Dynamics Corner
About Dynamics Corner Podcast "Unraveling the World of Microsoft Dynamics 365 and Beyond" Welcome to the Dynamics Corner Podcast, where we explore the fascinating world of Microsoft Dynamics 365 Business Central and related technologies. Co-hosted by industry veterans Kris Ruyeras and Brad Prendergast, this engaging podcast keeps you updated on the latest trends, innovations, and best practices in the Microsoft Dynamics 365 ecosystem. We dive deep into various topics in each episode, including Microsoft Dynamics 365 Business Central, Power Platform, Azure, and more. Our conversations aim to provide valuable insights, practical tips, and expert advice to help users of businesses of all sizes unlock their full potential through the power of technology. The podcast features in-depth discussions, interviews with thought leaders, real-world case studies, and helpful tips and tricks, providing a unique blend of perspectives and experiences. Join us on this exciting journey as we uncover the secrets to digital transformation, operational efficiency, and seamless system integration with Microsoft Dynamics 365 and beyond. Whether you're a business owner, IT professional, consultant, or just curious about the Microsoft Dynamics 365 world, the Dynamics Corner Podcast is the perfect platform to stay informed and inspired.
Dynamics Corner
Episode 404: AI Agents and Their Impact on ERP Software and Business
🎙️ In this episode of Dynamics Corner, Kris and Brad converse with recent 🎉 Microsoft MVP Sai Turlapati 🎉. Listen in as Sai shares insights on the evolution of AI, particularly in the enterprise sector, emphasizing Microsoft's significant role in AI adoption. He discusses the importance of prompting in AI interactions and the emerging concept of agents that can automate tasks.
🎧 Listen to hear more of the conversation about:
➡️ How prompting is crucial for effective AI interaction
➡️ The practical applications of AI agents in scheduling transformative impact of AI on time management, enterprise applications, and business workflows
➡️ How AI copilots can enhance productivity and efficiency in various industries
➡️ The importance of adapting to new technologies and the potential challenges businesses face in integrating AI solutions.
#MSDyn365BC #BusinessCentral #BC #DynamicsCorner
Follow Kris and Brad for more content:
https://matalino.io/bio
https://bprendergast.bio.link/
Welcome everyone to another episode of Dynamics Corner. Copilot, jack of all trades, master of none, but oftentimes better than a master of one. I'm your co-host, Chris.
Speaker 2:And this is Brad. This episode was recorded on January 29th 2025. Chris, Chris, Chris, that was a good little jingle. Did you use Copilot to write that, Chris?
Speaker 1:Chris.
Speaker 2:Chris, that was a good little jingle. Did you use Copilot to write that which part?
Speaker 1:No, I did not, I did not use Copilot for that, but you did say a comment. You used that term, jack of all trades, master of none. And then I realized there's actually a full quote and this was very fitting. When you said that, I was like, ah, very fitting, I like that. I was like, ah, very fitting, I like that.
Speaker 2:And that was fitting, because today we had the opportunity to dive deeper into this world of AI, which everyone seems to be talking about, and there's a lot of information to unravel, and there will be a lot of information to unravel in the future as well, too. With us today, we had the opportunity to speak with Sai Charlapati about Copilot, ai and many other things hey good morning, good morning. Hey, good morning.
Speaker 1:How are you?
Speaker 3:doing. Hey, good morning Chris, Good morning Greg, how are you guys?
Speaker 2:Very good, very well, very well, thank you. Thank you for taking the time to speak with us. Been looking forward to speaking with you.
Speaker 3:Yeah, thanks for inviting me. I heard a lot of episodes. I'm really interested to talk to you guys and learn so much from your podcast, I think today.
Speaker 2:We're interested in speaking with you and learning a lot from you, or hearing a lot from you about some popular topics that I see a lot of information on and you also share a lot of information about, which is exciting.
Speaker 2:I'm getting old, so it's all difficult for me and it's very difficult for me to keep up with everything that's going on. It seems that everything's accelerating quickly and I just can't keep up, but that's why we get to talk with people such as yourself to hopefully share some insights, to help us get a handle and a better understanding on some of the technology that is available to us. Before we get into the topic, would you mind telling everybody a little bit about yourself?
Speaker 3:Yeah, sure, my name is Sai Thirulapati. I am in the IT industry for the past almost 20 years. I saw the Y2K. During the time I was very young, fresh out of college, trying fresh out of the college, trying to understand that mainframe transition and other things. Then I saw mobile revolution, then cloud revolution. So there are these waves of technology revolutions that we saw and I was able to ride those waves and recently, for the past few years, I was very interested in the AI space.
Speaker 3:So I looked at the different. Who are the players in the AI space, especially enterprise AI. The enterprise AI. Microsoft, claudie, who is the Anthropic, is the company that creates this quality, like open AI is having charge upt. These are the players, especially in the b2c space. That's how I see it. In the b2b space, microsoft, amazon, oracle and, you know, google are the players, but predominantly I see Google with Gemini and Microsoft with their own Azure framework. They started with Azure with the backend, trying to talk to any LLMs, but finally they decided to just create a wrapper around it and explore the you know the LLMs that are being developed by other players.
Speaker 3:So that's how I got interested in this space and I feel like the first wave of the impact of AI is going to be in the enterprise side, at least on the customer service and sales. That's how I see it, because that's where there is a quick value that enterprises can see. So in that space I evaluated who are the top players in the CRM and customer service. Salesforce is one of the top players and Microsoft is another one. Hubspot is there, sage CRM is there. Those are very good players.
Speaker 3:So in that I looked at who can really help the enterprises who are having the end to end story. When I looked at it, microsoft is having the teams right Microsoft teams and Salesforce is having them. Slack that's the company that they bought, so those two are going to be really competing in that space for the AI to get the enterprise adoption. And one thing that Salesforce is not having especially lacking is the cloud story, whereas Microsoft is having the good cloud story. I looked at the Google. Google is, gcp is having cloud stories, so as Amazon, but they don't have the enterprise software such as Dynamics 365, erps or CRM, customer service and all those things. Then I felt like, okay, I am in my 40s, I feel like I need to bet on one of the real vendors who are going to take me to next 10 to 20 years. I looked at Microsoft.
Speaker 3:I feel like okay.
Speaker 1:Microsoft is having. You took your bet on Microsoft versus Google.
Speaker 3:Yes, because Google is not having Chris. Google is not having any ERP or CRM. They tried to buy the HubSpot but they withdrew that bid recently. To buy the HubSpot, but they withdrew that bid recently. So for any cloud vendors, for that fact, for any enterprise companies, to build this CRM and ERP systems, it's long, you know, it takes a long time. And also, the important thing is the user base. Right, they can build the efficient software solutions, but I feel like attracting the users is a difficult thing, so you're going with Microsoft for the.
Speaker 2:B2B enterprise company to have a larger adoption within the B2B space because of the exposure to businesses with the existing applications that they can build upon utilizing.
Speaker 1:AI. Well, you covered a lot. See, it's already a lot on there. We're just getting into it, man, I know.
Speaker 2:We're scratching the surface. We got into it. I'm still back at see, my mind is still processing. I'm still back at Y2K, which I remember when that was the end, and I almost wonder, you know, maybe would we have been better off if it didn't then or not? Uh, but you, you had mentioned microsoft.
Speaker 2:With ai I mean microsoft, ai one. To me, artificial intelligence is a very generic term because ai encompasses a wide spectrum of topics. You know, we hear the lg's. I can't even cover all of the points for it because, you know, a lot of times people just think of the llms. You mentioned chat, gpt and recently we've seen some in the news some other local large language models allow processing locally, so it's there. So, with with microsoft and ai and the adoption, or where you see the adoption to B2B to adopt, utilize and gain benefit from the use of AI in the organizations or increase some efficiencies, how do you see and position the Microsoft tools to be able to use these AI features and what are some benefits that you see an organization can get from using AI?
Speaker 3:Yeah, sure, especially, that's a very interesting question In the B2B space especially, microsoft is having very good footprint, especially with the Microsoft 365 Office 365 suits and the way I see is especially the users. When chart GPT came, that is a aha moment in the artificial intelligence revolution, right? They? Everybody thought that it is going to take some time, but the user interface for chart GPT is a prompt.
Speaker 3:I looked at the landscape in the enterprise computing. Who are having that prompt readily available? I see there are broadly three players. One is Microsoft Teams and another one is Slack, which Salesforce own, and third one is Zoom right Zoom calls.
Speaker 3:People are used to this video Now they started. You know the charting also. One is zoom right zoom calls. People are used to this video now they are. They started. You know the charting also. So those are the three predominant players for humans to have that kind of interaction from B to C space where chart GPT and Tropic, google, gemini and other players are there to convert that B to C space, that chart prompt experience, into the enterprise experience of the business users. I feel like these three predominant companies like Microsoft with Teams, salesforce with Slack and Zoom, are the three players that are going to be really taking this enterprise AI to the next level. Those are the three players that are going to be really taking this AI enterprise AI to the next level. Those are the user interfaces, because people already have the experience of using prompting the chart.
Speaker 2:I hear the word prompting with an AI and I hear individuals talk about how to become a prompt engineer or prompting tips and tricks for prompting. What is prompting and how does someone come about with the prompting? And we're talking with large language models and prompting how can those be utilized within the B2B space? How does someone understand what prompting is and maybe how to construct a prompt to get the results that they're looking for accurately? But I also want to hopefully get into also this new thing that I'm hearing about, which is agents, to where maybe it expands to a little bit more than just prompting or typing for information getting information back, where you have an agent that can possibly do something. So it will take some tasks that are possibly repetitive or tasks that can be automated in a sense to allow for someone to have more time and opportunity to do other tasks. So how does that all fit within the B2B space? How does the prompting work? What can you do with the prompting and also then with these agents that are being created?
Speaker 2:I know within Business Central we see a lot of news about Microsoft adding agents and agent previews that are available and talking about that. It's not even within Business Central. I see the word agent everywhere. I think it's going to be. I think the word of 2025, if we could talk about it would be agentification or agentizing Agentic.
Speaker 1:I hear that too Agentic.
Speaker 3:Yes, yeah, that's a very good question and very reflective on the introspective question. What is prompt? Prompt is nothing, but, at least in my words, prompt is nothing but asking a question. How do you ask a question is a prompt. How do you ask a question to a computer? In this case, the AI bot is a prompt. The way you ask a question and the way you respond to a question is also a very interesting leadership insight. I read a book, or I listened to a book called how Great Leaders Ask Questions.
Speaker 3:So the way we structure the question and what is the strategies that we can use in order to structure your question enables the person to gather more information. So this prompt is nothing but the way you ask a question to the bot or AI agent, right, ai on the other side, and the AI computer or AI bot or AI chart, we call it in the Microsoft setup, we call copilot, right, ui. So the way we structure the prompt involves different strategies. Right, first, we can give the context. We say that, hey, what is the news today Is a prompt. We can ask that as a prompt. Or what is the news today in the United States in the financial sector Is more specific. So we are able to structure it and ask a question to get a, you know, intended answer for us. So prompt depends on how fine-grained means how specific we are. The answer is going to be that much, you know, clear from the ai agents or ai bots. So you touch a lot of topics, br. Brad. So I agree with you this 2025 is going to be the age of agents. You know, when we talk about agents, I remember the movie that I watched in 1998, matrix, right, I'm sure everyone remembers about that movie. You know the agents. So the difference between the way I look at it is the difference between agent is an autonomous thing. That's what Salesforce is also calling them. And Salesforce came up with the agent force as one of their solutions and they are going full-fledged.
Speaker 3:How Microsoft came with Copilot, satya Nadella, who is the CEO of Microsoft, very clearly articulated that Copilot is the user interface that humans are going to interact with the LLMs or the AI machines, right, and the backend is going to be the agents who are going to do the work. If we try to do that in the, you know, correlate that space into the Power Platform, I feel like agents are nothing but Power. Automate, right, they are nothing but a Power Automate workflows right. Co-pilot, when the user interface, when user prompts or ask a question. That goes to the agents, microsoft. Interestingly, in one of their documentation they referred agents in three ways One is a responsive agent, another one is a task-based agent and third one is autonomous agent. So I feel like, chris, you are know when we talk about agent, which can go and do a task and come back, it is like a power automate flow, right? People who are aware of this Microsoft power platform knows what power automate is, which is nothing but a RPA space. Uipath is another company that you know they do in the RPA space that they provide the solutions. So for our context, agent is nothing but a you know, a software program in the back end that goes and completes a task without giving the information.
Speaker 3:Then what is the difference between? Now comes the question what is the difference between power automate and the agent? Right? Power automate we use to go in the power automate. If I want to create a flow, I need to go and drag and drag and drop all the required components. What is the trigger, what it needs to do?
Speaker 3:The power automate means send it a email.
Speaker 3:Let us take a simple use case, right, if we want to read an email based on the incoming email, I just want to create an Excel sheet or Word document and send that information back to a team. If I take that use case in order, for If I take that use case, in order for us to do that use case right now in the Power Automate, I need to go and create a trigger, say that, hey, incoming email is the trigger to this email box. Once we get that email, then do this processing, read the email and create that Excel or Word and send that information to the teams. I need to go and create that Excel or Word and send that information to the teams that I need to go and do that. But Microsoft, now recently they created a copilot for Power Automate. Now I can go to the copilot and say that, hey, create this workflow. So this workflow of reading the, you know, anticipating for the email and reading the email and creating a Word document or Excel and sending it to them. So, stepping back really quick Sai.
Speaker 1:You mentioned Copilot, basically more of a. The way I look at it sounds like to me Copilot is more of a translator. You ask a prompt of what you want based on what's available for you within your maybe tenant, then it chooses the correct agent to respond. So it's almost like a translator. Right for that prompt Because, as you know, in the B2B space, when you're creating or you're interacting with Copilot within your organization, it should only respond based upon what's available to it.
Speaker 3:Right.
Speaker 3:So you are right, chris. So the Copilot is like you said. It's basically an interface. It does some operation, it manages the agents. You can say that it's an orchestration piece where it takes the information from the user and, based on the available agents, it will direct the agents, orchestrate the agents to go sequence of tasks and come back and provide the answer to the user, to the human or to the user in the NLP, natural language processing. So now the way we interact with the co-pilots or AI agents is completely changed. From the mouse, we take that and click that different buttons to get the information. Now we are using natural language processing to talk to, like how we are able to talk to other human, like how we are discussing, we are able to just enter the information to the co-pilot.
Speaker 3:Microsoft is having their own lab called co-pilot. You know Microsoft Labs. They are experimenting with voice also. So, like how we are discussing, they have a co-pilot voice, the co-pilot voice. We can just enable the voice and we can say that, hey, this is the task that we want to do. Then you know, it can go ahead and create the agents and orchestrate the agents and come back and with the answer.
Speaker 3:So in one of the recent interviews also, I think, satya Nadella, ceo of Microsoft, he told that SaaS kind of you know, in the future SaaS may be. What is SaaS applications? Saas is software as a service applications. Right, they are basically a CRUD. Applications means they are having a database On the top of the database. The user interface provides the user to interact to perform the CRUD operations.
Speaker 3:If we take CRM right, crm is having a sales module in that there are certain database tables which are in the Power Platform called Dataverse. Sales module provides the user interface for the users to go ahead and create codes, purchase orders, leads and opportunities, all those things. In the future, what is going to happen is people are expecting that may be sooner, maybe within the next few years. Instead of user going to the sales application and entering the information, people will go to the prompt copilot, sales copilot and they say that, hey, this is a new lead that I got, this is the you know. Take the picture. Say that, hey, create a lead information in the sales of Dynamics 365. It should be able to create that information. So the user experience itself may be, you know, completely changing the way users interact with these enterprise applications. Maybe really changing.
Speaker 2:That could take me down a completely separate path because Chris and I recently spoke about that as well as far as how we interact with data, how we retrieve data and having the ability to use natural language to interface with that. But I'm still trying to go way back to the beginning of prompting to get information out. How do we come up with a and how do we learn and how do we know to come up with the proper prompt either for to go back to the points that you had mentioned, either it's data retrieval or language and learning I type, you know, create me a picture or ask some information based upon the data that the model has been trained on or in the construct of what you and Chris had mentioned, with the Power Platform to utilize Copilot Studio in a sense, which I want to get into to create these tools for us, basically our own agents. But where I get confused is we mentioned task-based agents how is their variability in tasks? Because I still say, something that I tried to do, I wish I could do, is even something as simple as scheduling, taking my emails, taking a look at my calendars to be able to automatically reply, like even with the podcast, for example, we do a lot of scheduling of the guests, such as yourself with the podcast, with the.
Speaker 2:We do a lot of scheduling of the guests, such as yourself with the podcast, with the pre-podcast planning calls. Chris, you have to fix that Pre-podcast planning calls to the actual schedule of the recording taking a look at calendars, taking a look at time zones to offer and suggest times that best fit based upon availability time zone and such times that best fit based upon availability, time zone and such. There's a lot to that, and is that something that could be done and how could you do that? Is that multiple agents within Power Automate? No-transcript.
Speaker 1:Right, so now you give a it's all within that space.
Speaker 2:So, utilizing that, how could I do that? I hear a lot about Copilot and I hear a lot of things that we have agents that can do anything. I'm just trying to see a practical use and example of it.
Speaker 3:Yeah sure, so let's take that use case that you mentioned about the podcast right For us to create this Microsoft AI agents or Microsoft co-pilots broadly. There are two ways that we can do it right now in the Microsoft platform. One is using the. Microsoft came up with a co-pilot studio that is part of the Power Platform that provides the tools and knowledge bases and inbuilt agents also that enable the user. That's a low-code, no-code platform Copilot Studio, where the users can go ahead and create the AI agents. And another way to do that in the Microsoft platform is Azure AI Foundry. Microsoft just recently launched Azure AI Foundry. Microsoft just recently launched Azure AI Foundry, which is based on them. We can go ahead. We can use the Azure AI Foundry and create the agents using different LLMs that are available, such as we can use OpenAI Microsoft is having 49% stake in the OpenAI, so they create exclusive access to the OpenAI models or we can use Anthropic models, or we can use LAMA, which is Meta's open source AI models. So broadly, we can do it in two ways. One is Copilot Studio Microsoft Copilot Studio or Microsoft Azure AI Foundry. For our conversation.
Speaker 3:I have good experience in. You know, I created a couple of agents in the using Copilot Studio so we can do the use case that you mentioned using the Copilot Studio. Copilot Studio is a very easy way for us to create the agents. Previously Microsoft used to call as co-pilots. They renamed it a few months back to agents. So to create any agent we need broadly two or three things. First one is what is a knowledge base right, based on what the agent need to create the information. Second one is tasks. These tasks are nothing but the tasks that just you outlined to create this podcast. We need to look at, you know first, evaluate this. You know participants, send them an email and have the review session so we can create. We need to break down into different tasks and that task.
Speaker 3:Microsoft is very good, especially in the Coopilot Studio. They came up with a lot of connectors. We can connect with the Outlook, which is a native thing, so we can easily connect to the Microsoft Outlook and create a task and send an email If we want to talk to any other databases or like Riverside if we are trying to use, task and send an email If we want to talk to any other databases or like Riverside, if we are trying to use. We will go ahead and see whether the Co-Pilot Studio is having any Riverside connectors. If not, users can create that custom connectors. So Microsoft enabled all these features for the low code. No code developers to create this kind of connectors to create the agent. So the agent can be created. First, this podcasting use case we can break down into tasks and each task we can go ahead and create. It is similar to creating a workflow in the Power Automate. You're muted, by the way, brad. You are muted.
Speaker 2:Brad, don't tell anybody, because I was getting excited and I had to mute myself because I wanted to hold back. So I can create an agent that will send an email to Sai. Sai, we'd like to speak to you on the podcast, are you okay? I'm simplifying. It may be one use case In the other cases where individuals contact us and say they would like to speak with us about a topic which we enjoy getting those emails as well. So I can say email Sai, ask him to be on the podcast. You'll reply yes. So the agent can reply to that email, knowing that the original email was sent out as a request to the podcast. Response is whatever verbiage is yes, and then the agent can respond and say okay, let's do this, let's set up a planning call. Is this time good for you? Or here's these times that are good for you? Based on rules or based on Based?
Speaker 1:on our calendars. If we we could do this, this would be amazing.
Speaker 2:So I can send out the email. The response would come back. It would automatically send dates based upon a calendar for availability. The participant would be able to then respond with this works best for me and then it would automatically schedule and put in the text that I like to use. And all that and the link, yeah, because the studio link is yeah, that's, that's correct, right.
Speaker 3:Yeah, that's correct, chris. So what you know, now we are getting into very we need to do this afterwards.
Speaker 2:If we can really do this, I would like to schedule time. You can certainly set it up is this something you can do and then send to me? Yes, I think we can try that. We'll do a follow-up because I want to see this in action, because that is such a good experience and good use of the tools, as well as saving time yeah, not only that, you that you know you will have, you know this Chris and Brad will have their own agents right To send the email to schedule this.
Speaker 3:I will have my own agent. So as soon as I, that is who could do my email right. So as soon as I see any request or any information if I want, my agent will respond to your agent. I can create a small agent, say that, hey, if I am going for this podcast or speaking once I get an email, I create a small agent and say that, hey, just respond back with my email ID, with my calendar availability next couple of weeks to your agent. So this is going to be really agent orchestration.
Speaker 3:Right At your end you will have a couple of agents which will be triggering the email or receiving the email. I can just next time I will send an email say that, hey, I'm interested in your podcast. Or I will just ask co-pilot say that, hey, next couple of weeks I am interested to. I have this time I want to really talk and get to know more about what is happening in the dynamics with Brad and Chris. So I will just ask the co-pilot and the co-pilot goes and talks to my agent and send an email to you guys and your agent can pick it up and look at your availability and schedule and confirm something back to my agent.
Speaker 1:There's actually two places where I can see this working Right now. Our website has a place for you to be a guest, right, you fill out your information and stuff and we get an email. So we could use a Power Automate to collect that information and, based on that information, then we can use Copilot to act upon that. Where it looks at our calendars, make sure that it answered you know we got all the information it needs and then it can, you know, schedule that for us. And number two we can even put copilot on our website, probably, and sai can interact with it. It's going to ask all the questions that the form would have asked anyway, collect that information based on size responses, notifies us and looks at our calendars and let us know like hey, si's interested in this and then schedule it out and we just show up and have a conversation.
Speaker 2:I I like the use case because it's to go back to where I started with. This is. We hear all this ai agent, we hear prompting, we hear models, we hear all this, but I hear it. Well, you can do anything or you can do specific tasks. Now I'm trying to just put my head around something as simple as scheduling with somebody to be on a podcast. Somebody could do this on their own.
Speaker 2:For something else, even lawn maintenance, if somebody has a landscaping or a lawn maintenance company or even electrical services, you know any type of scheduling that you need to go through. We usually have an individual going back and forth. I know often I'll use what they used to call fine time or whatever. That is where you can say, okay, here's several dates and times, pick the ones that work the best and then from that. But that's, to me, is not such an elegant experience sometimes. So I would like the more personal interaction of I'm sending an email to Cy. Step one, chris. I like the idea of also taking ingesting on the inside. Then all of a sudden stuff shows up on the calendar and then we just just do it. I think that's also great.
Speaker 1:I think you can even prompt it where like, do not schedule anything just within the space because maybe you're already busy, and then look at, you know if there's already existing one and you can specify it's the only schedule between these days or between these times.
Speaker 2:Oh, we have to do this. Okay, so we can set it up to where we have an agent in Power Automate that will send an email. It will send an email based on me just saying send an email to Sai to be on the podcast, right, yeah.
Speaker 1:Just like that.
Speaker 2:We can easily do that, yes, and then we'll send an email to Sai with a template with the information that's pertinent to Sai so that he understands what the podcast is. Then you'll reply. The agent will read the reply and we can say go look at this calendar and this calendar and propose some times based on size, time zone. I like this. That is important. I'm trying to think of the variability here because these are the scheduling challenges. We recorded all hours of the day to make accommodations are the scheduling challenges. You know we recorded all hours of the day to make accommodations for everyone's schedule. That that's going to so how much how much time you spend, brad.
Speaker 3:I think uh looks like it's a lot of efforts for you. You know, to host this kind of podcast right. Look at the look at the just calendar.
Speaker 2:Simple task of calendar it's looking at calendars, going back, making sure that it's a lot of appropriate for the guests because, as we say, it's it's anybody who's been on.
Speaker 2:We, you know, in the planning call, we talk about that when they're at their best, when it fits them. We try to work around trips if somebody has conferences to go to, for example, or if there are holidays and and sometimes individuals don't mind, you know we'll do a recording on a holiday or something. So there are some variables in there that, based upon, we may need to find out which times work best for you, but it is a lot to juggle schedules for many calendars.
Speaker 3:So how do, how do you guys do? Do you guys outsource that piece of?
Speaker 2:work we do.
Speaker 3:outsource it to me piece of work to me.
Speaker 1:Yeah, man it's a lot of work, right then a lot of energy, guys.
Speaker 2:The scheduling is a lot of work. The scheduling is uh, I'd want to say it's a full-time job, but to try to do proper scheduling and I like to do things properly as well as you see, when you go through the experience, to make sure that everybody has an enjoyable experience as they go through this with a little bit of a personal touch as well. But, it does say take some time because we have several calls per week that we do on top of everything else.
Speaker 1:You know, it'd be fascinating though, because once we get all this solved right, it's to have a system, or maybe co-pilot or an agent, where he takes all of our files and says I want you to edit this for our podcast video and it just does it for us.
Speaker 2:Right now it's all manual man, we do it man we do it well, chris, does the the post production you know we have a process and it works well. Because of timing, I'll do a lot of the scheduling, interfacing with the guests that come on that we are extremely appreciative of everybody that spends the time with us. Time is extremely valuable. I know to me personally and Chris and I talk about it because it's what we have. Once you use it, you don't get it back. You don't get a redo of a minute.
Speaker 3:You are a wise man, Brad. People realize that very late. I am realizing now. I think time is the real.
Speaker 2:It is. It takes you. You do have to get to a certain point in life, I think, where just maturation in life, that this is something I wish. Everyone always asks me what would you tell your younger self? That's one of the things I would tell myself is one listen to those that have gone through a lot because their experiences. I'm not saying you have to listen to the experience as far as following, but sometimes just listening objectively to somebody's experiences and maybe learn from them instead of thinking, ah, they don't understand, I can do this, I can do that.
Speaker 2:And also time, you know where you spend your time and what you spend your time on. You cannot value anything more than that. But to go back to what we talked about, so I do a lot of the scheduling, chris does the post-production. Hopefully at some point we can incorporate some ai into it, um, which thankfully riverside has added quite a bit that we can do some stuff. But uh, chris, I don't want to jump the gun yet. I'm still trying to go back to the scheduling to save myself some time and we'll set this up and I won't even tell Chris and I'm like I have to go through all this scheduling.
Speaker 1:I think, like you said, you put it well perfectly about the time spent, where I think co-pilot AI in general is really, really important for the future, because at that point, as we use it more, we don't trade time for money. We get to a point where I want to trade time for experiences, right, and and that's going to be, um, that's going to be important in the future for it, for my, for my view, because, as like you said, sai, you know, you want to make sure you're you're utilizing your time in the right places and not trading it for money every single time.
Speaker 3:Life is short.
Speaker 2:It really is. It's um. You know, you go through phases.
Speaker 1:I thought we were now getting philosophical and I don't mean to digress, maybe I'll just stop.
Speaker 2:I could get on the philosophical road forever but um time. So we'll go back to the efficiency of time. So we can set up an agent to send an email. We can set up an agent to read an email and then, based on the contents of the email, work on scheduling the podcast. I have to see this work.
Speaker 3:Yeah, that's a good use case, at least in 2025. Maybe next, 2026, 2027, we just need to talk to that. You know co-pilot or the UI, the prompt say that, hey, this is what we want to do. It has to. It may be going and doing all this. You know scheduling and creating all this for us. Maybe right now we need to enter the prompt on the keyboard In the future. You know there are NVIDIA. All these companies are investing heavily on voice-based, so we just talk to them. Hey, do you guys? I have a question Do you guys recently OpenAI released Operator? Did you guys look at that Operator?
Speaker 2:demo. I watched the demo of again you need to have from what I read, you need to have OpenAI Plus or whatever that means, Right, $200. The expensive plan, which I understand, but that was impressive as well. It would go to a website and interact with the website. I saw it do the scheduling, I saw it do reservations and a number of other things. That is impressive. That's interesting.
Speaker 3:That is impressive. Yeah, interesting, that is impressive. Yeah, I have a question for both of you. Given you guys have so much of experience in the IT side, right? So, technology-wise, in the leadership roles and all those, how do you see this enterprise AI evolving? So I shared my thoughts, right, and going back to that mainframe era. I know a lot of companies like banks, insurance companies. Going back to that mainframe era. I know a lot of companies like banks, insurance companies. They are still on mainframe, given the architectures you know in the enterprise computing. You know it is very difficult to move to the latest and greatest, given SLAs and you know lawsuits and all those things right.
Speaker 3:So on the Java side, I worked in Sun Microsystems in India for almost three years, the guy who invented Java also I was able to. I was part of one leadership committee way back, so I was able to meet that guy, james Gosling, who invented Java and it's a very interesting experience. But when I put that also in the context, java, the latest version is Java 20 plus right Now, oracle, bot, sun, they have 20 plus, but in production they will have old versions of Java. Still, I know Java 8, which was released way back in 2006-2007, their enterprises are using it. If we put mainframes and Java versions in the enterprise penetration right In the production environments, people will be doing a lot of testing and POCs and sample projects. But for enterprise applications or CRM kind of applications, how do you guys see this AI going to, the transition or adoption of this AI in this ERP and CRM space?
Speaker 2:That is a challenging question. In my opinion, you brought up some key points. It's where is an organization in its journey? Which systems do you have? Also, which systems and which tools are available? I think you need to have a combination. Should you always have the latest and greatest? I don't know. I think, in my opinion, sometimes there's risk and you need to evaluate what you use. I think for those more mature organizations, there may be pieces that you can plug in. So if you think of even going through to bring it back to a point, to a business, central implementation or implementation of an ERP application, it's a matter of architecting a solution with the right pieces and putting those right pieces together to get the desired results.
Speaker 2:But individuals also need to almost change their way of thinking at some points to ask questions outside of the predefined constraints, Because a lot of times people make decisions based on the past.
Speaker 2:I know, running through this woods I ran into a bear.
Speaker 2:So now I'm going to make sure every time I come through this point I'm going to ran into a bear. So now I'm going to make sure every time I come through this point I'm going to run into a bear. But now I need to make sure, if I go down this path, I do all this stuff but in reality, that bear may never be there again. So you have to take off the constraints of the limitations you had based upon the past and not think that you need to do something in totality to where you have such a radical shift, but maybe compartmentalize the pieces to incorporate those changes Again the efficiency that you can get in the AI to where you can increase the adoption within your organization and ensure that it's going to give you the desired results as well. It's a lot there of what I am saying, but I think organizations need to evaluate where they can get the benefit of using a tool, making sure they use the right tool and don't use the tool just to use the tool.
Speaker 1:Yeah, that's a good point, Brad. From my perspective, there are two different paths, because there's still some human element. As you know, when someone uses a technology on their personal life, they typically bring that to work, expecting to do the same thing. There's still a lot of education that still needs to happen when it comes to AI. I've had a lot of conversation, a lot of people, even day-to-day people, that talks about AI and they think it's a one one solution fits all and, as we know, in our space, that's not always the case. That's not the case at all, because now we're talking about agentic or agents that are used in the back end to do some specific task or give you results or just have a plain conversation of when you're having that utilizing ai. So I I still think we have a little bit of time that we need to educate everybody that there are differences between the two, because you talked about Gemini right as another LLM, but then you also have Copilot and so from a public perspective, it's just an AI to have a good natural language conversation, but in our space, in the enterprise space, that's not the case.
Speaker 1:But in our space, in the enterprise space, that's not. We're going to have systems talk to each other and what comes to that means there are going to be things or, unfortunately, positions that are going to be replaced because of those co-pilots or because of those agents, and I think, from a business standpoint, that's going to be a place where you need to plan. You know what does that? What does that mean for your business? Um, that means more time for you, maybe more time to be more creative, but even then, creativity could be replaced as well, it's like ai, it's, it's one of those never-ending cycles, but we also have to.
Speaker 2:It goes back with time. It's sometimes you have to worry about what's in front of you versus so far into the future, because you don't know and nobody can predict what will happen. Uh, the any businesses have evolved since back in the early days when they use ledgers with ink pen, inkwells and pens, right quill pens, and now then you had the ballpoint pen and the pencil, and then you went to computers with spreadsheets. So there's always been an evolution in of efficiencies and gaining of those efficiencies and then just a reallocation of talent to do those tasks that haven't been to the point where they have been as made, optimal, I guess you could say, or added the efficiencies. So it's.
Speaker 3:Yeah, I think both your points are very valid and very interesting perspectives. The way I look at is the ROI right. As a business, they will see what is the ROI on their investments. So, especially with the teams summarization now when I am using teams in my workplace after the meeting previously I used to take the notes and all that information. There will be someone who takes the notes and share that after the meeting. Now, with the team scope, we can get a summary of the meeting pretty quickly. Perfect, that is a very good ROI. For me, that is a great use case.
Speaker 2:I don't mean to cut you off, but with Teams turning on the transcription to record it.
Speaker 2:some individuals get a little nervous, thinking I'm going to do the video recording or someone has the recording, but I agree with you. Recording, or someone has the recording, but I agree with you. Just something as simple as doing the transcription of the voices gives you the benefit in the meetings that those participants can pay attention to what's being discussed instead of worrying about the notes that they have to take, because you cannot do both tasks at once. If you're spending time trying to write the proper notes, you're not listening. I don't care what anybody says. They think that they can multitask listen and basically listen and talk at the same time.
Speaker 2:So I just want to bring up something as simple as that is a huge gain. And you get actual summaries, and I don't know why. I wish I could have it set where it says okay, record any call that I jump into for the transcription so I don't forget, because there have been times like, ah, I wish I had this on and I forgot.
Speaker 1:Do you remember, on meetings like that, where you have someone's responsibility and that's all they did was note-taking? If you guys recall back in the day, where you sit in a Conference you have somebody sit in the back corner, that's all they did was take notes, right, that's my point. Right, like there's gonna be a shift where that role is no longer needed in. It's a lot more accurate for note-taking, right, and and so it's. It's always always listening when a human may be distracted, and so it's always always listening where a human may be distracted. And they forgot a specific note. Now, with Copilot, to be able to do that for you and summarize and even ask, like, what was the action items out of this meeting? Because you want it to be a productive meeting, it's going to tell you, versus having to like ask that person, say, hey, can you type that all up, and then by the time you get those notes, it's the end of the day where Copilot can give you that information right after that meeting.
Speaker 3:Yes, I think that you are right that jobs and all those they need to be retrained or they will be going into a different place in this era. That is one of the reasons in the Copilot Studio. Microsoft enables us as soon as we create the agent. It allows us to publish to the teams first Teams are. It gives a different channels where we can publish. It Looks like the teams is one of the very efficient way to interact. And another use case also recently I was working with one of the very efficient way to interact.
Speaker 3:And another use case also recently you know I was working with one of the clients. They had a lot of knowledge base. They went with a big implementation right of their ERP but that was not successful. So they were trying to evaluate and we got RFP. I was trying to me and my team members were trying to look at their business models or business rules. What exactly is their business? So I cannot share the client details, but it is in the healthcare sector. There is a lot of information. They went for the ERP implementation for almost one, two years. It was not successful. We got a RFP.
Speaker 3:So generally the process was go through all the documentation to understand their business, specific business, because you know their business process and what are the challenges that they faced. So what we did was we took their Word documents, their PDFs, their audio, their video recordings and downloaded the transcripts. We combined all those things and we uploaded to the SharePoint and created a co-pilot on top of it and started asking questions to the co-pilot Say that hey, what is the business process? Can you explain in broad I know high level 10 steps. Surprisingly, it was able to give us at least six, seven steps correctly.
Speaker 3:So we started fine tuning the prompts and adjusting, given what happens is this copilot, once it goes to the knowledge source, in our case the SharePoint documentation, the backend, it indexes and it creates a structure so that the co-pilot can efficiently go and read and give the response. So we need to do some kind of fine tuning. But instead of going through all the documentation, videos, transcripts, I asked what are the different statuses, what are the major modules? It was able to give me all that information. That was really, you know, reduced my work at least 200 hours just to go through the documentation.
Speaker 2:It's incredible the use. I just get excited and I can go off on tangents because think, now, having all that information readily available, you also don't need to memorize and if you can retrieve the information quickly, now you can prompt to get the information back without having to spend time searching or memorizing or going through. Nothing's perfect, but even if it can get you 80% of the way there, or even something as simple as you had mentioned, that it can do surprisingly well most of the steps or most of the things that are outlined, at least it gets you started and it can show you the reference documents where you can look more. I'm waiting for the day where I just it's like we plug in the microphone jack into a computer to speak that you have a little jack you plug into your head and you just think and all of this information will come into your brain and you know. It's like having an external hard drive Exactly, you know.
Speaker 1:What's interesting is that you gave this a perfect example on a specific industry that's. You know, even in legal it's the same thing If you ever dealt with. There's a discovery and there's like tons and tons of documents and typically a paralegal would be the one that's doing that. Right, they would have to reference a specific document, and it's a lot of writing and all this stuff. Now you can just use Copilot to do that and be able to summarize or even search for a specific thing like, hey, did this person say this? And then they'll say yes, they did for that particular topic, and then it's going to reference where it found that on the documentation. So that's actually a perfect use case.
Speaker 1:Sorry, and it goes back to the co-pilot that we were talking about, where a co-pilot is someone that can when I say someone, see, I'm referring it, now, it's like a human being someone that can, when I say someone, see, I'm referring it, now, it's like a human being, it's a tool that coordinates all the other agents. Another perfect use case for that would be if a client interacts with your co-pilot and says, hey, I want to look at your products that are available based on my description. I'm asking. Then it could look at your data database and looks at hey, these are the items available for this business and then if the client's interested in purchasing that, then that same co-pilot can call another agent to create a sales order. So you got to look at that way. When we're talking about co-pilots, that's another use case. When it's calling multiple agents based on different tasks One's informational and then the other one could be a task where it creates a sales order and then submits it to maybe a business central. So many different ways, use cases, so many different ways.
Speaker 3:Use cases. Yeah, that legal area is legal vertical, especially legal industry, like healthcare is also. So I was very interesting this AI is going to disrupt more. I was reading somewhere about which area AI is going to have a very quick ROI. Looks like it's interestingly a financial sector, because everything is really predictable, mathematical. So what they are saying is in the financial sector AI will have a lot of impact, means it can bring a lot of ROI In terms of healthcare. It can unlock a lot of new medicines and solve and come up with a lot of breakthroughs in the healthcare sector. So, as in legal, which is more on the documentation side. You are right, Chris, the paralegal work, like meeting notes, paralegal work also could be now backside. You know, take a back step, or paralegals can use the copilot to come up with their understanding and revalidate.
Speaker 1:Finance is interesting, though, because it's a large, natural, large language model, but it doesn't does it do a good job crunching numbers, though, if it gives you a bunch of data.
Speaker 2:I think you need to have the right tool for the job. That this is where it goes back to. If you're trying to use a hammer to do math, it's not going to work. If you're going to use a calculator to do math, it's going to work. And this is where I think humans have this natural ability to want to destroy. You build a robot. People will start throwing things at it. Why? Because Because it's a robot, and I think the same thing.
Speaker 2:When this first came out, everyone's like oh, I trained it to do four plus four equals nine and not eight. It's silly, but you have to step back. That's not what it's supposed to be doing. It's supposed to retrieve and summarize and show information, not do math. So even go to the agent. The agent that sends the email isn't going to be the same agent that responds to the email in our scenario. So it's a matter of using the right tool.
Speaker 2:You mentioned model Sai or the right agent for the job. So I think, with finance, depending upon listen, finance, if you're talking investments and finance that whole market can spiral if you just let it go, ai out of control, because it will just read the patterns and respond to the patterns and you could just have a sharp crash or a sharp spike. But I think, from an organizational point of view, you can use AI to help with financial information, financial reports or even some analysis of information, which you need the right agent and you also need to have the proper data. This topic can get me all of it when it comes to AI within the world. It's great, but to go back to now, business Central, to go back to Copilot, agent Power Platform and the use of AI within that space is where I really like to focus, because I think, brad, the enterprise, especially enterprise, ai, Microsoft, the way I assessed a couple of years back, I think that still holds good.
Speaker 3:The feature also looks like Microsoft is going to win a lot of Dynamics 365, er, pcrm and go head-to-head with Salesforce, hubspot, oracle all the spaces given their ecosystem, microsoft ecosystem, especially with Cloud, azure, with data. They streamlined their data platform. Now they are calling it as a Microsoft fabric. So that is a. Satya told that that is the greatest enhancement that they did to their SQL Server data platform. Right, sql Server, power BI. They have ETLs I work with their ETLs like Azure Data Factory and SSIS, ssrs, all those things you know. They all club together and now they are calling as a Microsoft Fabric. Data is one of the very important things for these co-pilots or agents to work. So Microsoft really, you know, nailed it. It is competing. I have some experience with Snowflake also, which can go to different clouds and gather the information. That's what.
Speaker 3:I was a data architect for a couple of years. In 2017 to 2019, I worked for Ford and FedEx as a solution architect. I started with the programming language. Then, in one of the meetings, one of the project managers said, hey, that is a matrix organization. I asked what is it? Project managers said hey, that is a matrix organization. I asked what is it? He said, hey, that is a PMP thing. So I said I'm interested to learn. Can you help me? He said go and get PMP. So I went and I got PMP and in almost 2009,. They gave me a big project. I ran the project. I understand how to run the projects and what it is. I got real good respect for the project managers. Then I looked at the space and architecture is the technology thing that I like. So I worked as an architect. I went and I got my TOGAF Enterprise Architecture Certification to look at the space, this IT, differently. So that gave me a different lens when I look at all these things and put this AI journey.
Speaker 3:Microsoft is having Microsoft Fabric ecosystem, which is a data which is core to this co-pilot. It's a knowledge base, and they streamlined their security landscape. They have Azure or Azure KD and all those things. Now they are calling it as Azure Entra. So Copilot is there. Now if people have Copilot enabled in their Azure security, they can go on just prompt it and say that, hey, what are the security risks? There are a lot of tools, from Microsoft to Microsoft Defender and all those things. So Microsoft platform, you know, especially the implementers or partners. There are a lot of tools from Microsoft to Microsoft Defender and all those things. So Microsoft platform, you know, especially the implementers or partners are going to win big in this year. That's how I am seeing, given the way they are able to.
Speaker 3:The co-pilot is integrated into all different areas of Microsoft M365, you know, licensing, security, data, dynamics 365, erp, crm, bc and they created the platform. See, one of the things that Satya did was that we escorted that IDE and GitHub. All these things are so tied together. I think this year is going to be a very good year for Microsoft. In fact, in one of the meetings I think Satya was saying that he was surprised to see Dynamics 365 is winning a lot of bids, you know, in their sales.
Speaker 3:I think that's where the power of this co-pilot agents are going to be for this enterprise and implementers, especially business central space. If you look at right in the SMB space, according to Gartner and Magic Quadrant, there are very few competing companies right, netsuite, bc. So in that also, oracle NetSuite is not having the kind of ecosystem that Microsoft is having right, so they don't have the Copilot, they don't have the Azure Cloud. They don't have the Azure cloud. They have OCI, oracle Cloud Interface. They are still evolving, whereas Microsoft they have copilot, their UI and the backend it's the agents. I think it is one of the really good years.
Speaker 2:They can use the connector. Well, there's a lot to copilot and you're mentioning the ecosystem from the Microsoft platform, which to me you mentioned that fabric is sort of a blend of a lot of different separate services now into one level plane. I think the whole ecosystem is changing as well, where you have the ERP interface, the ERP software, the data backend, the automation, the tasks. There's a lot to this. Copilot within the Microsoft ecosystem we talked about co-pilot studio, we're talking about agents, we're talking prompting when is the best place for someone to go to learn? And also, how much do you learn? Right, I mean it's I drive a vehicle. Do I need to know how to build the vehicle? Do I need to know how to fix the vehicle? I just didn't know to go to talk to somebody, but I still need to learn how to drive the vehicle. Or you know where do you go to do what, but Brad, that's like this journey.
Speaker 1:That's like back in the day when someone says I'm in IT, right. That's like back in the day when someone says I'm in IT, right. Back then it was like, oh, you fix computers, but now that's not the case, right? When you say I'm in IT, it's like which part If anyone tells me they're in IT?
Speaker 2:Chris, I don't even talk to them anymore, because if someone says well, what do you do? And they say I'm in IT To me right there, that just means I'm not going to talk to you, because you think you do everything and you really don't, because it's impossible to know everything in IT.
Speaker 2:It's almost like AI, because AI itself encompasses much, much more than what people think it does with just saying a large language model. But where are some? Where can someone go to start to learn their journey of maybe creating an agent to do emails for a podcast, or maybe even help schedule their calendar time, or I don't even know? I'm trying to think of all the other practical uses you could use, both professionally and personally, to have some of these agents simplify your day so that you have more time to do the things that are enriching you in your life and your family's lives.
Speaker 3:Yeah, sure, I think Microsoft documentation is the first place to go. I always refer that learnmicrosoftcom there for this co-pilot. There is a very good documentation. Microsoft really improved over the few years. That is the best place and to know complete details, technical details about it. And if you have a question in the Microsoft copilot studio and all those things, go to the forums. Microsoft is having good forums, dynamics, our Power Platform, community forum from Microsoft. I answer a lot of questions in that, so that's another good place to get quick answers.
Speaker 2:Oh, I'm going direct to you.
Speaker 1:after this, we're going to have a lot of conversations. You do a newsletter too, right? That's what I was just going to mention.
Speaker 3:I publish weekly a newsletter called D365 Co-Pilot Digest on LinkedIn. In that, my goal is to just give a quick update on four things. Number one, dynamics 365, erp or CRM. That is first one. What are the updates that Microsoft is publishing Are they releasing any new co-pilots? And second one is Power Platform how the Power Platform is evolving, given Microsoft is publishing are they releasing any new copilots? And second one is Power Platform how the Power Platform is evolving, given Microsoft is integrating AI into copilot, into their Power Platform source, like Power Apps and Power Automate. So that is the second topic I write weekly on the Digest. And third one is Copilot Studio or AI, microsoft AI related things. And fourth one is Microsoft Fabric, or, uh, yeah, I, microsoft, yeah, I related things. And fourth one is microsoft fabric, microsoft data platform related. I feel like these are the core for this next evolution. So I write this uh, linkedin digest. You can find that digest on the linkedin I. You know I can share that information we'll also put the.
Speaker 2:we have a guest page now, so on the episode on the website, we'll also put the profile, which has a link to your LinkedIn profile, so that someone could read past issues of your digest and also see the new issues that are coming out. So, cy, my mind is blown again this AI thing. I don't know where to begin and where to end with it, but You're still confused. It's not that I'm confused, I understand it, you know. And some things I say in jest, because it's just so much, so fast, that I think it's important to find the nugget that interests you or you think that you'll benefit from and be aware of the others and pursue that.
Speaker 2:It's almost like the master of what is it? Jack of all trades, master of none. I think you need to start focusing on where you think you'll get the best ROI for what you're going to do and then be aware of the other stuff, because you may have to change your thought process because of something else that you can incorporate to what you want to do. So I'm not confused, I'm overwhelmed and exciting, and I could go down so many different tangents, because AI itself has so many different roads that you can go down side roads or side streets.
Speaker 3:I guess you could say yeah, broadly two, two, two areas. Right one is b2c space and under is enterprise b2b space. So in the b2c, b2c space there is so much happening, you're right who are going to be players? Especially deep seek model is able to. You know the the thing that happened.
Speaker 2:It's also very interesting the new I need to get one of those, and we'll have an episode coming up shortly to talk about that. But I need to get an lm installed locally, or do I even need to right that's my question. It's do I need to have it or can I just use one of the existing tools and models and go from there?
Speaker 3:I think that's a whole other question it is like you know your personal laptop versus having a vm on the cloud right, so do you. Which one you prefer?
Speaker 2:well, it's a matter of mac os well, si, thank you, I could talk with you for days and, uh, oh, you're going to hear from me shortly after this because, chris, we're going to get some emailing set up, hopefully even some. Yeah, we should build one out. Yeah, even even some.
Speaker 1:Oh no, sorry, you volunteered did you hear that we have it on recording? Definitely.
Speaker 2:So yeah, we'll get some emailing ai set up that's in in some fashion to assist with the scheduling, to give us the opportunity to speak with more guests and not have to schedule.
Speaker 3:Yeah, if you guys are doing manually, we have to optimize that. You know, the four-hour work week book is the best one. You know, when you try to do this kind of really at scale, try to automate it and optimize it so that you can just move on.
Speaker 2:That's where we're looking to go, but again, thank you again for all the information you shared. Thank you for all that you do for the microsoft ecosystem. You share a lot of information. I read your digest as well, as I do come across you at some points, uh, within the forum, seeing some of this as I'm reading up on it. So we appreciate that, all that you do. In the meantime, if anybody would like to get in contact with you to learn more about AI and some of the approaches that are available, what's the best way to contact you?
Speaker 3:Yeah, linkedin, sai Thurlapati. Or, like you mentioned, there will be a page. I will share that information with you. Or D365, copilot Digest is the other newsletter. Those are the two ways.
Speaker 2:Excellent, excellent. Thank you again. We appreciate your time. Look forward to speaking with you very soon.
Speaker 3:Very, very soon, thank you. Thank you so much. I listened to your episodes. I learned so much.
Speaker 2:Thank you. Thank you, we appreciate it. Have a good day, ciao, ciao.
Speaker 3:Bye for now. You too Bye.
Speaker 2:Thank you, chris, for your time for another episode of In the Dynamics Corner Chair, and thank you to our guests for participating.
Speaker 1:Thank you, brad, for your time. It is a wonderful episode of Dynamics Corner Chair. I would also like to thank our guests for joining us. Thank you for all of our listeners tuning in as well. You can find Brad at developerlifecom, that is D-V-L-P-R-L-I-F-E dot com, and you can interact with them via Twitter D-V-L-P-R-L-I-F-E. You can also find me at matalinoio, m-a-t-a-l-i-n-o dot I-O, and my Twitter handle is matalino16. And you can see those links down below in the show notes. Again, thank you everyone. Thank you and take care.
