AI Personal Assistant 2.0 | This Agent Calls Other Agents (No Code) in n8n

so I said can you schedule a meeting for tomorrow with Michael Scott at noon and then can you email him to confirm if that works so we're going to fire that off we'll see it take place real quick it just got Michael Scott's email information from the contact database now it's going to go back to the agent and then the agent is going to figure out which agent to send it to as you can see it's hitting the calendar agent as well as the email agent looks like the email just got sent looks like the calendar event just got made and now it's going to respond to us the meeting with Michael Scott has been successfully scheduled for tomorrow at noon additionally an email has been sent to him to confirm if that time works you can view the meeting details here as you can see here's that meeting confirmation hi Michael I hope this message finds you well I wanted to schedule a meeting with you tomorrow at noon please let me know if this works for you looking forward to your confirmation best regards Nate and then hopping over into calendar we can see tomorrow at 12: to 1:00 p. m we have a meeting with Michael Scott and if we click in we can see that he was emailed as well for the um meeting a few weeks ago I uploaded this video where I showcased this personal assistant AI agent that I made within NN and you would be able to talk to it and it would take action on your behalf within Gmail calendar Google Sheets Etc so today I wanted to introduce you guys to personal assistant AI agent 2. 0 so I've come back and I've made this agent a lot smarter a lot faster and more scalable and here's how switching back over to the original personal assistant we gave it access to the following six tools two in database two in email and two in calendar now switching over to the new version instead of giving the agent access to tools we gave this agent access to four different agents it has email agent which has actions within email calendar agent which has actions within calendar and the same thing for a research agent and a projects agent this is a lot more powerful and a lot more scalable because once the agent gets the incoming message from our telegram trigger rather than it figuring out which tool it needs to go to and passing a ton of information between each step it's just going to be figuring out okay if I need to do email I'm just going to send it to the email agent and the agent's going to take care of it same thing with the other agents it's super powerful and super scalable because the prompting is a lot less intense and we can start to slowly add more agents and more agents for example if I was to text this personal assistant and say hey can you email Nate and remind him about our meeting at 3:00 it would get this message and then it would think okay I need to email someone so first I'm going to get that information from the contact database and then all I have to do is send this information to the email agent because the email agent knows how to take care of this so I hope you guys already see how powerful that this type of AI agent framework is going to be um we're going to get into examples we're going to test out every agent every tool that this personal assistant has access to but before that I just wanted to quickly set a goal um I'd love to make a how-to sort of step-by-step tutorial on this sort of build and I would love to do that if we can hit 1,000 likes on this video I think that's a good goal to set and it would be a new record high for me so let's see if we can get there but with all that being said let's hop into a first live example where we'll be using the calendar agent so real quick I'll open up the calendar agent workflow as you can see this agent is being called by the larger agent so the trigger is when called by another workflow this agent all it has to do is understand the incoming query and then figure out which of the three tools it needs to use it can get events it can create events or it can create an event with an attendee and then all it's going to do is respond to um the agent with the success message or it's going to tell it that there was an error and tell the main agent to try again all right so we're going to hit test workflow on this main agent so that the telegram trigger is listening for a telegram message I'm going to pull up telegram paste in this message real quick that says you create a calendar event with Michael Scott for tomorrow at 600 p.

m. for dinner we'll fire this off we will see it taking action it looks it's looking in the contact database to get that email now it's hitting the calendar agent and it should be finishing up anytime now so we got the message the calendar event title dinner with Michael Scott has been successfully scheduled for tomorrow at 6 p. m.

and an invitation has been sent to Michael Scott so let's check our calendar as you can see right here tomorrow 600 p. m. we have dinner with Michael Scott and if we click into here we can see that he and fact was invited Michael Scott was one of my emails so this is the email that it sent off to so that's the proof that this agent is working let's go back into the agent click on the execution and make sure that it actually did do exactly what we said so this is the most recent execution of the calendar agent the query that it got in the beginning was to create an event titled dinner with Michael Scott for tomorrow at 6 p.

m. invite Michael Scott and then it searched our contacts database in order to pull that email which I filled in as up at digital gmail. com so then once the agent saw that it knew that it had to create an event EV with an attendee so let's click into this node see what's going on and before I hop into this stuff I want to explain why I decided to come in here and update my personal assistant I saw a video from AI Workshop subar hey if you're seeing this keep up the great work but he showcased these new tools that you can give agents that are much much stronger than they used to be so there's this this Javas JavaScript function which is dollar sign from AI where you can tell this node what to fill in for each of these parameters so previously you would kind of have to map them out based on the input and you would use some sort of like open AI node maybe to figure out based on a query what's the start time what's the end time who's the attendee and then the summary of the event but now you can have that sort of baked into this note so from AI you're going to label the what it's pulling so in this case it's going to search that query and look for a start time and then I gave a brief description of what that start time is I'll explain this in a in a sec in a bit more detail not in this editor so we can understand better but basically it's just a way to bake in the AI is going to look at the query and interpret start time end time attendees and summary so it's a lot lot smarter than it used to be so as you can see it filled in the start times automatically it filled in the email and then it filled in the summary the title of the calendar event dinner with Michael Scott and then all it did in the success message was sent out that the event dinner with Michael Scott was created and it responded to the agent so that the agent could respond to us all right so I wanted to hop into the editor real quick and explain this dollar sign from AI thing in more detail so that for the rest of the nodes and the Agents that we're testing out it's all going to make more sense so let's come in here and pretend that we're adding another calendar tool we're just going to say that this is another create event so to create an event in your calendar once you have all your credentials set up you need a start time an end time and then let's just say we want to add a summary as well which is just the title that shows up in Google Calendar so from the query let's say we asked you know can you make an event for dinner from 5: to 6:00 so obviously the start time end time and the summary are all in there but this node doesn't know that so we need to give this node some context of how to fill in these different parameters so typically what I would do is once that query comes in we would run it through like maybe an open AI node to message a model and then that model would figure out what's the start time what's the end time and what will we title this event but now we don't even need that we can just sort of come in here and we can do a an expression which is going to be um dollar sign dollar sign right here from AI click on this and then we can see we need to add a key and then we can add other things that are optional usually what I've been doing right now is adding a key and a description so in this case the first thing we need to enter is a key so we're filling in the start time parameter so our key can just be start or I guess let's just do start time to make more sense and then if we we can leave it as that and the AI will probably be able to figure out what the start time for the event is but if you want to be more detailed you could add a comma another quotation mark and say the start time of an event and then end the quote and it should go gray and that's how you know that it's going to be good to go because then the AI will read in from here based on the query what's the start time and if it can't figure out the start time it's going to look at the description in order to understand more context about the start time so that we did the exact same thing let me just go back into the execution real quick we're going to look at the create event with attendee node that just executed with that example that we did as you can see the start time is from AI it's looking for a start time we said the time the user asks for the event to start same thing with end time except for the event to end then for attendees we said we gave the key of attendees and the description for what an attendee is is the person or people that the user is asking the event to be scheduled with so in this case it was upad digital gmail.

com and then finally we gave it from AI the key is a name and the description of this is just a name for a calendar event so hopefully that made sense to you hopefully I explained that well but basically all you're doing is within each parameter you're telling the AI how to pick out of the query what should be going in here all right we're going to do another quick example of the calendar agent our telegram trigger is listening to us we're going to send off create an event for today at 400 p. m for my meeting with my team it's going to check that talk about what we need to do hit the calendar agent and then we should be seeing a success message the schedule or sorry the event titled meeting with the team has been scheduled for today at 4 p. m.

top end of the calendar we can see right here after an event called gym we have meeting with the team real quickly let's test out the last tool the calendar agent has access to which is getting and summarizing a calendar so I said can you please get my calendar for today we'll send that off it's talking to the brain it's hitting the calendar agent and then we should see back in telegram our calendar getting summarized for us so let's just give this one sec to finish up the run it just finished so we should be getting the message any second now it's just summarizing the information there we go calendar events today November 5th we've got gym from 3: to 4:00 meeting with the team from 4:00 to 5:00 and then dinner from 6:00 to 7:00 we also invited up at digital at gmail. com and you can also click on view event right within here and it will open up the acttion actual calendar event for us so as you can see we have the gym we have meeting and then we have dinner so it did that successfully all right the next agent we're going to be looking at is going to be the email agent so let's hop into this workflow real quick same thing we're calling this agent from another agent so that's why the trigger is here and in this case we're only giving it send email and get email messages you know there's so many different options if we come in here to gmail you could um delete messages you could Mark some as red mark them as unread you could add lab you could reply and that just um involves using different things filling in different parameters but for the sake of the video I just wanted to keep this one simple and really the whole point is to show how agents can call multiple other agents and how that's more efficient and more scalable but right now let's really quickly look at one of these nodes so for a send email we need to know who it's going to go to what the subject is and what the message is going to say so once again the query is going to come through with something like can you email Nate herk reminding him to bring the presentation material for our meeting today so now these these from AI functions are going to be figuring out okay from that query we're going to find the email address and then that's how we're going to fill in the two we're going to we're going to figure out what the message is going to say and then we're going to make a subject and put it here and then finally we're going to actually make the email message and put it in right here email body which is the body message of the email so like I said I'm amazed that they've added this kind of stuff it's super cool that you can sort of bake in like an open AI node within each parameter it's super cool but let's just pull up Telegram and test out this agent all right we're going to send off can you email Nate herk and ask him how the project is coming along we'll send that off it's going to think about it it should be hitting the contacts database to get Nate herk's email and then it's going to go back to the email agent the email agent's currently deciding which tool it's going to use and then it should send us off the email and then let us know so I've sent an email to Nate herk asking for an update on the project let's go check our email and see what that one looks like okay that email just came through the subject is project status update hi Nate I hope this message finds you well I wanted to check in and see how the project is coming along could you please provide an update at your earliest convenience thank you best regards Nate so with very minimal prompting we were able to have it send a very you know it's formatted like an email it signs off it has line breaks and that stuff is awesome and like I said within this email agent I hardly even proed this thing all I did was say if a number of emails isn't specified just assume it will be five for you'll see that in the next tool but then I also just said when sending an email always sign it off from Nate never includes something like square brackets your name so obviously I want to build on this agent I want to UPG upgrade the prompting I want to start to give each agent more tools but I really wanted to get this video out so you guys could see how to start playing around with sort of very custom AI agent Frameworks so the next tool that this agent has is get messages as you can see it's going to be looking for messages from a specific sender so that will be specified based on the query and then it's going to figure out how many messages to get so that's why in The Prompt I said if a limit isn't specified just grab five all right the trigger is list for us again we're going to say can you please get my emails from Michael Scott and this one should check the contact database to understand who Michael Scott is what that email is so then it can tell the email agent that we're looking for emails from this specific address looks like it's working through to do that right now in the back end and then we should get a success message here and we should get our messages from Michael Scott summarized in telegram so that just came through here are the emails from Michael Scott which is upat digital gmail. com we've got lunch this weekend it's going to give us a date and content um we've got the subject project Rhino it's going to say a reminder about your meeting with him tomorrow don't forget to bring note cards in the poster and then the third one is Project Panda um reminder that the project must be completed by 2025 to avoid any consequences so super cool way to get emails quickly summarized from a specific person all right moving on to the third agent that this personal assistant has access to is the research agent let's take a look at what this one is doing same format in the sense that it's getting called by the agent so it's triggered like that the research agent we gave it a very brief prompt basically just saying your research agent you have Wikipedia Hacker News and Sur API to answer the question first search Wikipedia if you can't find it there then look through Hacker News and then if you can't find it there use Sur API so that's just sort of the flow that we wanted to go through and then finally if there's an error it's going to tell the agent to try again and if it's a success then it's going to Output the information that we wanted okay so for the first one let's try just saying can you find out some recent news about open AI let's hit that off it's going to talk to the brain go to the research agent the research agent right now is figuring out which are the tools that it's going to be able to use in order to answer our question and any second now it should be going back to the AI chat model which will go back to the agent and give us our answer so as you can see we just got some recent news about open aai open ai's board has fired Sam Alman the board of open a announced the dismissal of Sam Alton from a CEO position each of these has links to read more which is pretty cool um let's look at this last one open ai's whisper search or sorry open AI whisper speech recogn they've released whisper which is an open source speeech recognition model showcasing showcasing their advancements in AI technology we could click on read more and we could open up um the specific article that it was able to find so let's go into the research agent look at the executions and then see which tool it ended up using in order to give us that answer okay looks like this time it was able to come through the prompt was recent news about open aai it hit the agent it figured out that it was going to go to Hacker News in order to get recent articles for us and then in the output we got sort of of like a summarization about those articles another very simple use case but let's just say we're asking what is Tesla I imagine this one will go to Wikipedia since it's something more basic but right now it's hitting the research agent the agent's thinking about which tool it's going to use and I'll be back in a sec when we get the answer okay looks like we just got the answer Tesla most commonly refers to nicoa Tesla a Serbian American engineer Tesla Inc or Tesla a unit of magnetic flux density in the International System of Units so that's kind of interesting um Tesla Inc is related to vehicles and sustainable energy okay so that was an interesting response I wonder um which one that this one went through so let's give this a second to update right here we got the newest execution so this one just did Wikipedia so that's pretty cool I imagine the search criteria was what is Tesla so it pretty much just searched Wikipedia and gave us three different answers of what Tesla is all right and for this third one I'm going to say can you find Apple's most recent earnings hopefully this one will hit Sur API we will see um but it's pretty cool to see that you don't actually have to be using credits and Sur API in order to get some of your questions answered like I kind of thought that Tesla one you know with the answer that it gave I thought that was pretty complex but let's see right now it is hitting the research agent it's going to hit the brain summarize the information that we're getting which is the chat model and then it's going to go back to the agent and then respond to us in telegram all right looks like this one's about to finish up there we go Apple's most recent earnings highlights for 2024 second quarter reported a profit of 23.

6 billion revenue of 90. 8 billion third quarter profit was 21.