Show HN: Filter out engagement bait and politics on your X/Twitter feed
A browser extension that uses an LLM to hide engagement bait and political content from Twitter’s “For You” feed prompts debate over whether AI-powered filtering is a meaningful way to reclaim control over social media. Commenters weigh the benefits of algorithmic curation against its role in amplifying outrage, with some preferring tools like custom feeds, keyword muting, or RSS, and others arguing the only real solution is to leave Twitter entirely. Many see personalized, user-controlled filtering — whether via AI or built-in platform tools — as an inevitable response to information overload and manipulative engagement incentives.
Overview of the tool and reactions
- Browser extension uses an LLM (via Groq) to hide engagement bait and political content from X/Twitter feeds, mainly “For You”.
- Several commenters praise the concept and speed, and see it as an early example of AI-powered personal feed curation.
- Some want more granular controls (e.g., filter all posts about specific public figures, or certain topics) and real-time “mood” sliders.
- Others note that even humans struggle to define what counts as “bait,” so perfect automated classification is unrealistic.
Existing platform controls and alternatives
- Many argue that turning off “For You,” using only the “Following” tab, disabling retweets, and using lists already remove most low-quality content.
- Third-party extensions (e.g., “control panel” tools) are mentioned as effective for cleaning feeds without AI.
- Some use lists like an RSS reader, organized by topic, to minimize algorithmic influence.
Debate on staying vs leaving X/Twitter
- A vocal group says the healthiest solution is to leave entirely, deactivate accounts, and switch to RSS, blogs, Mastodon, Bluesky, etc.
- Others stay for network effects, real-time news, expert communities, or to share projects, while acknowledging rising toxicity and owner-driven enshittification.
- Some see X as no worse than legacy media and valuable if one can filter well; others highlight overconfidence in personal “discernment.”
Algorithmic feeds, propaganda, and truthfulness
- Several note that algorithms amplify outrage, politics, and war propaganda; balanced, nuanced content gets little traction.
- There is concern about misinformation around conflicts, and skepticism that community fact-checking mechanisms can work in polarized situations.
- Some argue platforms and their incentives—not just users—drive the most toxic patterns.
AI/LLMs as filters: promise and concerns
- Commenters see a broader future where AI filters overwhelming information streams, including social feeds, local news, and long videos.
- Others criticize this as wasteful: AI will both generate low-value content and then be used to summarize/filter it.
- Doubts are raised about LLMs inferring intent (e.g., whether something is deliberately engagement bait) and about reliance on remote APIs vs. local models.