Summary and next steps


With this chapter, we are reaching the finish line, the end of the Conversational AI Assistants with CALM course. This video series was intended to gave you a better understanding of how CALM operates and how the combination of strict business logic and the flexibility of LLMs empowers you to build better and more efficient enterprise-grade assistants much faster and much easier.

What you have learned

Throughout this course, we covered all of the key components of CALM. We looked into how we can define business logic, how we can add components like LLM-powered dialogue understanding, and more advanced features like enterprise search. This course also gave you a better understanding of how you can build conversational AI assistants with CALM in practice. By now, you should know how you can get started, how you can configure your development environment, and continue building your assistant by implementing flows, adding the necessary LLM-powered components, and most importantly, how you can run your assistant in a production environment.

Next steps

It is highly recommend to spend more time going through the documentation of Rasa Pro because it has all of the relevant information about all of the parameters and customizations that you can make when building your assistant. The documentation also comes with a number of follow-along guides that can be really useful when implementing specific components of your assistant. In addition to that, you should also check out the Rasa's blog to find more tutorials and interesting articles about CALM and the conversational AI field.

Most importantly, you can get necessary technical support on Rasa's developer forum.

Test your knowledge

After finishing this course, you should be ready to test your knowledge and become a certified Rasa Pro developer by taking the Rasa Pro Developer Certification.

2016-2024 © Rasa.