Show HN: AccInt – a Work Model for AI coding agents
摘要
该项目以猎头招聘为案例，演示了 AI 代理如何执行候选人筛选、背景调查、个性化沟通及 ATS 更新等任务。AccInt 强调“推理每一步”，在关键节点（如发送信息）需人工确认，并能从历史运行中学习偏好（如特定发送时间的效果、候选人对技术内容的偏好），从而在后续运行中实现自动复用。
荐读理由
借鉴其“工作模型”架构，通过“验证回放”与“显式约束学习”机制，将你开发的 AI Agent 从不可控的自动运行转向可验证、可复用的专业级工程交付。
原文
you · agency recruiting · monday 08:35“Run the staff-platform-engineer search — my name is on every message, so quality only.”
RUN 1week one
08:42find47 engineers match — your ATS first, then GitHub + conference talksVERIFIED
08:58reada “why now” per person — repos, talks, job changesVERIFIED
09:16refuse“blast 400 InMails” — consent floor: 11 named people, never a listREFUSED
09:34draft11 first-touches — the Kestrel Labs one opens with her k8s-migration postmortemHELD → your OK
09:55send11/11 sent from your seat — each confirmed deliveredVERIFIED
10:07keepATS true: stage, source, next step — per candidateVERIFIED
41 min · every step reasoned
9 weeks later
RUN 9week nine
08:09replaythe sourcing pass — 5 verified steps from runs 1–8, ATS + GitHub re-checkedREPLAYED
08:12skipArclight’s staff eng: “happy till my March vest” in run 5 — re-engage thenKNOWN
08:14draft6 touches — both re-engages cite what changed since you last spokeHELD → your OK
08:17send6/6 + ATS true — the sourcing pass was verified replayVERIFIED
10:07filetwo submittals out to the client — a fee rides on eachVERIFIED
week nine: the Work Model paying out — 6 min of decisions, the rest verified replay
what it now knows about your world
run 2learnedseniors reply to postmortems, not perksCREDITED
run 4learnedthu 08–10 sends = 2.1× responseCREDITED
run 5learned“blast it” stays refused — named people onlyCREDITED
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