Hacker News

Article URL: https://www.reuters.com/world/middle-east/amazon-cloud-unit-flags-issues-bahrain-uae-data-centers-amid-iran-strikes-2026-03-02/

Comments URL: https://news.ycombinator.com/item?id=47223331

Points: 1

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Article URL: https://www.bbc.co.uk/news/articles/cj4zlnezrl7o

Comments URL: https://news.ycombinator.com/item?id=47223330

Points: 1

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About 6 years ago I wrote a blog post [0] with some ideas on how to help popular open source maintainers deal with all the noise on Github. Patted myself in the back and never did anything about it :)

There's recently been a lot more discussion around this due to AI, so I've built a simple tool called "Slop Meter" [1]. It gives maintainers a quick snapshot of the user's history in open source:

1) Do they just open issues and expect you to do everything, or will they put in the work to fix the problems and open a PR? What's the issues : PR ratio? 2) If they do contribute, what percentage of their PRs actually gets merged?

I feel like these are the two most important signals when triaging what to pay attention to in open source.

You can install this on any Github repo and it will automatically post a comment with the stats. We do not run this on maintainers or existing contributors.

You can also go on the web and look up a Github profile; it will take a minute or so to import depending on how much public data they have (maybe longer if this makes the front page...).

Example profile: https://slopmeter.kernellabs.ai/u/mitchellh

If you are an OSS maintainer, I'd love to hear any feedback.

[0] https://www.alessiofanelli.com/posts/how-can-we-help-oss-mai... [1] https://slopmeter.kernellabs.ai/

Comments URL: https://news.ycombinator.com/item?id=47223316

Points: 2

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Article URL: https://github.com/marketclaw-tech/marketclaw

Comments URL: https://news.ycombinator.com/item?id=47223301

Points: 1

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Article URL: https://secondthoughts.ai/p/45-thoughts-about-agents

Comments URL: https://news.ycombinator.com/item?id=47223299

Points: 2

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Article URL: https://www.pipulse.dev

Comments URL: https://news.ycombinator.com/item?id=47222619

Points: 1

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Article URL: https://we-make-money-not-art.com/we-the-bacteria-notes-toward-biotic-architecture/

Comments URL: https://news.ycombinator.com/item?id=47222599

Points: 1

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I've been running multiple AI coding agents in parallel on the same repo. The agents code fine. The problem is managing multiple parallel sessions with git. Multiple agents, one branch, one overwrites the other.

Git worktrees give isolation but the per-session setup/teardown doesn't scale. GitButler looked promising but testing each agent's changes in isolation was tedious. Neither was built for this workflow.

git-stint automates the full lifecycle. Each agent session gets its own branch and worktree automatically. WIP auto-commits on exit or crash. Full diff, squash, and PR workflow for review. Conflicts caught before merge. Main stays clean.

Zero runtime deps. npm install -g git-stint. Built for Claude Code's hook system but works with any AI tool that writes to a git repo.

Been using it daily across my own projects. Would love feedback on the approach.

Comments URL: https://news.ycombinator.com/item?id=47222581

Points: 1

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Article URL: https://arstechnica.com/tech-policy/2026/03/fcc-lets-charter-buy-cox-says-no-reason-to-worry-about-higher-internet-prices/

Comments URL: https://news.ycombinator.com/item?id=47222578

Points: 1

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Article URL: https://mudita.com/products/phones/mudita-kompakt/

Comments URL: https://news.ycombinator.com/item?id=47222569

Points: 1

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Article URL: https://minutes.substack.com/p/civis-romanus-sum

Comments URL: https://news.ycombinator.com/item?id=47222556

Points: 1

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Article URL: http://CTORank.com

Comments URL: https://news.ycombinator.com/item?id=47222543

Points: 1

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If you'd like to learn about how I corralled the agents to do this, check out this blog post https://vers.sh/blog/elixir-webassembly-billion-tokens

And, of course, here's the GitHub https://github.com/hdresearch/firebird

I also posted a thread to Twitter where I ship nifty stuff if fun uses of technology is interesting to you https://x.com/itisyev/status/2028543436388016510

Comments URL: https://news.ycombinator.com/item?id=47222540

Points: 1

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If you'd like to learn about what Elixir and WebAssembly are or why even integrate the two together, check out this blog post https://yev.bar/firebird

And, of course, here's the GitHub https://github.com/hdresearch/firebird

I also posted a thread to Twitter where I ship nifty stuff if fun uses of technology is interesting to you https://x.com/itisyev/status/2028543436388016510

Comments URL: https://news.ycombinator.com/item?id=47222519

Points: 1

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Article URL: https://github.com/NikitaDmitrieff/feedback-chat

Comments URL: https://news.ycombinator.com/item?id=47222513

Points: 1

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Article URL: https://react.design/

Comments URL: https://news.ycombinator.com/item?id=47222509

Points: 1

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After Fakespot shut down in July 2025, I built FakeScan as a free alternative. It uses AI (Llama 3.3 70B) to analyze Amazon product reviews and detect fake/manipulated ones.

How it works: paste any Amazon product URL, and it analyzes review patterns, sentiment distribution, reviewer behavior, and linguistic markers to give you a trust score and detailed breakdown.

No signup required - just paste a URL and get results. Built with Next.js, running on Groq for fast inference.

Would love feedback from the HN community on the analysis methodology and UX.

Comments URL: https://news.ycombinator.com/item?id=47222497

Points: 1

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Article URL: https://daniellombrana.es/blog/2026/03/01/claude-improved-my-keyboard-firmware

Comments URL: https://news.ycombinator.com/item?id=47222494

Points: 1

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Article URL: https://www.paulweiss.com/insights/client-memos/sdny-court-considers-whether-ai-generated-documents-are-subject-to-privilege-protections

Comments URL: https://news.ycombinator.com/item?id=47222493

Points: 2

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Article URL: https://simpleflying.com/delta-air-lines-blended-winglets-no-more/

Comments URL: https://news.ycombinator.com/item?id=47222488

Points: 1

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