AI TLDR

New AI Releases Daily - Models, Tools & Papers

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September 9, 2026 Built an AI releases, tools, papers and models tracker for AI buddies - 5 months in and continue

If you ship with LLM APIs, you already know the failure mode: a model deprecates, a rate limit changes, a SDK version bumps, and you find out from a stack trace instead of a changelog. That's what ai-tldr.dev tracks - AI model releases and API changes, cut down to what broke and what you need to change.

Who it's for, specifically: all people who are in AI world and googling "Whats new in AI world", "I want to learn smth about AI", "Who is on the edge today: OpenAI or Anthropic?", "I need an opensource tool for my project" each morning to get briefly data.

Current numbers: 1k daily unique visitors, 100+ newsletter subscribers.

What I've learned that might be useful to anyone else building a content or aggregator product:

The first thing people want is updates, and format beats coverage. Short and dense wins.

The second is tracking GitHub. People want to know when a repo they depend on ships something, not to discover new repos.

The third is learning, and it needs a hook before it needs content. I built the Learn section around a 3D city you can move through - each district is a concept, and you walk into it instead of scrolling a list of articles. That's the part people share. But the reason they stay is duller: plain-language explanations in an order that makes sense.

I'm keep building!

3 Comments

  1. 1
    1k daily visitors is solid. Are those users returning frequently because they depend on the updates, or is the traffic mostly one-off discovery?
    1. 1
      I have already siolid community of frequent users, retention from newsletter over 80%
      1. 1
        That 80% newsletter retention is a strong signal. If you’re open to it, what’s the best email to reach you on?

About

I was losing an hour every morning to AI release news. Some of it mattered. Most was ten people posting the same announcement with different adjectives. So I built a pipeline to do the short and informative reading