39.755 --> 00:23:45.875
It is also about having the wherewithal and the organizational juice to execute that strategy.
00:23:45.875 --> 00:24:05.390
So I would say that, you know, I'm personally working with several organizations, a number of organizations that are building that AI strategy, and I kind of finish the strategy crafting and I think to myself, in at least half the cases, there is no way that this organization is going to have the wherewithal to actually do this.
00:24:05.390 --> 00:24:07.881
Yeah, like to actually get this done, and that is a.
00:24:07.881 --> 00:24:11.777
That is not a lack of, that's not about a lack of talent or knowledge.
00:24:11.777 --> 00:24:12.178
That is a.
00:24:12.178 --> 00:24:13.840
That is a lack of will.
00:24:13.840 --> 00:24:19.838
Um in in, not not william, a lack of willpower no, no, no, loud and clear.
00:24:20.259 --> 00:24:31.634
Loud and clear, andrew the third point and this came up in a very recent in some very recent work that I was doing with one of these organizations I want to go back to the shadow ai.
00:24:31.634 --> 00:24:44.157
Right is that this the shadow ai phenomenon in this particular organization is is rampant, and you know, I think that that organizations are going take just as they always have with shadow IT.
00:24:44.157 --> 00:24:52.123
They're going to take one of two approaches here either to try to lock it down or to do better right.
00:24:52.123 --> 00:25:21.087
Or even if you're a C-level leader or a leader that's not in technology, that's not in the IT space, locking it down cannot be the answer here, because locking it down equals you will likely fail as an organization over the next five years or so because you won't be competitive.
00:25:21.087 --> 00:25:30.128
So the answer has to be do better so that your users don't have to turn to shadow ai yeah, but I think a lot, many of them won't.
00:25:30.249 --> 00:25:33.740
Many of them won't well, it's a no-brainer, right as in.
00:25:33.740 --> 00:25:36.871
I can understand why shadow ai is taken off.
00:25:36.871 --> 00:25:44.987
Like I'll get somebody send a screenshot which has text in it and in a heartbeat I just upload that and say export that as text.
00:25:45.166 --> 00:25:48.462
Right, and so yeah I was gonna say why do we use any tools.
00:25:48.462 --> 00:25:50.128
It's where it's an era of convenience.
00:25:50.128 --> 00:25:50.891
We live in people.
00:25:50.891 --> 00:25:52.799
People want things to be convenient.
00:25:52.819 --> 00:26:18.602
Sorry, mark, uh, the caffeine's kicked in from the coda and I've just just rocketed off people want things to be convenient, but uh, we we also, like I, do feel that we are stepping into the trap of luxury of AI, if you will, just by using unauthorized tools or whatever.
00:26:18.682 --> 00:26:41.082
Spitting out results and using them in your organization doesn't make you smarter, and using them in your organization doesn't make you smarter, Like, without having these sort of governance steps or like a framework in place as an organization to recognize these behaviors, you're only going to be effective for like five minutes and then you're going to fail because you're going to make mistakes, right?
00:26:41.082 --> 00:27:07.967
So today I was at Curve's office for us to work on this project and I saw a friend of mine who happens to work in the same building and I went to research a little bit about her company, where she works, and I knew that they do AI, but what they do is actually, do you know what they do?
00:27:07.967 --> 00:27:18.240
They use artificial intelligence solutions and generative AI to optimize code at large scale, like data science optimization.
00:27:18.240 --> 00:27:19.601
That's pretty cool.
00:27:21.165 --> 00:27:22.307
That's pretty cool.
00:27:22.346 --> 00:27:31.941
So, we're starting to see really amazing tools to actually use AI in a structured way for real results.
00:27:34.509 --> 00:27:45.818
Yeah, I still think that this is, I mean, obviously, really innovative technologies are always put to work first by technologists, right?
00:27:45.818 --> 00:28:06.190
So you know, but I think that some of the most impressive, some of the most impressive uses of AI that that we've seen to date have a lot to do with interpreting interpreting data at scale Right, or optimizing code at scale Right.
00:28:06.190 --> 00:28:16.664
I mean so, so, and I don't know if this is still the case, but for a long time, GitHub Copilot was by far the most successful of of the Copilot.
00:28:16.664 --> 00:28:19.393
So you know, that's that's a.
00:28:19.393 --> 00:28:20.395
That's interesting what they're doing.
00:28:20.664 --> 00:28:47.566
Yeah, I think that the big thing for GitHub Copilot is that they one of the complaints about it is that only used open AI models about it is it only used open ai models and one of the other new features is now you can select from a a range of ai models, um like from different parties I believe that's a new feature in co-pilot studio as well, which yeah did, yeah, yeah, yeah as an infoundry, particularly a lot, in fact, you know, as a feature.
00:28:47.586 --> 00:28:57.338
And the other thing in ai foundry that I think is really important in the diagram that came out is the two-way integration between that and ai studio.
00:28:57.338 --> 00:29:25.230
So it's going to allow this kind of you know framework for those that want to you know whizzy wig build ai solutions using co-pilot studio to be able to have that extend then into um azure ai foundry and really go and, let's say, bring in a tailored piece of ai work that has been done by a pro dev team and consume that and vice versa.
00:29:25.230 --> 00:29:39.732
So it's kind of like dare I say it and I hate the word, but we've had it for some time which is this no-cliffs type experience right the way through from Copilot M365, which I don't know if you saw the branding of that has changed as well.
00:29:39.732 --> 00:29:48.325
So your SaaS solution through to your tailored solution with Copilot Studio, through to your advanced developer solutions in Foundry.
00:29:48.325 --> 00:29:52.676
I think it's Microsoft constructing a very robust end-to-end story.
00:29:53.585 --> 00:29:59.631
Can we be clear on the rebranding that you just mentioned so that everyone listening at home can keep up with this?
00:29:59.631 --> 00:30:02.534
What is specifically that rebranding Mark?
00:30:03.484 --> 00:30:15.234
So the co-pilot that we would typically you know bought for 30, is it 30 US a month inside your organization that there is Copilot M365.
00:30:15.234 --> 00:30:15.234
?
00:30:16.164 --> 00:30:20.316
Copilot M365, not Copilot for M365.
00:30:20.517 --> 00:30:20.717
Nope.
00:30:20.717 --> 00:30:27.875
So it has a Copilot logo with the, you know, in beautiful black font M365 branded on it.
00:30:27.875 --> 00:30:37.830
Now, and it basically covers 365 branded on it now and it basically covers five.
00:30:37.830 --> 00:30:40.681
It covers all the stuff that would be included in your m365 subscription from a co-pilot perspective.
00:30:40.701 --> 00:30:55.693
I was just going to say, just as a little aside, I to this day I was just talking to someone about this recently that that the 365 or the 365 branding still is dumb to me, right, because, like, and I remember when it came out, right.
00:30:56.145 --> 00:30:57.308
I love the fact that we have.
00:30:57.348 --> 00:30:57.528
New.
00:30:57.548 --> 00:30:59.513
Zealand 365.
00:30:59.513 --> 00:31:01.258
No it's true, it's true right.
00:31:03.730 --> 00:31:04.335
Hear me out on this.
00:31:04.335 --> 00:31:05.605
Hear me out on this, of course.
00:31:05.605 --> 00:31:09.435
So Mark did not come up with the branding.
00:31:09.435 --> 00:31:15.611
Mark is simply jumped on the bandwagon of the branding, and here's my issue with it.
00:31:15.611 --> 00:31:28.505
Right, I always thought it should have been Microsoft 360 or Dynamics 360, because were people sitting around wondering if Microsoft 365 worked on Sundays?
00:31:28.505 --> 00:31:32.656
Like did we need to be reassured that it worked every day of the year?
00:31:32.656 --> 00:31:42.676
Like it just always felt to me like this was, like the branding was conveying a message that did not need to be conveyed because it was the answer to a question nobody was asking.
00:31:42.676 --> 00:31:50.700
Microsoft Office does not celebrate the Sabbath, nor does it observe the sabbath or celebrate holidays.
00:31:50.700 --> 00:31:51.541
Just to be clear.
00:31:51.541 --> 00:31:58.496
Right, it works every day and you have now been reminded via this apparently permanent branding.
00:31:58.496 --> 00:31:59.278
End of rant.
00:31:59.278 --> 00:31:59.825
I'm sorry.
00:31:59.845 --> 00:32:12.473
Back to you, nz, nz 360 guy nz 365 guy, yeah, um, yeah, no, very good, very good it's um so much trouble after this episode no, I, I don't, I don't.
00:32:12.473 --> 00:32:15.996
It's interesting that you know that it wasn't 360.
00:32:15.996 --> 00:32:22.071
You know, 360 degree view, you know all around there's like lots of metaphors that would play off that.
00:32:22.071 --> 00:32:24.877
But yeah, who knows where it came from.
00:32:24.877 --> 00:32:30.153
I just was surprised when they dropped the office 365 and became out with M365.
00:32:30.153 --> 00:32:34.702
But Microsoft's a master of keep rebranding right, keep changing.
00:32:34.765 --> 00:32:37.713
It's just all year round productivity Mark.
00:32:37.713 --> 00:32:38.395
That's what it means.
00:32:38.395 --> 00:32:40.693
It works every day just like Mark.
00:32:42.345 --> 00:32:43.451
Yeah, not so much.
00:32:43.451 --> 00:32:48.153
Well, that kind of wraps us for this session.
00:32:48.153 --> 00:32:52.423
Indeed, go check out the ignite website.
00:32:52.423 --> 00:32:54.407
You can go and watch my stuff on playback.
00:32:55.269 --> 00:33:12.506
I will throw to will to kind of wrap us up I, uh, I've been so impressed that we try to keep a golden thread going throughout all this with ignite, and we went off on many sort of tangents and, uh, you know, went from from British drinking business culture all the way to other things.
00:33:12.506 --> 00:33:13.709
I think it's just been fantastic.
00:33:13.709 --> 00:33:24.009
So I, for one, I'm looking forward to going off and digesting a bit more of that big book of news and engaging in the comments with anyone that's listening to this podcast.
00:33:24.009 --> 00:33:27.597
So have a great day and speak soon.
00:33:28.701 --> 00:33:30.546
Thanks for tuning into the Ecosystem Show.
00:33:30.546 --> 00:33:36.592
We hope you found today's discussion insightful and thought-provoking, and maybe you had a laugh or two.
00:33:36.592 --> 00:33:42.613
Remember your feedback and challenges help us all grow, so don't hesitate to share your perspective.
00:33:42.613 --> 00:33:48.684
Stay connected with us for more innovative ideas and strategies to enhance your software estate.
00:33:48.684 --> 00:33:52.751
Until next time, keep pushing the boundaries and creating value.
00:33:52.751 --> 00:33:54.329
See you on the next episode.
00:00:01.080 --> 00:00:02.685
Welcome to the Ecosystem Show.
00:00:02.685 --> 00:00:05.160
We're thrilled to have you with us here.
00:00:05.160 --> 00:00:11.153
We challenge traditional mindsets and explore innovative approaches to maximizing the value of your software estate.
00:00:11.153 --> 00:00:13.523
We don't expect you to agree with everything.
00:00:13.523 --> 00:00:17.472
Challenge us, share your thoughts and let's grow together.
00:00:17.472 --> 00:00:19.545
Now let's dive in.
00:00:19.545 --> 00:00:20.528
It's showtime.
00:00:20.528 --> 00:00:22.382
Welcome back, everybody.
00:00:22.382 --> 00:00:23.463
We're live on air.
00:00:23.463 --> 00:00:30.356
We have our reporter in the field, mr Huntingford, coming all the way from Ignite 2024.
00:00:30.356 --> 00:00:32.146
Chris, how's it there?
00:00:38.262 --> 00:00:47.344
So what I feel like we can summarize this week, as the four of us have worked like dogs while Chris has partied like it's 2019.
00:00:47.866 --> 00:00:48.167
Exactly.
00:00:48.167 --> 00:00:51.387
I'm sure it's been hectic for him, though.
00:00:52.200 --> 00:00:54.307
I love when you say been, I have been.
00:00:55.581 --> 00:00:56.524
Nice, nice.
00:00:56.926 --> 00:01:00.006
Do you guys think that's because Chris never went to bed?
00:01:00.006 --> 00:01:07.927
It's possible, let's just check Chris's expense app to see when.
00:01:07.968 --> 00:01:10.093
Chris stopped buying alcohol last night yeah.
00:01:14.662 --> 00:01:18.013
So there were a lot of announcements this week, of course, at Ignite.
00:01:18.536 --> 00:01:18.775
Yeah.
00:01:19.381 --> 00:01:20.587
Anything, stand out for anybody.
00:01:22.001 --> 00:01:27.566
Agents, agents, agents, a lot of AI sessions, which is like shocking, isn't it?
00:01:28.040 --> 00:01:30.527
Over 200 AI sessions at Ignite.
00:01:31.849 --> 00:01:32.691
Hick of a lot right.
00:01:33.965 --> 00:01:34.831
And Contact Center.
00:01:34.831 --> 00:01:36.385
You know the emphasis on.
00:01:36.385 --> 00:01:37.111
Ivr, etc.
00:01:37.111 --> 00:01:39.606
At the moment has been pretty impressive, I must admit.
00:01:39.606 --> 00:01:48.173
Actually, most of the news I've missed, and I think Anna and Andrew may be in the same boat, because Anna and Andrew and I have been hanging out with each other this week almost every day doing work.
00:01:49.439 --> 00:01:57.025
Will, anna and I actually were all co-located and did actual work together this week, which was fun actually.
00:01:57.045 --> 00:01:57.447
I loved it.
00:01:57.447 --> 00:01:58.971
I really did like it.
00:01:59.640 --> 00:02:21.709
It was so good, like, just like going back to basics and like creating, um, you know, a new project that we believe in so much, and, once again, like seeing the uh, the experience of doing projects upon projects upon projects, and yeah and also, do you know what actually it's?
00:02:22.310 --> 00:02:25.340
it's one thing that you you know at senior layer and it needs to go higher and higher.
00:02:25.340 --> 00:02:27.329
You get quite removed and people you know what actually it's one thing that you know at senior layer and it needs to go higher and higher.
00:02:27.329 --> 00:02:34.400
You get quite removed and people you know I don't think it's a prag, but people do say, oh, I haven't done a workshop for years and stuff like that.
00:02:34.400 --> 00:02:36.188
Well then, how are you sharpening your tools?
00:02:36.188 --> 00:02:37.174
And you know, I loved it.
00:02:37.300 --> 00:02:39.328
I was in a room with Anna today and I love working with Anna.
00:02:39.328 --> 00:02:47.227
I love working with Andrew, but he wasn't there today and I got to get out a whiteboard.
00:02:47.227 --> 00:02:49.094
You know, just get a pen onto a whiteboard drawing out architecture, discussing and debate.
00:02:49.094 --> 00:02:49.516
You can't beat that.
00:02:49.516 --> 00:02:59.560
That's why you got to exactly where you wanted to be and where you are in your career, because you loved doing the workshops, you loved doing the basics and you loved engaging and debating over, in this case, tech, and I just loved it.
00:02:59.560 --> 00:03:06.611
And getting to do it with andrew and anna, who have been friends of mine for years, but now actually getting to work with them and realize actually andrew is as good as he seems on paper.
00:03:06.611 --> 00:03:08.014
Well, uh, it was really good.
00:03:08.014 --> 00:03:10.430
Obviously, I've worked with anna for a long time.
00:03:10.430 --> 00:03:14.144
Well, some people look great on paper but are shocking when you engage with them.
00:03:14.144 --> 00:03:17.861
But in this case, I actually said this to andrew when he was on a room on his own with me.
00:03:18.984 --> 00:03:22.549
He did so we were, we were, we were in, we were in the room, just the of us.
00:03:22.549 --> 00:03:37.014
We were looking at this massive data model that I had put together and Will sort of pulls me close and I don't know what's about to happen and he says you know, andrew, some people that you expect to know what they're talking about end up being shit.
00:03:37.580 --> 00:03:41.288
And I thought that was about to be followed by and you're one of them.
00:03:41.429 --> 00:03:43.612
No, I was impressed.
00:03:43.612 --> 00:03:46.284
We're looking at a at data models.
00:03:46.284 --> 00:03:55.004
He designed it so elegantly, with best practices front of mind, and I was looking at this, this, this particular piece of it, which we know famously.
00:03:55.004 --> 00:04:00.348
Even microsoft have had scalability issues around in the past and andrew, just it was just fantastic.
00:04:00.427 --> 00:04:06.250
And I said, right, you know always nervous working with friends that you know might be good and turn out to be awful.
00:04:06.250 --> 00:04:14.693
I was like, and in this case I'm very happy because I knew you were going to be great, and you are Awesome, awesome, thanks, man.
00:04:15.479 --> 00:04:32.805
But it's really cool because we read, you know, all of the new capabilities and the ideas and you know and everything else, and how do we get started with AI and what sort of governance we need to put in place, what are the processes, how do we design, how do we build a practice?
00:04:32.805 --> 00:04:42.119
But we mustn't forget that once upon a time we used to like build databases and that's valuable, like that's really valuable.
00:04:42.380 --> 00:04:43.404
It's so crucial.
00:04:43.786 --> 00:04:47.142
Yeah, this thing and I promise we'll get, we'll get back to ignite.
00:04:47.142 --> 00:04:55.588
I made I I anticipated the question and made a list of things that were announced this week that I am excited about however, it was.
00:04:56.108 --> 00:05:09.865
It was really, um, one of my favorite, uh, technical tasks to do is data modeling and I I'm not talking about little models, but like really big, large scale data models.
00:05:09.865 --> 00:05:36.423
I learned, I learned, everything I know about data modeling from Dave Milton, who's the technical director for the Microsoft Global Blackbelts now for the Western Hemisphere, for the Americas, and you know back in, you know back in the day, americas, and you know back in, you know back in the day, and this, this thing that we're all working on together, has been so much fun because I've gotten to, you know, I've gotten to go do this thing that I actually find really enjoyable.
00:05:36.423 --> 00:05:48.954
And, yeah, it's, it's absolutely massive and it's in, it's in safe, it's in safe, safe hands with, with Anna taking the, taking the lead from here, I think.
00:05:50.021 --> 00:05:59.862
Oh, I think it's with with, actually, the implementation team, who are really really amazing and wonderful, and that's just so great.
00:05:59.862 --> 00:06:04.050
As you can tell, we're really passionate about this project because of the.
00:06:04.050 --> 00:06:06.574
It's also because of the cause.
00:06:06.574 --> 00:06:15.418
You know, it's like a feel good humanitarian project that we're really, really into.
00:06:15.418 --> 00:06:25.744
It's like the sort of thing that you've always dreamed to be able to do and you never thought you could, and now we have this opportunity.
00:06:25.744 --> 00:06:26.425
It's amazing.
00:06:26.927 --> 00:06:28.591
Absolutely All right.
00:06:28.591 --> 00:06:31.569
So the love fest between the three of us is over, mark, we're sorry.
00:06:31.728 --> 00:06:35.387
We're sorry, it's just getting going, mate, don't you worry.
00:06:36.862 --> 00:06:38.668
I was letting you guys go for it.
00:06:38.668 --> 00:06:41.447
The term circle jerk came to mind.
00:06:44.045 --> 00:06:47.833
But again, this is a podcast what's your favorite news?
00:06:48.942 --> 00:06:50.766
mark from from ignite.
00:06:50.766 --> 00:06:52.850
Uh, what do you?
00:06:52.850 --> 00:06:56.098
Think is most exciting uh, about what?
00:06:56.139 --> 00:06:57.242
the announcements of this week.
00:06:57.242 --> 00:06:58.485
Well, andrew has a list.
00:06:58.485 --> 00:06:59.827
Andrew, what's on your list?
00:07:00.670 --> 00:07:03.403
all right, all right, so so well deflected.
00:07:03.403 --> 00:07:08.603
Yeah, mark, mark couldn't, mark couldn't, mark couldn't get the the book of news to open.
00:07:08.603 --> 00:07:08.944
Is that?
00:07:08.944 --> 00:07:09.687
Is that what I'm hearing?
00:07:09.747 --> 00:07:10.350
Come on quickly.
00:07:12.201 --> 00:07:15.458
No, no, I didn't even attempt, as an animal was trying to get the book of news open.
00:07:15.458 --> 00:07:17.360
I haven't even touched the book of news.
00:07:17.581 --> 00:07:17.940
I have.
00:07:17.940 --> 00:07:21.122
I have it's open right now so I can check.
00:07:21.122 --> 00:07:24.845
I can fact check to see whether your list is correct.
00:07:24.964 --> 00:07:30.028
So here are the five things, in no particular order, that I would say.
00:07:30.028 --> 00:07:51.410
I'm going to hold off on whether I'm excited, but I am intrigued by uh transactional, uh databases built on, you know, built with azure sql, that you can now quickly spin up, spin down, build uh, build applications on top of in fabric.
00:07:51.410 --> 00:07:55.288
So actually I'll just read them off and then we can, we can dig into these if we want.
00:07:55.288 --> 00:08:28.451
So fabric databases, one lake catalog, a co-pilot studio embedded in power apps, which I think is intriguing, like the ability to build I'll call them mini agents inside of your app, which, of course, has brought to mind sort of flashbacks from how Microsoft has never really figured out a clean way to deal with in-app automation, as evidenced by the fact that some of us are still using classic workflows because there's nothing else that can do the job.
00:08:28.451 --> 00:08:31.375
So I think that's interesting.
00:08:32.299 --> 00:08:37.413
There's also supposedly You're going to be like crucified for that.
00:08:40.620 --> 00:08:58.323
I'm sure there's also supposedly deeper RAG capabilities in Copilot Studio, which I think is potentially representative of a broader blurring between Copilot Studio and Azure AI Foundry, formerly known as Azure AI Studio, but there's been a rebrand.
00:08:58.323 --> 00:08:59.950
We can't have Ignite without a rebrand.
00:08:59.950 --> 00:09:34.100
And then the final one that has piqued my interest is these managed security and managed operations capabilities in Power Platform, coming to the Power Platform Admin Center, I presume, from enterprise management via COE starter kit to actual enterprise management via an actual scalable set of tools.
00:09:34.100 --> 00:09:35.703
So I think that's interesting as well.
00:09:35.703 --> 00:09:36.969
Those are my five.
00:09:36.969 --> 00:09:39.489
I'm sure there's others that I've missed, but those are my five.
00:09:40.251 --> 00:09:53.296
Nice, very good, I think you're on point around the governance piece that's obviously coming out as part of the Power Platform, particularly on Copilot Studio and having that level of governance in there.
00:09:53.296 --> 00:10:01.091
I think a lot of people in customer land were really wanting that type of control over who's creating what.
00:10:01.091 --> 00:10:05.538
Also, for the first time, new licensing for co-pilot studio.
00:10:05.538 --> 00:10:07.144
A lot of people were like hang on a second.
00:10:07.144 --> 00:10:14.347
The licensing hadn't changed since when it was called power virtual agents, which was based on number of messages etc.
00:10:14.347 --> 00:10:16.613
And now it wasn't just a chatbot tool anymore.
00:10:16.613 --> 00:10:20.491
But there was kind of no iteration of that and of course now there is.
00:10:20.633 --> 00:10:23.522
You can go for, uh, on demand type licensing.
00:10:23.522 --> 00:10:32.486
It still raises a thing you organizations, as they start committing to these tools, have kind of got no understanding of how much it's going to cost them.
00:10:32.486 --> 00:10:49.091
In a way, it's almost like there needs to be some type of t-shirt sizing for well, if you're going to do this, it's going to consume about that rather than just suck it and see and see how much you clock up on your, your bill for the month, right, um, which can be crazy.
00:10:49.091 --> 00:10:54.225
The other, the other thing that I thought was interesting is andrew is laughing see, I'm sorry.
00:10:54.245 --> 00:10:56.229
Like, is that a kiwi phrase?
00:10:56.229 --> 00:10:58.373
No, no, that's a common phrase.
00:10:58.373 --> 00:11:07.152
No, we use that in the uk all the time you do, yeah, you do, suck it, yeah, it's very common I've lived here for four years and I've never heard someone say that.
00:11:07.393 --> 00:11:07.855
Have you not?
00:11:07.855 --> 00:11:09.605
You're hanging with the wrong crowds mate.
00:11:10.207 --> 00:11:11.380
Yeah, yeah, you know what Actually?
00:11:12.484 --> 00:11:15.251
so Will just sorry an aside.
00:11:15.251 --> 00:11:19.751
I want to talk about business drinking culture in the United Kingdom.
00:11:19.751 --> 00:11:22.345
Let's put a pit in that and come back to it after Mark.
00:11:22.365 --> 00:11:23.708
Let's not even turn over that rock.
00:11:23.708 --> 00:11:26.725
No one needs to look under there.
00:11:28.847 --> 00:11:30.320
I mean, I think we should turn that rock.
00:11:30.320 --> 00:11:35.768
I already turned over the classic workflows rock, which I feel like that needs a shout every six months or so.
00:11:36.269 --> 00:11:39.150
Suck it and see it's apparently British English in origin.
00:11:40.157 --> 00:11:40.639
Ah, there you go.
00:11:42.202 --> 00:11:46.131
So you used to suggest the only way to know something will work or be suitable is to try it.
00:11:46.131 --> 00:11:48.092
You know it's a coincidence.
00:11:48.134 --> 00:11:48.457
There you go.
00:11:49.259 --> 00:11:51.144
I tried to figure out who was the first to coin it.
00:11:51.144 --> 00:11:52.267
Probably Mark Smith.
00:11:52.628 --> 00:12:02.606
Ha ha Ha ha, I could go further in how we could expand on this, but I'm just going to reign it in.
00:12:05.140 --> 00:12:21.951
It's a very unique name as well as well, I mean typing that in on google this late at night was probably my first, my first issue, but but luckily it all stayed pg, so but talking about drinking culture, I was shocked my first day in london.
00:12:21.991 --> 00:12:24.866
When I moved to london I was living in the business district.
00:12:24.866 --> 00:12:25.229
I sorry I was.
00:12:25.229 --> 00:12:28.500
I was living in the city of London right in the financial district yeah.
00:12:28.500 --> 00:12:37.759
And I rock out of my apartment and it's like 1030 am on a Monday and the bar was.
00:12:37.759 --> 00:12:44.663
People were like right out the door, you know, like going for it, and this is like 1030 on a Monday morning.
00:12:44.864 --> 00:12:47.323
So so your apartment was above Ledenhall Market.
00:12:47.323 --> 00:12:48.408
Is that the idea?
00:12:49.563 --> 00:12:49.663
here.
00:12:49.663 --> 00:12:50.707
I couldn't believe it.
00:12:50.707 --> 00:12:51.923
No, it wasn't.
00:12:51.923 --> 00:12:55.826
It was over by what's the big dumb cathedral there?
00:12:56.500 --> 00:12:57.363
Did you say the?
00:12:57.363 --> 00:12:58.947
Big dumb cathedral.
00:12:59.749 --> 00:12:59.970
No no.
00:12:59.970 --> 00:13:01.860
I said what was the big cathedral over there?
00:13:02.808 --> 00:13:05.926
Sorry, you clicked out and I thought you said the big dumb cathedral.
00:13:05.926 --> 00:13:06.707
No, no.
00:13:07.109 --> 00:13:14.253
It's quite commonplace, so it's like I've never really walked past a Wetherspoons that doesn't have a queue before opening, you know, for people to get their ale and stuff.
00:13:14.253 --> 00:13:17.909
So, yeah, and it's probably the people out there, the ones that hate Mondays at half ten.
00:13:17.909 --> 00:13:19.245
So you know, just join them.
00:13:21.961 --> 00:13:35.900
Yeah, but working in either in insurance or in, but mostly like around Lloyd's Market, you know the insurers, brokers, stuff like that there's.
00:13:35.900 --> 00:13:43.062
No, you cannot get a sensible phrase out of anybody after lunch, Like it's just, it's a thing.
00:13:43.563 --> 00:13:53.422
But at the same time you also don't have visibility of any deals, any like.
00:13:53.903 --> 00:13:56.912
No transparency, no data, no nothing.
00:13:56.912 --> 00:14:00.208
So I would be very curious to see it right now.
00:14:00.208 --> 00:14:02.383
Because when was that Mark?
00:14:02.383 --> 00:14:04.206
When you moved to London?
00:14:04.246 --> 00:14:06.051
When was it yeah 2017.
00:14:06.051 --> 00:14:07.173
I think when was it yeah 2017.
00:14:07.173 --> 00:14:08.296
I think it was 2017.
00:14:08.296 --> 00:14:09.057
Yeah.
00:14:09.057 --> 00:14:16.169
The person I had a drink with there was in that area, because they were working in that area.
00:14:16.169 --> 00:14:19.033
Who Scott Durow?
00:14:20.076 --> 00:14:28.118
scott deroe yeah, he was working at metro bank at the time well, I mean, who wasn't, who wasn't working at metro bank at the time?
00:14:28.139 --> 00:14:43.548
yeah, yeah, yeah, yeah no, but the reason this came up, the reason this that I thought of this, was that so yesterday, as we, as we said, you know, there was this, there was this team, uh, that we had, you know, put together, uh, working on this, working on this thing together.
00:14:43.548 --> 00:14:56.240
Uh, anna and will and I were all there and it was kind of a mixed team of folks who had come from, who were based here in the UK and who had come from the US for these working sessions.
00:14:56.240 --> 00:15:32.207
And I was chatting with one of the Americans, not like myself, an American living in Britain, but an American living in the United States, and somehow, you know, it came up and I said you will find, if you hang out here long enough, that Britain has a drinks after work many days in London that you don't have in the US, because in the US you have to drive somewhere that's correct yeah gotcha.
00:15:32.635 --> 00:15:35.706
I think a lot of that goes back to a lack of right exactly.
00:15:37.278 --> 00:15:38.443
Business as usual, mate.
00:15:40.335 --> 00:15:42.985
But when I moved here, it was astonishing to me, right.
00:15:42.985 --> 00:15:47.506
It was like why are these people out all the time drinking?
00:15:47.506 --> 00:15:56.907
As if it's like this expectation that you work in the UK, therefore you will all be drinking together in a posse every night of the week.
00:15:56.907 --> 00:15:59.543
That was jarring for me when I came here.
00:15:59.894 --> 00:16:01.438
It's the only way to get over the weather.
00:16:01.458 --> 00:16:06.663
really, it's so true, I thought I didn't want to get out of bed today.
00:16:06.663 --> 00:16:18.895
One of the other things that came up at Ignite that I thought was interesting now that we've taken the pin out of that subject and dealt with it was.
00:16:18.895 --> 00:16:21.283
Windows 365 Link.
00:16:21.283 --> 00:16:24.039
Did you see that Windows 365 Link?
00:16:24.039 --> 00:16:25.143
I haven't seen that one.
00:16:25.143 --> 00:16:25.563
Tell us more.
00:16:25.583 --> 00:16:26.726
They reckon it's the first.
00:16:26.726 --> 00:16:29.803
It looks like an Apple computer.
00:16:29.803 --> 00:16:34.101
You know the little square computers that Apple have that are just you've got to plug in a screen, keyboard and stuff.
00:16:34.101 --> 00:16:54.009
So this here is a little box about the you know the size of two packs of fags, and it allows you to plug in, uh, your keyboard, mouse and the whole operating system is running from the cloud, so from running from an azure it's like a little apple.
00:16:55.298 --> 00:16:57.784
Yeah, it is sorry but it is.
00:16:57.784 --> 00:16:58.186
It is.
00:16:58.186 --> 00:17:00.371
Yeah, it's like a version of the mac mini.
00:17:00.491 --> 00:17:08.588
Yeah, yeah yeah, exactly yeah, mac mini, that's, that's the one and uh, they're claiming it's the first one out there where, kind of like, all the heavy lifting is done in the cloud.
00:17:08.588 --> 00:17:12.705
So it reminds me of back in the day, right where you had these things called thin clients.
00:17:13.056 --> 00:17:14.319
Well, virtual desktop.
00:17:14.319 --> 00:17:15.744
This is a dumb terminal.
00:17:16.204 --> 00:17:27.073
It's a dumb terminal where the back end is Azure rather than your server down the hallway type thing, which is how you know mainframes in a lot of organizations used to run in the old days.
00:17:27.954 --> 00:17:34.180
So it's just a cloud version of that and you can imagine right as in if you watch the video and stuff on it and warehousing and stuff like that.
00:17:34.180 --> 00:17:35.123
What a brilliant idea.
00:17:35.123 --> 00:17:37.134
You know you can have that little terminal.
00:17:37.134 --> 00:17:41.421
It does all the work around, you know, scanning, whatever they have to do.
00:17:41.421 --> 00:17:56.914
But you don't have to have a desktop computer sitting there for folks in the business where you need a computer, maybe connected to a printer, and can do a bunch of stuff, but the operating system at the end of the day is sitting in Azure.
00:17:57.414 --> 00:18:00.065
Yeah, and perfect for companies that just have virtual desktops.
00:18:00.065 --> 00:18:06.626
They just have that as the hardware sitting on the desk as well, and you know that's becoming more and more popular right.
00:18:06.646 --> 00:18:15.596
The security right would be would be off the richter because your security is going to be handled all in azure, not on device look at us talk about end user compute.
00:18:16.056 --> 00:18:22.519
Fair play to us yeah yes, yes, yes, the the the one thing that I liked.
00:18:22.519 --> 00:18:41.913
I have to admit I didn't see or read a lot of Ignite, but out of the news that I saw this morning going into work, the one thing that I find super interesting is the little interpreter bot in Teams.
00:18:41.913 --> 00:18:48.436
It's supposed to work real time and translate it into your language, and I don't know.
00:18:48.436 --> 00:18:48.959
I think there are.
00:18:49.019 --> 00:18:49.561
And your voice.
00:18:49.561 --> 00:18:57.405
So if you're talking Anna and you are speaking to a Japanese person, it still sounds like Anna speaking in Japanese in real time.
00:18:57.434 --> 00:19:01.807
But speaking in Japanese, can you imagine how that can break barriers?
00:19:01.807 --> 00:19:08.258
Because so far there was a barrier to technology, which is the english language.
00:19:08.258 --> 00:19:35.834
Right, no matter what we do, we need to uh, write code in the english language, the um, even the local platform, you know it's, it's, it's also in english, um, but now people who express themselves better in their own language, or rather people who understand better in their own language, have all these set of capabilities that they can surface.
00:19:35.834 --> 00:19:43.786
And how many of our projects actually fail because of a miscommunication somewhere?
00:19:44.557 --> 00:19:46.643
I mean most projects fail due to that.
00:19:46.682 --> 00:19:46.942
Yeah.
00:19:47.505 --> 00:19:47.665
Yeah.
00:19:47.665 --> 00:19:52.987
So here's another term that I heard a lot of, which is shadow AI.
00:19:52.987 --> 00:20:01.301
You know, just like shadow IT in the past, right, and one of the stats that they presented was 75% of people are already using AI at work.
00:20:01.301 --> 00:20:04.284
78% bring their own AI.
00:20:04.284 --> 00:20:09.164
So in other words, they're using their own tools Chat, gpt and other things.
00:20:09.164 --> 00:20:12.980
Yeah, yeah, oh, yeah, yeah, which is not sanctioned by you know.
00:20:12.980 --> 00:20:44.986
So you know the risk is, of course, you know they're training models or handing their data off to unsecure environments, but people are people, right, and they're like I'm just going to get a job done and they're not like concerned so much about the PDF you know that they're handing up, or the Word document, excel, et cetera might contain, you know, information that is proprietary to that organization, that they wouldn't want handed up to some random service so you can do your AI processing on it.
00:20:45.575 --> 00:21:08.762
I think that's so interesting because today I was talking to a friend and our friend, Chris, right, he's really into AI security and AI governance and how do we make a rule and how do we package it all in a box and ship it to people so that they can do this thing properly?
00:21:08.762 --> 00:21:12.075
We all know that he's like super interested in that.
00:21:12.075 --> 00:21:21.201
We were talking about companies who want to deliver an AI product and one needs to come with that, Like what are the safety policies?
00:21:21.201 --> 00:21:24.468
What's you know DSP in a box, right?
00:21:24.595 --> 00:21:26.381
Like digital safety board in a box.
00:21:26.982 --> 00:21:27.464
Exactly.
00:21:27.464 --> 00:21:38.887
It's interesting that you say that, mark, because today when we were talking, I was like, okay, cool with the products that this company is.
00:21:38.887 --> 00:21:43.181
You know presumably producing and shipping to a customer.
00:21:43.181 --> 00:21:50.607
Know presumably producing and shipping to a customer, but what about all of the end result of ai that people are using like every day and that goes unchecked?
00:21:50.607 --> 00:21:53.455
Yeah how about a safety board for that?
00:21:53.536 --> 00:21:59.896
exactly with what you're saying, shadow ai here's the thing, and this is where I think there's a lot for us to do.
00:21:59.896 --> 00:22:10.641
Um another and basically this is a survey of 4 000 companies done by our work trends index annual report 2024 microsoft and linkedin.
00:22:10.641 --> 00:22:19.961
60 of organizations say their organization lacks a plan and vision to implement ai 60.
00:22:19.961 --> 00:22:27.330
That is a crazy number when it comes to like your strategy, your vision and what you're going to do.
00:22:28.315 --> 00:22:29.420
But does it surprise us?
00:22:29.420 --> 00:22:42.463
Because actually, we could probably wrap that number around data, around low code, around cloud rationalization, around stuff that's been around for much longer than generative AI, because when we talk about AI, we're talking about generative AI at the moment, aren't we?
00:22:42.463 --> 00:22:43.940
Yes, yes, of course.
00:22:51.035 --> 00:22:52.218
Plug for the AI strategy framework.
00:22:52.218 --> 00:22:53.140
Right, the, this is your shortcut.
00:22:53.140 --> 00:22:58.011
Okay, absolutely, and and and cloud lighthouse will do the thing for you with you.
00:22:58.011 --> 00:23:10.564
Actually, that I've been running around doing this, you know, helping several big organizations build theirs, and you know a couple of things that have come out that I've seen here is that one?
00:23:10.564 --> 00:23:13.556
It's obviously really hard, right.
00:23:13.556 --> 00:23:20.087
So just having the strategy, the AI strategy framework, is not enough.
00:23:20.087 --> 00:23:20.989
It needs to be.
00:23:20.989 --> 00:23:31.189
You know, you need a framework like that in the hands of someone who is actually able to help you, you know, get the organization on that path.
00:23:31.189 --> 00:23:32.050
So that's one.
00:23:32.635 --> 00:23:39.755
Another point that I see here is that it's as with any strategy, it's not just about building the strategy.
00:23:39.755 --> 00:23:45.875
It is also about having the wherewithal and the organizational juice to execute that strategy.
00:23:45.875 --> 00:24:05.390
So I would say that, you know, I'm personally working with several organizations, a number of organizations that are building that AI strategy, and I kind of finish the strategy crafting and I think to myself, in at least half the cases, there is no way that this organization is going to have the wherewithal to actually do this.
00:24:05.390 --> 00:24:07.881
Yeah, like to actually get this done, and that is a.
00:24:07.881 --> 00:24:11.777
That is not a lack of, that's not about a lack of talent or knowledge.
00:24:11.777 --> 00:24:12.178
That is a.
00:24:12.178 --> 00:24:13.840
That is a lack of will.
00:24:13.840 --> 00:24:19.838
Um in in, not not william, a lack of willpower no, no, no, loud and clear.
00:24:20.259 --> 00:24:31.634
Loud and clear, andrew the third point and this came up in a very recent in some very recent work that I was doing with one of these organizations I want to go back to the shadow ai.
00:24:31.634 --> 00:24:44.157
Right is that this the shadow ai phenomenon in this particular organization is is rampant, and you know, I think that that organizations are going take just as they always have with shadow IT.
00:24:44.157 --> 00:24:52.123
They're going to take one of two approaches here either to try to lock it down or to do better right.
00:24:52.123 --> 00:25:21.087
Or even if you're a C-level leader or a leader that's not in technology, that's not in the IT space, locking it down cannot be the answer here, because locking it down equals you will likely fail as an organization over the next five years or so because you won't be competitive.
00:25:21.087 --> 00:25:30.128
So the answer has to be do better so that your users don't have to turn to shadow ai yeah, but I think a lot, many of them won't.
00:25:30.249 --> 00:25:33.740
Many of them won't well, it's a no-brainer, right as in.
00:25:33.740 --> 00:25:36.871
I can understand why shadow ai is taken off.
00:25:36.871 --> 00:25:44.987
Like I'll get somebody send a screenshot which has text in it and in a heartbeat I just upload that and say export that as text.
00:25:45.166 --> 00:25:48.462
Right, and so yeah I was gonna say why do we use any tools.
00:25:48.462 --> 00:25:50.128
It's where it's an era of convenience.
00:25:50.128 --> 00:25:50.891
We live in people.
00:25:50.891 --> 00:25:52.799
People want things to be convenient.
00:25:52.819 --> 00:26:18.602
Sorry, mark, uh, the caffeine's kicked in from the coda and I've just just rocketed off people want things to be convenient, but uh, we we also, like I, do feel that we are stepping into the trap of luxury of AI, if you will, just by using unauthorized tools or whatever.
00:26:18.682 --> 00:26:41.082
Spitting out results and using them in your organization doesn't make you smarter, and using them in your organization doesn't make you smarter, Like, without having these sort of governance steps or like a framework in place as an organization to recognize these behaviors, you're only going to be effective for like five minutes and then you're going to fail because you're going to make mistakes, right?
00:26:41.082 --> 00:27:07.967
So today I was at Curve's office for us to work on this project and I saw a friend of mine who happens to work in the same building and I went to research a little bit about her company, where she works, and I knew that they do AI, but what they do is actually, do you know what they do?
00:27:07.967 --> 00:27:18.240
They use artificial intelligence solutions and generative AI to optimize code at large scale, like data science optimization.
00:27:18.240 --> 00:27:19.601
That's pretty cool.
00:27:21.165 --> 00:27:22.307
That's pretty cool.
00:27:22.346 --> 00:27:31.941
So, we're starting to see really amazing tools to actually use AI in a structured way for real results.
00:27:34.509 --> 00:27:45.818
Yeah, I still think that this is, I mean, obviously, really innovative technologies are always put to work first by technologists, right?
00:27:45.818 --> 00:28:06.190
So you know, but I think that some of the most impressive, some of the most impressive uses of AI that that we've seen to date have a lot to do with interpreting interpreting data at scale Right, or optimizing code at scale Right.
00:28:06.190 --> 00:28:16.664
I mean so, so, and I don't know if this is still the case, but for a long time, GitHub Copilot was by far the most successful of of the Copilot.
00:28:16.664 --> 00:28:19.393
So you know, that's that's a.
00:28:19.393 --> 00:28:20.395
That's interesting what they're doing.
00:28:20.664 --> 00:28:47.566
Yeah, I think that the big thing for GitHub Copilot is that they one of the complaints about it is that only used open AI models about it is it only used open ai models and one of the other new features is now you can select from a a range of ai models, um like from different parties I believe that's a new feature in co-pilot studio as well, which yeah did, yeah, yeah, yeah as an infoundry, particularly a lot, in fact, you know, as a feature.
00:28:47.586 --> 00:28:57.338
And the other thing in ai foundry that I think is really important in the diagram that came out is the two-way integration between that and ai studio.
00:28:57.338 --> 00:29:25.230
So it's going to allow this kind of you know framework for those that want to you know whizzy wig build ai solutions using co-pilot studio to be able to have that extend then into um azure ai foundry and really go and, let's say, bring in a tailored piece of ai work that has been done by a pro dev team and consume that and vice versa.
00:29:25.230 --> 00:29:39.732
So it's kind of like dare I say it and I hate the word, but we've had it for some time which is this no-cliffs type experience right the way through from Copilot M365, which I don't know if you saw the branding of that has changed as well.
00:29:39.732 --> 00:29:48.325
So your SaaS solution through to your tailored solution with Copilot Studio, through to your advanced developer solutions in Foundry.
00:29:48.325 --> 00:29:52.676
I think it's Microsoft constructing a very robust end-to-end story.
00:29:53.585 --> 00:29:59.631
Can we be clear on the rebranding that you just mentioned so that everyone listening at home can keep up with this?
00:29:59.631 --> 00:30:02.534
What is specifically that rebranding Mark?
00:30:03.484 --> 00:30:15.234
So the co-pilot that we would typically you know bought for 30, is it 30 US a month inside your organization that there is Copilot M365.
00:30:15.234 --> 00:30:15.234
?
00:30:16.164 --> 00:30:20.316
Copilot M365, not Copilot for M365.
00:30:20.517 --> 00:30:20.717
Nope.
00:30:20.717 --> 00:30:27.875
So it has a Copilot logo with the, you know, in beautiful black font M365 branded on it.
00:30:27.875 --> 00:30:37.830
Now, and it basically covers 365 branded on it now and it basically covers five.
00:30:37.830 --> 00:30:40.681
It covers all the stuff that would be included in your m365 subscription from a co-pilot perspective.
00:30:40.701 --> 00:30:55.693
I was just going to say, just as a little aside, I to this day I was just talking to someone about this recently that that the 365 or the 365 branding still is dumb to me, right, because, like, and I remember when it came out, right.
00:30:56.145 --> 00:30:57.308
I love the fact that we have.
00:30:57.348 --> 00:30:57.528
New.
00:30:57.548 --> 00:30:59.513
Zealand 365.
00:30:59.513 --> 00:31:01.258
No it's true, it's true right.
00:31:03.730 --> 00:31:04.335
Hear me out on this.
00:31:04.335 --> 00:31:05.605
Hear me out on this, of course.
00:31:05.605 --> 00:31:09.435
So Mark did not come up with the branding.
00:31:09.435 --> 00:31:15.611
Mark is simply jumped on the bandwagon of the branding, and here's my issue with it.
00:31:15.611 --> 00:31:28.505
Right, I always thought it should have been Microsoft 360 or Dynamics 360, because were people sitting around wondering if Microsoft 365 worked on Sundays?
00:31:28.505 --> 00:31:32.656
Like did we need to be reassured that it worked every day of the year?
00:31:32.656 --> 00:31:42.676
Like it just always felt to me like this was, like the branding was conveying a message that did not need to be conveyed because it was the answer to a question nobody was asking.
00:31:42.676 --> 00:31:50.700
Microsoft Office does not celebrate the Sabbath, nor does it observe the sabbath or celebrate holidays.
00:31:50.700 --> 00:31:51.541
Just to be clear.
00:31:51.541 --> 00:31:58.496
Right, it works every day and you have now been reminded via this apparently permanent branding.
00:31:58.496 --> 00:31:59.278
End of rant.
00:31:59.278 --> 00:31:59.825
I'm sorry.
00:31:59.845 --> 00:32:12.473
Back to you, nz, nz 360 guy nz 365 guy, yeah, um, yeah, no, very good, very good it's um so much trouble after this episode no, I, I don't, I don't.
00:32:12.473 --> 00:32:15.996
It's interesting that you know that it wasn't 360.
00:32:15.996 --> 00:32:22.071
You know, 360 degree view, you know all around there's like lots of metaphors that would play off that.
00:32:22.071 --> 00:32:24.877
But yeah, who knows where it came from.
00:32:24.877 --> 00:32:30.153
I just was surprised when they dropped the office 365 and became out with M365.
00:32:30.153 --> 00:32:34.702
But Microsoft's a master of keep rebranding right, keep changing.
00:32:34.765 --> 00:32:37.713
It's just all year round productivity Mark.
00:32:37.713 --> 00:32:38.395
That's what it means.
00:32:38.395 --> 00:32:40.693
It works every day just like Mark.
00:32:42.345 --> 00:32:43.451
Yeah, not so much.
00:32:43.451 --> 00:32:48.153
Well, that kind of wraps us for this session.
00:32:48.153 --> 00:32:52.423
Indeed, go check out the ignite website.
00:32:52.423 --> 00:32:54.407
You can go and watch my stuff on playback.
00:32:55.269 --> 00:33:12.506
I will throw to will to kind of wrap us up I, uh, I've been so impressed that we try to keep a golden thread going throughout all this with ignite, and we went off on many sort of tangents and, uh, you know, went from from British drinking business culture all the way to other things.
00:33:12.506 --> 00:33:13.709
I think it's just been fantastic.
00:33:13.709 --> 00:33:24.009
So I, for one, I'm looking forward to going off and digesting a bit more of that big book of news and engaging in the comments with anyone that's listening to this podcast.
00:33:24.009 --> 00:33:27.597
So have a great day and speak soon.
00:33:28.701 --> 00:33:30.546
Thanks for tuning into the Ecosystem Show.
00:33:30.546 --> 00:33:36.592
We hope you found today's discussion insightful and thought-provoking, and maybe you had a laugh or two.
00:33:36.592 --> 00:33:42.613
Remember your feedback and challenges help us all grow, so don't hesitate to share your perspective.
00:33:42.613 --> 00:33:48.684
Stay connected with us for more innovative ideas and strategies to enhance your software estate.
00:33:48.684 --> 00:33:52.751
Until next time, keep pushing the boundaries and creating value.
00:33:52.751 --> 00:33:54.329
See you on the next episode.
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سلب مسئولیت: پادکست و آثار هنری تعبیه شده در این صفحه متعلق به Mark Smith [nz365guy] است که متعلق به صاحب آن است و به Listen Notes، Inc وابسته یا تایید نشده است.
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