GitDate

What it does

Unlike resume-heavy platforms, our launch merges GitDate’s real-time activity matching with GitHire’s automated vetting. We stand out by replacing static profiles with verified GitHub signals (code complexity, not just commits) and voice-based pre-screening. Candidates call a 10-digit Job ID to pitch their fit, instantly filtering for communication and technical depth. It’s the first bidirectional tool where "proof of work" meets automated human assessment.

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  GitHiredDec 2025 · ▲360

  Find your next 10x Engineer by proof of work, not keywords

• IM
  I made a tool that made me faster at Git2018 · github.com · ▲551
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  GitHiredMay 2026 · githired.tech · ▲251

  Find 100x engineers by proof of work, not resume keywords

• GW
  "Git who" – A new CLI tool for industrial-scale Git blaming2025 · github.com · ▲252

  I've always wanted a better way to explore the authorship data embedded in a Git commit log. I'm having fun building a CLI tool to do this. It's a bit like the "Contributors" tab on Github that shows you how many commits each contributor has made but much faster and with many more options. If you get a chance to try it out, please let me know. I'd love to hear feedback and suggestions. Thank you!

• IB
  I built a tool to find devs based on code, not LinkedIn titles2025 · gitmatcher.com · ▲86

  Hey HN After years working in software engineering and helping with hiring, I noticed a frustrating pattern: Companies often rely on résumés and LinkedIn titles to find developers instead of looking at what they've actually built. So I built GitMatcher. It analyzes GitHub profiles to surface developers based on: Their public repos Commit history Originality and usefulness of code Patterns that show consistency and real skill No keywords. No job titles. Just code. GitMatcher is useful if you're: - A recruiter tired of resume roulette - A founder looking for a technical co-founder - An OSS…

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• NW
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  Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…

  Life & fun · May 2026 · github.com

• FM
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