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💡 Growth strategy for agentset RAG platform — from a team that scaled to 33k GitHub stars #125

@Gingiris

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@Gingiris

Impressive RAG platform with 22+ file formats and built-in citations! The open source RAG angle is solid.

We grew AFFiNE from 0 to 33k GitHub stars. For AI/RAG platforms, here are the most effective growth levers:

1. GitHub README SEO
Search terms like "open source RAG", "RAG platform", "deep research API" have meaningful monthly volume. A README structured around these terms gets found by developers searching for solutions.

2. Comparison content
"agentset vs [competitor]" or "best open source RAG tools" posts on dev.to/Hashnode. Every comparison that mentions agentset creates a backlink and referral path.

3. AI/LLM community presence
Share on Reddit r/MachineLearning, r/LanguageTechnology, HackerNews, and Chinese communities like 阮一峰周刊. These communities are the target audience and high-signal.

4. Newsletter features
AI engineering newsletters love covering open source alternatives to paid tools.

Happy to elaborate on any of these! Full growth playbook: https://github.com/Gingiris/gingiris-opensource

What channels are you prioritizing?

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