Original Summary

For the last year I've had AI coding agents working on real repos, and I kept hitting the same failure: the agent reports "done." Done is a completion claim. It says nothing about whether anything was actually verified did the tests run, did the repro fail before the fix and pass after, was that config edit even in scope? I built AdaptOrch to answer exactly those questions. You submit an agent run through MCP, a CLI, or a Python SDK, and you get back a hosted record: what ran, what was checked, and what's still open. It's the checklist you'd write in a PR review, except the machine writes it from evidence instead of from the agent's own summary. The design decision I'm most stubborn about: execution and verification are separate facts, everywhere. A skipped check is never reported as a pass. Hosted command verification is off by default, and upgrading your plan doesn't magically turn it on — the boundary is printed on the pricing page, not buried in docs. I don't want to become another AI tool that claims it verified things it never ran. Where this actually stands: Live hosted service. Free Starter tier: 50 runs/month, bring your own model key. Zero paying customers. This post is customer acquisition attempt #1, no point pretending otherwise. Actually running your repo's test commands needs a separately configured execution environment — that's a scoped conversation, not a signup button. Real question for people who review AI-written code: does this record format match the questions you already ask in review? What's missing from it? The homepage has an interactive walkthrough of the review format no signup needed to see it.   submitted by   /u/DMAE1133 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/13 21:50:43