Okay, let's recap what we learned so far. We talked about how tools are such a key part of agents, because they are what allow you to connect your agents to the external world. So you're going to view tools and use existing tools to call APIs to integrate with our internal systems, to do some computational. It's a translation layer that allows your agents to communicate with existing programs that you might have. But in order for these tools to work properly, you need to make sure they're versatile. You need to make sure they're fault tolerant and need to make sure that they have a caching strategy. If you make sure that you're using those three qualities on all the tools that you use, you then have a system that is more reliable. So make sure to watch out for that when you're choosing what tools are going to use or building our own tools. Keep in mind again that because are using crewAI, you can not only use the tools that crewAI offers itself, but you can also use all the tools that LangChain offers. So you have a huge range of tools that you can start with. All right. We're going to wrap this lesson here. You're doing amazing. Keep at it. You're going to love our next lesson because you're going to talk about even more interesting stuff that is going to unlock more use cases. So I'll see you on your next lesson.
Multi AI Agent Systems with crewAI
- Introduction
- Overview
- AI Agents
- Create agents to research and write an article (code)
- Key elements of AI agents
- Multi agent customer support automation (code)
- Mental framework for agent creation
- Key elements of agent tools
- Tools for a customer outreach campaign (code)
- Recap of tools
- Key elements of well defined tasks
- Automate event planning (code)
- Recap on tasks
- Multi agent collaboration
- Mutli agent collaboration for financial analysis (code)
- Build a crew to trailor job applications (code)
- Next steps with AI agent systems
- Conclusion
- How to get your completion badge