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Show HN: I Built an Agent That Writes Fresh Newsletters for Any Topic
5 points by Arindam1729 33 days ago | hide | past | favorite | 3 comments
Recently, I was exploring the idea of using AI agents for real-time research and content generation.

To put that into practice, I thought why not try solving a problem I run into often? Creating high-quality, up-to-date newsletters without spending hours manually researching.

So I built a simple AI-powered Newsletter Agent that automatically researches a topic and generates a well-structured newsletter using the latest info from the web.

Here's what I used:

- Firecrawl Search API for real-time web scraping and content discovery - Nebius AI models for fast + cheap inference - Agno as the Agent Framework - Streamlit for the UI (It's easier for me)

The project isn’t overly complex, I’ve kept it lightweight and modular, but it’s a great way to explore how agents can automate research + content workflows.

If you're curious, I put together a walkthrough showing exactly how it works: https://www.youtube.com/watch?v=iDYnR_MlErg

And the full code is available here if you want to build on top of it: https://github.com/Arindam200/awesome-ai-apps/tree/main/simp...

Would love to hear how others are using AI for content creation or research. Also open to feedback or feature suggestions might add multi-topic newsletters next!




I would not subscribe to any newsletter written with AI. Why would I do that? The "content" so generated is almost by definition average or median. It will also be nothing new, by definition, but instead a rehash of other material the model's been trained on.

Now that I think about it, any organization or entity that makes a newsletter with AI/LLMs is probably creating "content" just to fill up space, for SEO purposes or some such not-even-nefarious, but rather dull and boring, reason. I'd probably ignore their newsletter and "content" accordingly.


Curious to know why you chose Agno? I've used Langchain previously. Any specific reason for that?


I was recently exploring it, and it was pretty easy to start and implement.

That was one of the reasons for using Agno




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