Forget CrewAI & AutoGen, Build CUSTOM AI Agents!

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If you are developing AI agents or multi-agent workflows, it is often better to create your own custom agents rather than relying on existing frameworks like CrewAI or Autogen. In this guide, I will demonstrate how I developed a simple custom web search agent in Python and explain why custom solutions are superior to the current one-size-fits-all frameworks available.

Chapters
Introduction: 00:00
Agent Architecture: 01:10
Python Code Walkthrough - Setup: 04:50
Python Code Walkthrough - Prompts: 06:55
Python Code Walkthrough – Web Search Tool: 11:15
Python Code Walkthrough - Agent: 21:08
Testing the Custom Agent: 28:48
Why Build Custom: 38:15
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I have used AutoGen, CrewAI and other tools. Honestly, they are not production ready. They are over engineered. What I've learned from building my own tools will be very useful for the future. Learn as much as you can building your own tools, its a lot simpler than most people think, just give it a shot.

rodrigoamora
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We need a framework that is very easy to use that is very clear qnd well documented. Right now unless you are a very very experienced dev its is hard to understand these frameworks. I now build my own functions from scratch (loaders, memory, tools) and just reuse them between projects. For one it helps me understand my code fully and know where to debug. Ive tossed the idea around of building a repo of LLM-related objects that are modular and that anyone can use and understand and customize further as they like.

matten_zero
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This makes the most sense I've seen on the subject in a long time.

darwinprod
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So many on my channel and my live streams have also indicated this frustration with the agent frameworks. The function calling in ollama is pretty rock solid but many frameworks have problems with it so that’s frustrating too. Thanks for putting this video together.

technovangelist
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Dude I've come to the same conclusion like in the last week. The timing for this is on point.

freedtmg
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This is so so good! I'm so into these agentic workflows myself, it's really cool to see how other people go about connecting things up

arinco
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What a delight it was to discover your channel! You speak clearly and provide details at a pace that is easy to understand. Great job unpacking popular agent frameworks and custom agents. Excellent video, presentation, and materials. Thanks!

donconkey
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Very Practical Approach. CrewAI is a distraction at the moment when people can spend less time and money just learning api and function calls

CustomGPT.AIAcademy
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Your conclusion matches my experience in every point spot on! Well put into words.

danielpaurat
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Thank you so much for this video!!❤❤❤. This is exactly what I was looking for. I will definitely check this out and see what results I get!

RayWrightRayrite
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Thanks for creating an alternative to using these tools. And keep creating great content!

sobukwelu
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I like your take regarding customization. I also felt that the moment you start customizing the mentioned frameworks it is a bit a hassle since you get constrained by their pre-defined workflow structure. I decided to make prototypes with langchain since it is more modular and has lots of features that works more like building blocks than a framework. Great content, cheers.

yt-caio
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Wow. Thanks for making this code available, my man! Great stuff.

taylormcclenny
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Thank you, my brother, for sharing your knowledge. This video is very helpful for me because I'm creating a new feature and I'll use agents to accomplish my needs. This video provides me with many insights.

robsoncoutinhoti
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Exactly.
Autogen - you have to put the agent interaction logic in the prompt.
CrewAI lets you properly create a workflow, but it just is not how I would do it.

That is kind of what I worked on this week. I'd made a decision to use LangGraph, and well...

Thanks for showing me your ideas :)

JohnBoen
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Man, you are dropping gems! Thanks for posting and sharing amazing content and tips.

MrAhsan
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Fantastic work here this is massive to see the process!

TheFocusedCoder
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Woooo great work datacentric. Following from my last comment on the previous video my idea of narrowing the problem space was correct. Also my predictions for Open AI's GTP4o release 😅. Time to build some custom optimised agentic workflows 🎉🥳

ARCAEDX
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Thanks a lot for that information. that was the question I was looking for an answer for. Wish you the best!

fullstackpedro
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Great rationalization and analysis. There's always pros and cons for both approaches. It's the convenience and quick ramp-up vs performance and targeted implementation. Would be great if you can somehow come up with a hybrid approach, i.e. just enough of a generic framework to ramp up but customize areas requiring more performance. Looking forward to your evaluation of AutoGen customization.

Bana