How I’m Building and Using AI Agents in Full Stack Apps

AI agents are powerful tools. 

They can perform specific tasks within your apps with insane efficiency.

But, how simple is it to actually build and integrate them? And what’s the best approach to making these agents part of your full-stack apps?

This week, I spent most of my time into building such AI agents from scratch and using them in creating scalable, full-stack apps.

( like this ⬇︎ )

What I’m Using to Build Apps Fast ⚡️ 

To speed up app development, I rely on Databutton. It does the job fast (and builds scalable apps), and we are making Databutton the best AI App Builder.

So, Databutton uses Python (via FastAPI routers) for backend creation.

That means, easy access to any Python libraries to create APIs.

Once the backend is done, it’s all about integrating it with a frontend.

Here, Databutton generates React code for the UI (plus the perks of shadcn ui which makes it look extra cool), making the whole process efficient and smooth.

Plus, once click deployment to push it live 🚀 

How I’m Building AI Agents 🤖 

For building agents, honestly I’ve found phidata’s Python package incredibly intuitive with its clean, straightforward syntax.

For those of you who like getting hands-on, here’s how easy it is to code an agent.

But, I admit, I often let AI write much of the code for me! Why not ?!

# Import Relevant modules
from phi.agent import Agent

# Agents having accessing to tools
from phi.tools.youtube_tools import YouTubeTools

# Initialize YouTube agent
agent = Agent(tools=[YouTubeTools()],
            show_tool_calls=False,
            description="You are a YouTube agent. Obtain the     captions of a YouTube video and answer questions. Provide concise, focused answers and use markdown formatting for better readability."
        )

# Get agent's response
response = agent.run(prompt)        

If you’re curious, check out my recent Youtube videos where I walk through creating these agents.

In fact, I even went a step further in my very first live-stream—I ended up building a whole team of AI agents! 🫡 

It was exciting to see how doable it is to create full backend systems with AI, right on the spot with phidata and spin a full stack app with Databutton.

Why I’m Loving Live Streaming 🖤

Live streamings = lowest effort, highest-transparency video format out there! 🌻 

The decision to live stream was spontaneous, but I learned a lot from the experience.

(Not gonna lie, I was super nervous at first, but it got better as the video progressed!)

Here’s why I think live streams might just be the best format for creators:

• 📈 Visibility boost: Live streams get better reach than regular posts (hello, views!)
  

• 🔁 Engagement potential: If your audience catches the stream, engagement can really build up ( I got couple of questions in my first live stream, and I engaged right there — super cool experience )
  

• ⏲️ Efficiency: No hours of scripting, recording, or editing—just go live, and you’re done!

That’s all from this week! 🙌 

If you know anyone interested in tech, AI, and the latest in app development, please forward this newsletter!