Welcome to AstroKobi
A hand-written seed post so the blog isn't empty on first build. Every post after this one is generated by the pipeline described on the About page.
This post is the one exception to the rule: a human wrote it. Everything that follows on this site is generated by a pipeline that runs every hour, reads what's trending across the web in space and astronomy, and writes a structured MDX post about whichever story scores highest. It's an experiment in what a small, opinionated automation can produce without turning into slop.
What happened
The pipeline went live today. It pulls from space and astronomy communities on Reddit, Hacker News, DEV.to, dedicated RSS feeds, YouTube, Brave News, and Google Trends, scores each candidate on popularity, engagement, and recency, picks a winner that hasn't already been covered, researches it, and hands the bundle to a large language model with a strict MDX contract.
Why it matters
Most automated blogs are indistinguishable from SEO spam because they're built to maximize volume. This one is built to maximize signal — a steady stream of clearly sourced posts with a consistent structure that makes them easy to skim. The goal isn't to replace reporting from NASA, ESA, or the people who actually point the telescopes. The goal is to produce a readable brief on what's happening in the cosmos, updated as it happens.
- Near-zero monthly cost on the free tiers of everything involved.
- Strict MDX structure means every post is skimmable in under a minute.
- Every source is linked — easy to verify or go deeper.
- No human review means occasional factual mistakes will slip through.
- The pipeline can only cover what the public APIs surface.
- Coverage is skewed toward what's already popular, not necessarily what's most important.
How to think about it
Treat AstroKobi as a synthesized summary, not as primary reporting. If a post catches your attention, click through to the sources. The value here is the synthesis and the consistent shape — not the authority.
FAQ
Who writes these posts?+
A large language model, given scraped articles and a rigid MDX template. The pipeline selects the topic; the model writes the prose; a human reviews nothing before publishing. See the About page for the full flow.
How accurate is any of this?+
It's as accurate as the sources it's reading. The model can still misread or over-generalize, so treat specific numbers and quotes skeptically and click through to the sources if a detail matters.
Can I suggest or block topics?+
Not today. The selection is driven entirely by cross-source scoring. The repo is public, though — if you want to fork it and run your own version, that's the best path.
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