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Microsoft Just Showed Us How To Use New AI Agents… TheAIGRID

um is uh let’s say you wanted to build a field service agent that you want to interface into co-pilot uh all you got to do is give it a system prompt tell it that hey I want you to be a field service agent point it to a SharePoint site where there’s a bunch of documents related to field service uh add to it even additional data sources in this case their Dynamics uh as the system of record for field service and you have an output which is essentially a field service agent which now you can talk to uh and have a conversation with just like you would with any other regular co-pilot conversation right so that Simplicity it’s kind of like back in the day we just created an Excel spreadsheet right it’s no more mystical than that uh just like how you could create an Excel spreadsheet that was a forecast you can now create AI agents using a low code no code tool like co-pilot Studio put it into co-pilot uh you can even think of these as the new form of applications uh and that so that was Sachin Nella at the AI tour in London showing you all just how easy it is to create AI agents now I think most people don’t understand the entire AI stack that SAA nadela talks about he talks about co-pilot and how this entire thing is going to be integrated with AI and I think this talk is one of the very best ones that we get to see how the future of work is we know that Microsoft is integrated into tons of computers even if you’re not on the Mac and this is going to be a really integral piece of information because this is Lar largely how the future of work is going to be on our personal computers so I’m going to break down this keynote speech giveing you guys the details but this is one of the most insightful things that didn’t get enough recognition so firstly Sati Adela actually speaks about how these agents are going to have reasoning and planning some of them are going to have memory and how this brings together the agentic experience for not just work but for a variety of different experiences that we’re going to be having in the future uh to make sense of it and then lastly you can feel it more context more memory uh so you put all these three things together you’re building out a very rich AI or agentic world uh in which you are going to have these AIS or agents right there will be some AIS and agents that are personal agents uh there will be things that will work in the context of a team in the context of an organization or business process or even Cross organization so this Rich tapestry uh of AI agents that augment uh everything else that we built right so that’s the other part the entire digital infrastructure and tools that we today have get augmented in this agentic world uh with all these AI agents that we build using the scaling laws as the underlying Force now of course it’s so then this is where we actually get Sati Adela talking about how this is going to be the UI for AI how copilot is basically going to be the interface for how AI interacts and integrates with your computer I think that’s the best way to put it because it lets people understand how the future of a gentic AI will be when it manages to merge with your computer and other essential applications pilot uh to us you should think of co-pilot is the UI for AI That’s the simplest way I think about it uh we then have uh the co-pilot and AI stack so to be able to for you to build your own Ai and AI agents uh and co-pilots we have a full uh and then lastly this new set of devices which are these co-pilot devices um and so I want to talk about each of these platforms starting with copilot now as I said if you start with this idea that this Rich agentic World ultimately does need to meet us and we need to meet it that means you need a UI interface right just like the PC or the phone was the user interface or the apps on a phone or a PC with the interface uh to essentially digital technology uh these co-pilots or and co-pilot is the UI for all of this AI right even in a world where there are lot of agents that are working autonomously uh they do need to raise exceptions get permissions uh from us and the question is how does that happen it happens through this new organizing layer for how in particular work gets done uh in fact work work artifact and workflow is going to change uh a great example of this is just a couple a month ago we launched something called Pages just like say back in the day in the 9s we launched Excel or you know word uh which were art you know basically editors to create new artifacts pages is the first I would say user experience to create new AI first artifacts right I can search the web or my work for retrieving information um and then I can put it into pages and it’s a document for it’s a document that I can then share across the organization and I can work with AI and humans in fact I sort of say the metaphor I use is I think with AI and work with my colleagues at work right that’s the new workflow what do the previous workflow i t on my own I created artifacts and I shared it across the organization and collaborated but now I not only I have a cognitive amplifier effectively with AI uh where I do my work and then I create artifacts and I collaborate with my colleagues in order to get things done and so that’s really the beginning of this co-pilot era uh where it’s just not about a chat interface but it shows how chat is just one modality of being able to retrieve information but it does lead to more sophisticated workflows and collaboration now you extend so the other thing is that this is not just about any particular artifact editor or workflow we created but you can extend co-pilot with any agent you build in fact co-pilot studio is a low code no code way for you to be able to build agents um and and these agents are really grounded in a rich set of data sources starting with in fact the most important database in most organizations is the database that contains all your office information right who works for whom who who are my colleagues on this project what documents are there uh related to a particular team or a project uh what is the relationships between all of these documents and people and projects all of that and all the emails you’ve had teams conversations you’ve had that’s all in fact in a first class database called the graph or the substrate that is now exposed through a graph uh in M3 now in addition for those of you who think that building AI agents might be difficult in the future sat nadela shows us exactly how quickly it’s going to go from prototype to working agent that you can use within your workspace that actually works really effectively and can do tasks on your behalf um is let’s say you wanted to build a field service agent that you want to interface into co-pilot uh all you got to do is give it a system prompt tell it that hey I want you to be a field service agent point it to a SharePoint site where there’s a bunch of documents related to field service uh add to it even additional data sources in this case their Dynamics uh as the system of record for field service and you have an output which is essentially a field service agent which now you can talk to uh and have a conversation with just like you would with any other regular co-pilot conversation right so that Simplicity it’s kind of like back in the day we just created an Excel spreadsheet right it’s no more mystical than that uh just like how you could create an Excel spread sheeet that was a forecast you can now create AI agents using a low code no code tool like co-pilot Studio put it into co-pilot uh you can even think of these as the new form of applications uh and that this is where we actually get the openi demo of the agent that you saw in an earlier video that I posted so this one is a lot more detailed because it is a Hands-On demo and this has a real working example so I’m going to let them take it away for the 6 minutes that they have but I think this is probably one of the most important pieces of content you’ll watch because you truly will see how the future is changing right in front of you please don’t miss this kind of content because I think the future is going to come quicker than you can imagine and not paying attention to exactly how the world is changing is a grave mistake but nonetheless this is of course these Microsoft co-pilot agents let’s take a look it all starts with an incoming email from a prospective client much like you see on the screen right here now previously they had had people on the back end essentially receiving these emails parsing through them and figuring out what to do next who should it be routed to what expertise did they have in The Firm but this is where the autonomous agent comes in now an email comes in and the agent Springs into action what you see here is that it will begin to parse out the email moving through the ambiguity of human language to for instance find out what the engagement is about to check the engagement history to also map it to their industry standard terms and then finally to try and find the right person to take the next step within the firm with all of this information in hand the agent then goes about writing an email that takes all of this information and summarizes it for the receiving partner and what you see on the screen is exactly that in comes a whole bunch of human written email the agent processes it summarizes it and sends it to the right partner in The Firm to take that very next step now it’s worth pausing for just a moment here to reflect on what you’re seeing it happens so F you you might miss it but essentially this agent has been given a loose set of instructions kind of like you would to a human and it deals with all of the messiness of human communication figuring out what the right next touch point is for the customer now this is Magic but it’s only half of the magic because now we’re going to go behind the scenes to see how easy it is to actually create an agent just like this for this we will move over into co-pilot Studio here you see that we have programmed up with McKenzie the agent but not using a sophisticated programming language instead using natural language the same way that you would tell a colleague to get ready to do this task you also see that what makes this agent autonomous is that we can set what’s called a trigger in this case the trigger is set to watch an email address and to react immediately when an email comes in but in fact you can set it to look for events across a whole wide range of systems sitting there working for you 24/7 waiting for an event to come that gets it going you also just like a regular human colleague add knowledge here we see a Word documents a SharePoint site and a database about engagements but of course you can add additional knowledge sources that includes line of Business Systems like sap or service now or even databases and finally to finish up what you give this agent to do its work you give it a set of actions and we saw those in the flow these are actions that include things like pulling out the relevant information or summarizing what a human has written all of this together makes the agent powerful because it can deal again with all of that ambiguity that a human throws at it now what we saw was one email coming in about one new client engagement but the exciting thing here is that this scales how does it scale well the see that we’ll go over to the activity pane where we can look at the long list of engagements that it’s working on zooming in up top for instance we can see that it’s worked on over 1300 engagements and there are 33 in progress if we want more details we can go into the analytics tab what this means is that this agent is always working on behalf of the firm and that’s very exciting for us now from here we also see that although the agent’s amazing it does sometimes need some human help so we’re going to jump into a case the second from the top here where we will see that it gets a little bit stuck as you look it’s gone through those steps that we saw previously but it’s stuck here at that one where it’s looking for the partner and if we zoom in we can see why here for instance we see that it’s picked the right partner but that partner has now left the firm it has an instruction that says if that’s true it needs to escalate to a human manager to give it someone else to go to now to see what that looks like we’re going to switch over to co-pilot and see that interface with that human manager here at the bottom right you will see that a notification pops up in co-pilot then the manager gets all the information he or she needs and can provide the right person to Route the email to back at the ranch going back to our agent we can see that it takes that information and fills out what it needs to do now we’re excited about this because of the business value it can drive McKenzie and its trials has shown that it can reduce lead time by 90% reducing o administrative overhead by 30% and as you look at this list what we envision is an orchestration layer just a bunch of agents that can be out there helping individuals teams and entire functions to streamline and automate their processes no matter what industry they’re in they’re so easy to make anyone can do it you design and set these co-pilots out to work in co-pilot Studio you interact with

FOR EDUCATIONAL AND KNOWLEDGE SHARING PURPOSES ONLY. NOT-FOR-PROFIT. SEE COPYRIGHT DISCLAIMER.