A demo of an AI assistant built with GPT-4.1 and Anthropic's Think tool orchestrates child agents to schedule a meeting with Dexter Morgan, cancel a dinner, and send confirmation emails. The Think tool acts as a scratchpad where the assistant verifies each step and confirms all requests were completed.
This is how Anthropic recommends to use a think tool for your AI agents. All right, so here is our beautiful Ultimate Assistant with the new GPT-4.1 chat model, as well as the new think tool. All right, can you please create an event for tonight, 7:00 PM? It'll be an hour long with Dexter Morgan. And can you send him an email to make sure that time works? Can you delete my dinner at 6:00 PM? And then can you email Michael Scott to let him know that I'm not gonna make it? Okay, cool. So we just sent that off. Our Ultimate Assistant is going to get that message, use GPT-4.1 in order to take action. And as you can see, it's gonna hit its different child agents down here. So it's using the contact agent to get that information, the email addresses. Now it's gonna hit calendar and email agent in order to delete that event, create the event, send off those two emails. And then as you can see, it just used its think tool down here to make sure that it did everything right. So the response that we got was, all set, your 7:00 PM meeting with Dexter Morgan has been scheduled and he's also been emailed. The 6:00 PM dinner has been deleted and Michael Scott has been notified that you can't make it. So before we go verify that, let's click into the Ultimate Assistant and and we'll look at its logs because this lets us see exactly how it thought about what it needed to do and what actions it took. So the first thing it did was contact agent to get Dexter Morgan's email, and then it did the same thing for Michael Scott. Then it went to the calendar agent to create an event tonight for 7:00 PM called meeting with Dexter Morgan. Then it went to the email agent to send Dexter an email to confirm if that works. It went to the calendar agent to delete the dinner. It went to the email agent to let Michael Scott know that we're not gonna make it to dinner. And then finally what it did is it used its think tool which is basically like a scratchpad for your agent to write down its thoughts and its actions and just to make sure that it's aligned with what you asked it to do. So what it wrote down here was confirmed that all requested actions were completed, created the meeting event for 7:00 PM with Dexter Morgan, emailed him to check if that time works, deleted the 6:00 PM dinner, and notified Michael Scott by email. No further steps needed unless the user requests more. So if at this point it realized, okay, I wrote down what I did and what the user wanted, oh, I actually do have more things I need to do, I'm gonna go back and call those tools until I'm ready to go. So this was perfect. It did its actions, it thought about it, and it decided that we were finished. And then it let us know all the things you just requested have been done. So looking at my calendar, you can see the 6:00 PM dinner was deleted and we now have a meeting with Dexter Morgan, and we can see that he was in fact invited. You can see here in our sent emails, we have a meeting time confirmation for Dexter and 7:00 PM. So I'm super excited to continue to experiment with this kind of stuff. When you pair a really nice model with the ability to basically write down its thoughts and reason, I think that this is going to be huge for creating agentic systems. If you wanna watch the full breakdown, the link for that will be down in the description, and I'll see you guys over there.
