Every morning: check Twitter for what dropped overnight, open The Verge, check Anthropic's blog, OpenAI's blog, go through a couple of newsletters, maybe catch a YouTube video from Andrej Karpathy or AI Explained if I had time. None of it was in one place. I was spending 45 minutes just catching up before I could think about anything else.
So I built AIWire.
It is a free, real time AI news aggregator. One feed, 20+ handpicked sources, updates every 30 minutes. free, no algorithm deciding what you see, no ads. Just the latest from sources I actually trust.
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What I was trying to solve
The problem wasn't that good AI coverage and news doesn't exist. It's everywhere. The problem is that it's scattered. You have to know which sources are worth checking, remember to check them, and then piece together the picture yourself. That's a lot of cognitive load before you've even read anything.
AIWire doesn't summarize or edit articles. It just puts everything in one place and lets you decide what matters.
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Sources it pulls from:
- Labs: OpenAI, Anthropic, Google DeepMind, Meta AI, Microsoft AI
- Media: MIT Technology Review, The Verge, TechCrunch, VentureBeat, Ars Technica
- YouTube: Andrej Karpathy, AI Explained, Two Minute Papers
- Newsletters: The Batch, ImportAI, TLDR AI, Ben's Bites
Full list at aiwire.app/sources
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What I learned building it
Source curation is harder than it sounds. The temptation is to add more sources to look comprehensive. The smarter decision is staying strict: only sources that consistently publish signal over noise. A feed with 50 sources that includes 30 mediocre ones is worse than a feed with 20 good ones.
Where it is now
Over the last few weeks, I added more sources, which include The Innermost Loop and AI explained. Last week, I launched a weekly newsletter: 5 stories that mattered this week, with a short breakdown of why each one matters. Not just headlines, but with context. Takes about 5 minutes to read, and you're caught up.
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Honest question
What sources do you think are missing? And for those of you who already have a routine for following AI news, what would actually make something like this worth adding to it?
Genuinely curious. Building in public means the product gets better when people are honest about what's wrong with it.
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