On a Time Crunch but Still Want to Learn to Develop Multi-Agent AI?

These 3 starter projects only take a weekend (and a few cups of coffee, maybe)

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Talk of the town: AI agents will replace SAAS.

This wasn’t a random statement made by any drug dealer. It was Satya Nadella, the CEO of Microsoft, saying this.

If you’re a developer or anyone in tech, you’d want to know how to build AI agents yourself. But not many of us can afford the time to learn them from scratch.

I’m writing this for you if you find yourself in this group.

This is also how I learned to develop AI apps — but more informally. Therefore, I wanted to organize it in a post so that you can follow along nicely and use your weekend to learn the basics of developing AI-powered apps.

I started this post with a reference to AI agents. I will get to that.

But before that, we should get our feet wet on LLMs. Don’t worry—this isn’t a very theoretical post. We will first build an app that uses LLM only. Then, we will build a retrieval-augmented app (RAG). Lastly, we will build a real agentic app.

You may have some knowledge of Gen AI tools. So feel free to skip to your desired project.

The Most Valuable LLM Dev Skill is Easy to Learn, But Costly to Practice.

What you need …

As I mentioned, this won’t take over a weekend to finish. But besides time, you need a few other things.

First, I assume you’re good at programming (Python) and have experience developing something. (Your pet projects and homework count in, too)

We will be using Python frameworks like Streamlit, Lanchain, and Phidata.

You need an active internet connection because we’ll use OpenAI models through their APIs. Oh, this also means you need an active OpenAI API key.

Your PC should be compatible with and capable of running vector stores like Chroma. Most…