Crafting a Digital Future with Personal Stories and Advanced AI with Jon Russell and Mike Gowland

They both work at A&S Group as Power Platform Configuration Consulting and Power Platform Consulting and Generally in general . Sorry , john is a regular blogger . He talks about mental health community and his passion for the Power Platform .

Mike has experienced in a variety of programming languages and technologies across low-code environments and has a good working experience with developing automation workflow solutions on the Power Platform . You can find links in the show notes for this episode to their bio , social media etc .

As well as if there's any resources like I know they've got video content etc you can go take a look at . We'll put those in the show notes so that you can get a good understanding of the amazing stuff that they have done this year in the space . With that , jon , mike , welcome to the show .

And then I've got two daughters , Esme , who is seven , and Tilly , who is five , Both quite different characters . Esme is my shadow pretty much , and probably vice versa , although I don't like to admit it , and Tilly is second child and she's completely crackers .

And then COVID here and it was a bit it kind of all died . But yeah , that's my main thing . It's the music as well . I used to DJ a lot a long time ago , played loads of different clubs in London , played in Ibiza , yeah . So music is a big thing for me as well .

You know , I've got my , I've got the same phone and I take a photo and it's like a daylight photo and it's 11 o'clock at night , you know , the moon's out , just the landscape looked just magic . The other thing then , dj . So do you have like your own turntables and what do you set up with there ?

So during lockdown I used to do like kind of like garden sessions , where I'd like have a barbecue in the back garden and also play some music at the same time . But yeah , I think my I was just talking about this with my wife I think my DJ'ing days maybe might be over .

I've been quite about a New Year's Eve thing possibly , which is local , so we'll see what happens , but yeah .

It was quite stressful , but in the grand scheme of things , like it wasn't actually too bad . But in that time before we got married , we ended up having our first child . So I've got . Jack , he's two and a half . He , I think he's determined to injure himself in any way he can at the moment . Yep , he's discovered climbing . He's discovered jumping .

Yeah , he's just , he's a bit of a handful at the moment . But he's great . What do I do for fun ? I mean , I'm just really into tech , you know .

So , like my , my idea of fun is actually like literally sitting down just in my own thoughts playing about with coding new bit of tech , really got into AI , like John just went down that rabbit hole very recently , and that's something I've bought me and John closer together than we already are , cause I think we are basically brothers at this point .

So , yeah , yeah . Fun fact about the wedding venue , mike yeah yeah , yeah , so we we don't live near each other at all , me and John . John probably lives about two hours away from me , but we both got married at the same wedding venue .

What surprised me in the UK is how much rigor there is around the legal part of getting married , like from the venue having a sign on it that says this venue is allowed to be used for a marriage ceremony , and then before the wedding , like I was there for my brother-in-law's wedding and , you know , getting on the hit flask and you know .

But we couldn't get too fucked up because the person that came along like has to make sure that everybody's sober enough to make their vows , that they're not doing it in an intoxicated state , because that's a breach of yeah , I was quite surprised .

I feel like doing like vow renewal or raising up that where it's not like for you registries .

I'd never , ever been to a night wedding before and it's something that my wife and I , where we chose a venue , was on a cliff top looking out over the ocean and we knew that it was going to be a full moon , so as long as no clouds were there and it was , it was just like that no clouds , full moon , reflection right across the water behind us .

It was , yeah , absolutely amazing . But I was surprised . You know that the older generation , once again , didn't think it was illegal because it wasn't done in daylight , where that's every wedding that ever been to their entire life .

Okay , let's talk about what you guys have been up to , and I find the subject so interesting in the area of AI , and that is because , you know , we've just had the birthday of chat GPT .

It's only one year old as of , I think , a week and a half , maybe two weeks ago , and so much has changed and , of course , added to this change is where we all work with . Microsoft technology is .

We've heard so much about co pilots and , of course , if you've been in the Microsoft ecosystem more than five minutes , you know that there's marketing , and then there's reality and there's v one of products and then there's , you know , battle hard and tried and tested three , four year old technology and you know it works .

And what I find interesting is that you guys have come up with some very practical use cases and and built something out and I'll unpack that in a second . And the one of the questions I get so much is I don't know where to start with AI . I don't know . Here's another one .

In fact , this was on a call literally five minutes ago that I was on with somebody else in the UK , which is I'd never pay for it . I don't see the value of it . And you know I bit my tongue because for me I do . I've paid for chat GPT from the day it was purchasable , so when it was $40 us a month , not the 20 it is now .

And you know I challenge myself every day to do a minimum of five prompts . And that is from .

You know , using mid journey , which I'm about to move away from , I'm going to go to stable the fusion's tools in the space , to chat , gpt , its evolution and the changes I've just seen in the past year , and the the ability to pre prompt it like so it knows a whole bunch of stuff about me before I even get into whatever my prompt is .

And I've bought a bunch of other third party tools . You know that that that build out personas , because I'm always looking for you know how can I become more efficient ? And the last thing I was say on this when I was living in London and this is 2018 . And I really dedicated 2018 to , to studying , researching five technologies .

Power Platform was one of them , but AI was one of them back then , right before for all the craze .

And one of the things I really liked about Microsoft is that they always took a view of the world around , what they call practical AI , you know where , where Google is like , oh , we've got the chess master of AI , we've got the you know go and it can beat everything .

And actually I've been in the offices in Paddington of of DeepMind , because my wife used to work for Google back then , so I saw all this kind of abstract AI . And then I saw Microsoft with this kind of you know and you know with their cognitive service type products around this practical application . And then that brings us to today .

So tell us , what are you guys built what ? What is just ask it and what was the how did you get to just ask it ? What was that journey to that point ? And then let's unpack what just ask it is .

I'm kind of more on the HR , payroll side , expenses and voices side , that kind of thing . I kind of understand that process . But the client that came to us , excuse me , asking for that was a water company and this was like Friday . It was like Friday , like half four on a Friday . Yeah .

So he gave this solution architect asked me you know , could you , could you think of a domain specific example for a water utility company to build something in data verse ?

And that's basically the information that I had and I'd kind of been tinkering around a little bit with , with , with AI kind of most of that day , I think , and I kind of thought , well , maybe this could , maybe I could use this to try and come up with an idea that is domain specific .

So that's that's when I kind of thought of the idea of giving it a prompt , telling it that , telling the AI system that it is a power platform consultant specializes in data verse , specializes is in entity relationship diagrams and its purpose would be to take a domain specific example and then come up with a data verse schema including tables , columns , relationships

and potentially an entity relationship diagram . But that kind of came . That kind of came second , and one of the one of the one of the coolest things about it really was and this is when we , me and Mike started talking about it is that I was playing around with getting the .

It was basically a power automate cloud flow that was getting triggered by a certain text inside a team's channel and the . The response came back and it was just one paragraph of you know of text and I thought , oh no , it looks , it looks horrible , like I need to kind of format that .

So I started looking in power automate and I was , I was like right , no , maybe I could like format it as a table and all this kind of stuff . I spoke to Mike and Mike goes just just to add another one and say , just ask it , just ask it , add another rule , put the , put the response in HTML format .

And that was kind of that was quite a a game changing moment for me because I realized actually , yeah , you can just ask it to do stuff . Obviously , there are implications with that , which we'll probably come on to in more detail , especially after a chat I had with someone today .

But yeah , that's kind of where we got to and then it kind of started evolving into a model-driven app . But I think the key to all of this really is that , being a consultant , I have the technical knowledge around date-versus and relationships and entity relationship diagrams , but I don't necessarily have the domain-specific knowledge that the client needs .

So I've already demoed this to our presales guys and I've said maybe you want to call with a I don't know , a beer-meat company Sales with the horseshoes . Yeah , yeah , and you don't know that domain , do you Right ? So , and they might say to you well , tell us what the benefits of using date-versus are . They can use that prompt , they can use .

Just ask it , put that in and a minute later they've got the date-versus schema and they can explain that to the client .

So it's really a kind of I thought it as a kind of starting point and a talking point for that initial conversation to build rapport with the client and build trust with the client , and then you expand on that , et cetera , and then the entity relationship diagram stuff kind of happened more and more on Mike's side .

This is , I mean , this is before Copiant Studio was generally available . I was looking at actually , you know , can I get ? Can I get it to just give me some JSON ?

and tell it what the JSON should be and actually , if I give it some context of what I could ask it , it could define the process and then that process could be converted into a JSON array of these different objects and parameters and then can I actually just iterate through that array in Power Automate and say you know what this is going to trigger ?

A child phone that does this particular action . These are the parameters in the string format . Just split that string up when the flow starts and then take that , ingest that all in , do the action and then rinse and repeat . And I was kind of like I was talking to Chris Huntington about it at the time .

I was like this is basically just a copilot , right , but I'm just probably going about it a long way and we've got Copiant Studio coming out when John was showing me just to ask it , which I can't remember what the name of it was originally we were looking at .

It's like a markup-ish language that allows you to build things like flowcharts , swim lanes , N2 relationship diagrams , that sort of thing . And I was like I wonder if we can just get it to give us that Mermaid schema of that table or all those tables , and map the relationships out that way . So we got it , we just asked it and it did it .

So we just fire off a second prompt once we get the first one , because there's a flag . In the way the flay works , it says if it's going to generate an N2 relationship diagram . Do the second prompt and ask it say this is the schema . Can you convert this into a Mermaidjs diagram or the text for a Mermaidjs diagram ?

We save that into an attribute in the table and then we actually just do some customization on the on the model-driven app form with some JavaScript , so just using the Mermaidjs library , and that you just convert that schema into a SVG graphic and then that's what we display to the end user .

Come and have a look at this entity . You know how it's creating the entity relationship diagram . And even for me , I don't think I've , I don't think I'll wipe city happy , were they .

I was really blown away by that and I was like , you know , because that's the thing , that's the thing about with AI and that's why Copilot is is successful , is because it's it's kind of and I hate to use this term because it's a bit of an enum must term but it's going back to first principles , and first principles are being able to have a conversation with

someone and getting what you need , you need from natural language , and that's that's the power with this . And yeah , like you said earlier on , you know it's only the , it's only the very start of what I think is going to happen .

You know , there's that whole stuff to do with Project Sophia , which was like really under the radar at night , but actually probably one of the more important parts , and all of that . I think we're only really touching the touching the very surface of what is potentially coming .

That could then be you know as you drill through it like a web interface , but then it continued to evolve based on how the discussion was changing to present the information in the most consumable format for the person engaged with it .

And I saw this in the context of you know being aware of Project Sophia and I'm like you know the concept of app automation chatbots , power pages . You know the tooling that we have in the power platform . You know what will they be in five years ? Will every interface be actually dynamically constructed ?

And you imagine an interface that was dynamic construction to present the data in the most optimal format based on whether I had any visual impairment , hearing impairment , tactile , et cetera . But in context of the data I was interrogating , I often see this in even in app design Is a dropdown or a multi-selectless the best way to represent a billion records ?

Probably not right , I would say , when you're trying to filter or whatever , but it's going to be interesting to see how these interfaces literally become liquid in their ability to evolve and engage .

be using the application , their user journey , et cetera . So I started looking into Lucid's API to see whether or not you can create those diagrams automatically , which you can do . So that then got me to think about well , hold on a second . We're already having a conversation with the client , ie from the horse's mouth , other animals are available .

That transcript is being the . We're recording that on Teams . The transcript is being recorded . Plug that into a large language model . Then , with Mike's help , orchestrate that to create the Lucid board .

I mean , I think there are ways and I don't know how far we are away from it , but I think there are ways to go literally from a conversation to proof of concept with a large language model . I think that's possible . I think that is possible .

But what you're describing here , it's a phenomenal game changer .

Because if I look across my career and I remember I went to Hong Kong some years ago and I had to pitch to the I think was the seventh largest shipping company in the world a concept to manage all their ships around the world , all their ports of call , all the scheduling , that type of thing and guess what I knew about shipping ?

I know ships go on water cargo , maybe I knew nothing , and so what did I do Back then ? I jumped on Google , I search and go OK , and I literally got on a whiteboard and said shipping company and I did really a mind map of all the kind of things . They obviously have ports where the plays are part of what they do .

They have shipping containers , they have different ships which have different sizing , they have crew , and I just went and that's how I would mind map out , right , a concept .

I chuck it into Vizio back then and that would be the start of my ERD , right , and then I would take any one of those nodes and I would build out everything I could Now go pitch to the customer .

I'm not even showing an interface designer or anything , I'm just showing this is how I understand it and they're straight away like wow , and you can do this on your software . And this was , of course , dynamics back in those days . Fast forward , hong Kong Jockey Club deal with thoroughbred racing , horses , right , and gambling and breeding .

And the same deal , right , I take a horse at the center , they're going to have vet , they're going to have health , they're going to have jockeys at the center . I would do these diagrams out and stuff and the customer would go wow , you totally understand us . I knew nothing about resources a day before , type thing .

Then you tell me about this tool and I'm just like going , oh my gosh , this is a game changer because it allows you to go out , I assume , does it allow you to go down to . You talk about a domain level like water utilities , but it could it go even more specific to the exact water utility and interrogate their web asset .

Maybe their directors reports , maybe any filings that they've had to do from a compliance . Could it feed that into the mix around ? You're saying having those conversations with pre-sales and things .

Now all I did was I handed their website to AI and I said tell me the top five issues that this organization is facing . And of course , it basically read that Royal Commission report and it came out and it said they have been told to have to address this , this and this .

And so when I jump on the call , I don't say I've done any of that right , I'm just like so what are you doing in this area and what are you doing in that area ? Like I'm asking these questions which I know a lot of the answers to , but of course they go oh my gosh , you've really thought about us , you've really understood where we're doing .

And then I ultimately had my team model that into a solution around stakeholder relationship management . And they're like wow , this is exactly what we're looking for . And I'm like , yeah , it didn't exist a week ago .

I think the issue is that the main thing is and like you said earlier on , mark , about you know , having this solution on GitHub actually the hard work is about the grounding of the large language model and coming up with a consensus that this is how we ground all models when we are using it for a certain application , whether that's consulting or whether that's

in childcare or whether that's in , you know , a doctor's surgery or anything like that . That's that's . That is that's the difficult part and that's where a conversation I had today we were talking about , we were talking about diversity and equality and inclusion , and you know you have the . The large language model doesn't know that .

So you have to kind of baseline it and ground it with these prompts where you're telling it what diversity is , you're telling it what you know race , ethnicity , you know people who have different kind of impairments , et cetera . You know all of that needs to be factored in and I think that is where that is where the work needs to be done .

With I , I think that we will get to the point where things like inclusion and diversity is , ai will define it based on everything it's consumed around these scenarios and it would potentially write a better model a more bias removed , et cetera than what any human , because it'll understand what bias looks like , because it'll understand what racism looks like looks

like and therefore it will , if you like , create a self healing process around that to make sure it doesn't creep in . You know , like you know , you've seen this , the sample around where CVs are read and they're like how come we only employ males in the organization ?

Because historically , all the CV daddy have given it I've been male centric CVs and it would go hang on a second . I understand how the bias is creptin . Now I'm going to put counter measures in place against such bias .

Just make it , aren't we , john , where we actually can have feedback on prompts and actually give feedback and I can help a prompt engineer to then reiterate what that prompt actually does .

So you're so right a prompt that might have worked six weeks ago , If the models have been updated , might not be as relevant or or accurate today .

But if you ask , like how to make it normally , you might actually get a few different recipes if you ask it over and over again . So actually , prompt engineer isn't just about when the model updates , it's also , you know , as the model is in its current state you might need to review that prompt over and over again .

We have the mental health first aid is group , which I lead various different groups , and today Mike showed us on a demo like a kind of prompts catalog , and we were talking about that and realized that Mike had kind of split that out by department , so maybe you might have slightly different rules set for People in the IT department , people in HR and actually ,

yes , actually it's , it's , it's bigger than that . Yeah , it's not really department based , it's domain specific based .

And so what we've been thinking is and I said this today on our we had a , we had a EDI meeting this afternoon with like the lead on the lead in our people team , and I was talking about this and I said , actually what we need to do is we need to involve all of these groups To provide the grounding rules to the large language model .

So , yeah , that , that , that is that I could . I . That's the . There's a big shift , I think , now from people who might not think they are necessarily tech savvy . We don't actually need those people that are tech savvy because we've kind of what that bit out .

We now need the domain , specific expertise that me and Mike might not have or other people might not have , that are tech based . We would like to speak to someone who knows more about dyslexia , for example . You know what ? What rules , what rules do you want to put in the , put into the model , to ground it ?

Which which would improve the response for someone who is dyslexic ? That , that , that kind of thing . That's that's kind of where we are with that , and I think that's gonna be . That's gonna be very powerful . I Also think . I also think there is some not so much at the moment , but you know we know how technology goes .

We know is that you know more's law of . You know Mm-hmm capacitors and transistors getting smaller and smaller and smaller , which means a Smaller chip with more more data to more data inside it , or more data it can handle . And I think excuse me I think there will come a point where we will be able to build our own large language model .

Now , I don't think that's very , I don't think that's close , I don't think that's near , because of the cost of it and there's lots of other , there's lots of other considerations , but I think that is gonna be where the gold is . You know you you could have a consultancy . Speaking to a client wants to use AI .

They're a little bit protective about their data . Fair enough , pii data , whatever . Okay , yeah , let's , let's help you spin up your own large language model , trained on your proprietary data and Yep , secured inside the Microsoft ecosystem within your region . That's , that's , that's gold level , I think , and it's I don't think .

I don't think it's close because of you know the , the GPU issues that you're gonna have with . You know You've only got like arm and Nvidia maybe that are producing those and Kind of sustainability aspects about .

You know how much it actually costs to run An AI dense , an AI data center , for example , but I think in a couple of years time , maybe that's that's where it's gonna go . I think that's where it's gonna go .

Well , in other words , the latest version of an LLM will be able to commit dense to under two gigs in size and Everybody will have a personal LLM on their device that you then control all your private data against .

And he saw some kind of concept of you would have kind of like an API into that , but you would control anybody as in what you would give out of your personal LLM on your device . Therefore , the whole advertisers etc . Wouldn't be able to get that .

That's why I think my guess is Apple is working on something that's going to , because they've been very quiet about AI , right .

I've got gigs of stuff , photos and my electronic footprint waiting for this day . Now I am going to be able to go have it all but not owned by anybody out in the public arena that's going to make money off that and go .

Let's talk and let's understand Mark as a digital version of me that understands that 15 years ago I went to a doctor and I had this medical treatment and now I've got a medical file that's my medical file of stuff that I've totally forgotten about . What was my last eye check at when I went to get my x-rays from the dentist ? That's fitted in there .

And now I've got this model of me and stuff around me that I've collected over my life and it operates on a LLM . That's my personal LLM . So I think you're right . I think that that is going to be I don't know if it's going to be two years away . I think it might be less .

Honest , not harmful , and I can't remember what the other one is . It's harmless .

And you just stuff like that just really annoys me , because you've got like people who , people who are quite skeptical about AI .

And then I'm like , ok , so that's an unresearched knee jerk flick , because of course , that TechCrunch article the the whole quite clearly that it's a concept . It wasn't , but it was not pitched as a concept .

Guys , this is one of the longer podcasts I have done , having the two of you on or at 45 plus minutes in any resources that people can look at . Go see in any final words that you want to want to add before we close out .

It's a good if you've not got into it yet . It's a way to just go step by step understand how to write a prompt , what you need to include in it , how to actually interface that with Power Platform , specifically Canvas apps in this case . But it's a connector that also works over Power Automate .

It's just like a little starter really to get into it and understand what the parameters do . It's generally maybe a good starting point . We've also got our video API solution where you can actually see just ask it in action and GitHub coming soon . And GitHub coming soon Awesome .