If you've spent five minutes on a news app in the last decade, you've been ranked. The feed isn't reverse-chronological; it's a model output. The model is trained on what made other people scroll, click, and rage-share. The natural endpoint of that loop is a feed that's optimized to make you keep using the app, not to inform you.
WeSearch goes the other way. Our home feed is deduplicated, source-diverse, and time-ordered. We pull from 700+ editorial RSS feeds — left, right, center, international, science, finance, tech — and merge them by recency, with simple deduplication when the same headline shows up across sources. There is no ML model picking which headline gets shown to you. There is no "Suggested for you." There is no "You might also like."
How it actually works
- Pull, don't predict. Every 5 minutes we pull a fresh batch from each subscribed feed.
- Merge by time. Stories sort by publish time, newest first. That's the whole sort.
- Dedupe by URL. Same headline from three wires? You see it once.
- Categories are honest. Each source's category comes from a static directory we maintain, not from semantic clustering. Tech is tech, World is world.
- Trending is opt-in. The 24-hour trending row counts community reactions, not engagement velocity. If you ignore it, your feed stays untouched.
What you give up
An algorithmic feed is, in some narrow sense, more efficient — it learns what you click and shows you more of that. The trade-off is that it builds a bubble around you, slowly, without telling you. WeSearch refuses that trade. You'll see headlines you wouldn't have clicked on. That's the point.
What you get
The same news a working journalist or analyst sees in their RSS reader, with deduplication done for you, comments and reactions added, anonymous identity included, and zero data harvested off the back. It's a community hub, not a personalization engine.
Browse by category, not algorithm
If you want to filter, do it manually. Each category page lists the most recent stories from every source in that bucket: world news, US news, politics, technology, science, business, markets, health, climate, AI, culture, media.
The longer argument
For a more complete argument about why we made this design choice, see why no algorithm. The short version is: engagement and informedness are not the same objective, and any feed optimized for the first will, at scale, undermine the second. We chose the second. Chronology is dumb on purpose.
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Frequently asked
What does 'no algorithm' actually mean?
The home feed is sorted by publish time, deduplicated by URL, identical for every reader. No ranking model, no engagement velocity boost, no personalization vector. You can filter by category, but the underlying sort is chronology.
What about the trending row?
Trending is a count of distinct anonymous reactions on a story over the past 24 hours. It is a count, not a model. There is no virality smoothing, no engagement-velocity prediction, no model output.