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[ARTICLE · art-52266] src=dev.to ↗ pub= topic=developer-tools verified=true sentiment=↑ positive

Save yourself from drowning

A developer built and open-sourced an internal tool called Dev.to ASSISTANT that uses a Gemma 4 layer to summarize Dev.to posts by tag, extracting key details like project purpose, tools used, and engagement metrics. The tool aims to help builders quickly find high-value projects without scrolling through lengthy posts. The backend uses Python (FastAPI) and the frontend uses Next.js, with the entire project available on GitHub.

read2 min views4 publishedJul 9, 2026

Dev.to is an absolute goldmine. On any given day, thousands of builders are sharing brilliant engineering lessons, launching side projects, breaking down new AI models, or submitting clever hackathon entries.

The problem is that this massive amount of information is hard to process. When a new tech challenge or hashtag trends, it is difficult to find the best work.

We want to support fellow builders, but nobody has the time to click through fifty long posts just to see what someone built and how they built it.

I wanted a simple way to find high-value projects without spending my entire evening scrolling. So, I vibe-coded an internal tool called Dev.to ASSISTANT and decided to open-source it.

Instead of explaining it, here is the tool turning the noise into a clean, structured summary in real-time:

The goal isn't to skip reading—it's to figure out exactly where to dive deep.

When you pass the assistant a tag (like #weekendchallenge

or #ai

), it uses a Gemma 4 layer to extract the meat of each post. You instantly get:

The exact "why" and "how" behind the project, stripped of fluff.

What tools, frameworks, or models were used.

Live reaction and comment counts so you can see what's sparking conversation.

A link right back to the original Dev.to post so you can jump in and engage with the author.

Because Dev.to is an open ecosystem that generously provides an official API, I wanted to build this in that exact same spirit.

The backend is built with Python (FastAPI) and the frontend dashboard uses Next.js. I’ve made the entire project completely open-source so any builder can run it locally, tweak the filters, or add new curation features.

If you want to discover great engineering lessons faster, track challenge submissions, or just find amazing people to follow without getting lost in the feed, give it a spin.

[Check out the GitHub repository here](https://github.com/siddqamar/dev.to-assistant) ⭐️

If this tool helps you find a cool repository or saves you some scroll time, I’d love to hear your thoughts in the comments below!
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