Langchain has been making lives of developers easy with their agent framework. Making AI agent is now lot easier due to agentic coding and the framework from langchain. By adding additional extensible frameworks you even more those agents powerful.
Take example of Google's Gen AI SDK which can be plugged with the Google ADK and Langchain. I recently tried the Langchain noticed how easy it is to build agent.
A lot of coding part is already being taken care of agentic coding. I decided to build use case based AI agents. Here's my video on how to build such simple AI agent with Langchain.
How did I made it?
I started by asking the Gemini on creating a simple ai agent. My goal was to give it Openrouter Key and the models. And from there onwards my goal was super specific.
Goal was to build an desktop assistant that can be used as an agent convo within command line. I didn't went for something fancy with web based chat wrapper.
This agent can be simple to use and you can chat like any other AI model. And forget which model is behind. So I try to make it simple to learn more about agents.
If you build agents then go with use case based agents. This way you learn how to use the AI agents in real life.
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