Let me share some experience about the agentic AI trainings I completed on Linkedin:

• Hands-on AI: Implementing Agentic Systems
  This one-hour course is very fast. Starts with a high level overview about agents and frameworks, touches on some security aspects, and then jumps into showing actual agentic AI apps using Python and CrewAI.

  The course gives you a glimpse of how the source code looks: most of the application consits of prompts in a yaml format, defining a 'crew' of AI agents, and then very little and generic code invoking CrewAI based on this yaml. The course does not explain how the code works line by line, and you will have trouble following it unless you know what to expect. It also shows cools examples of how all this can fail: in one case when the tool had no access to source data, the AI tool decided to make up some realistic looking source data itself.

  If you want an intro on how an agentic AI ecosystem 'feels', this course can be useful. If you want to learn how to create such an app, then this is not for you.

• Creating Agents with CrewAI
  This course teaches you step by step how to write agentic AI based apps using Python and CrewAI, it takes two and a half hours. It is very hands on, jumps right into doing stuff.

  The course explains how you can install CrewAI and fire up your environment. It uses OpenAI but also gives guidance on how to make other platforms work. (You need to purchase credits to use OpenAI via APIs, but Gemini has a free tier; I could make the latter work with rather little effort.) The course explains concepts behind CrewAI and teaches you what you can customize and how. It builds a couple of applications, walking through each steps of the process. It does the kind of babysitting I was looking for.

I find frameworks like CrewAI rather useful; they allow you to write code fully independent of the AI platform you use (OpenAI, Gemini, Claude, etc). It also orchestrates how you call the LLM, helps you glue your prompts together and extract results. Not rocket science, but very a handy tool.

This post was first published on Linkedin here on 2025-10-19.