01 / THE SIGNAL

我们发现了什么

Enso Method 是一组面向 Claude Code 和 Codex 的新 AI 技能,我已将其在 GitHub 上开源,主要面向那些替负责产品/业务决策的他人构建软件的开发者。自 2024 年底 Sonnet 3.5 时代起,我基本上 100% 用 AI 写代码——那时它勉强能用,做这件事的人很少,而且这种开发方式得到的支持也极少。

  • 来源:Hacker News(发现于 2026-10-13)
  • 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
  • 商业模式:待核验
  • 主题:AI Agent
  • 初筛评分:18.4/100 · 收录 1 次
#工作流自动化#待验证#开源
02 / SOURCE & EVIDENCE

证据,比故事更重要。

发现产品或需求信号,暂未获得可核验的商业证据。

规则清洗与初筛,未经人工商业核验。原文语境、实际客户和付费情况仍需自行验证。

引用与数字披露

来源类型(原作者自述/第三方测算/媒体转引)需采集端标注,本版尚未落字段。

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中文辅助译文(全文)

Enso Method(圆环方法)是我在 GitHub 上开源的一套用于 Claude Code 和 Codex 的新 AI 技能集,主要面向那些为他人构建产品、而由他人做产品/业务决策的开发者。自从 2024 年末的 Sonnet 3.5 时代起,我就基本上 100% 用 AI 来编写我代码了——当时效果勉强能用,做这件事的人寥寥无几,对这种开发方式的支持也极其有限。我固执地认为这将成为未来的趋势,并想出了一套让它行之有效的方法论——那时候甚至还没有"AI 技能"这个概念。从那以后,我一直在不断完善这套方法,最近刚刚将其开源。该方法在前期就聚焦于需求(PRD、TDD),并具备能够自主迭代需求的技能,会声明应由相关方验证的假设。它不要求你必须是独立创始人,也不要求坐在键盘前引导 Claude 或 Codex 的人同时身兼产品负责人和业务决策者。我认为我们大多数人都处于这样一个位置:为做出决策的他人开发。如果 AI 的一切都关乎速度,那么当我们不得不放慢节奏、等待产品负责人审阅和决策时,这就会严重打击大家对 AI 开发效率的期望。Enso Method 的一个核心特性是:在实施之前审视需求时,它会询问存在哪些问题/缺口,并尝试自行回答这些问题。如果它能对答案拥有 95% 以上的把握,就直接采用这些答案。如果低于这个把握度,它就会在 assumptions.md 文件中声明该假设,并将其转交给业务相关方进行审阅。然而,在此期间我们仍然视其为绿灯,可以在带有假设的情况下推进和实施;

之后如果我们从业务方那里得知假设有误,我们会更新需求并重新实施——因为现在的实施成本已经很低,而等待的代价却很高。

译文由上游机器翻译生成,可能有误;判断请以英文原文为准。

英文原文(来源本站未改写)

The Enso Method is a new set of AI skills for Claude Code and Codex which I've open sourced on GitHub predominantly for developers who build for someone else who is making the product/business calls.I've been using AI to write basically 100% of my code since late 2024, back in the Sonnet 3.5 days, when it barely worked and there were few people doing this and very little support for this way of developing.I stubbornly thought this was going to be the future and came up with a methodology for making it work, before "AI skills" were even a thing.Since then I've continued to refine the method and I just recently published it as open source.

The method focuses on requirements (PRD, TDD) up front, and has skills that autonomously refine the requirements, declaring assumptions that should be validated by stakeholders.It doesn't expect you to be a solo founder or that whoever is at the keyboard directing Claude or Codex to be the product owner and business decider in addition to being the developer.I think most of us sit in the seat where we develop for someone else who decides.And if AI is all about velocity, then if we have to slow down to get product owners to review and decide, that puts a serious damper on the efficiency everyone expects from AI development.

So a defining attribute of the Enso Method is, when it reviews the requirements prior to implementation, it asks what questions/gaps there are and it tries to answer its own questions.If it can get to 95%+ confidence in the answers, it just rolls with those.If less then it will declare the assumption in an assumptions.md file which gets routed to business stakeholders to review.In the meantime however we still consider this to be a green light, we can move forward and implement with the assumptions, and if we later hear from the business that the assumption was wrong, we update the requirements and re-implement, because implementation is now cheap, and waiting isn't.

出处https://ensomethod.org抓取日期 · 采集源 Hacker News

03 / EVIDENCE GAPS

这条还缺什么证据?

下面每条都由本条已有字段推出(等级、理由、商业模式、来源次数、是否演示), 本站不生成推测性结论;通用验证方法放在方法论页。

  • 可核验的收入或付费证据查官网定价页与付费口径;第三方数据源(如 GetLatka)只作旁证,需标注来源与时点。
  • 商业模式未定确认按席位/按用量/授权还是开源托管版收费;开源项目另查 LICENSE 与是否存在付费版。
  • 只有单一来源找一手站点或其他渠道是否重复出现同一产品;社区热帖数量不等于商业进展。

通用验证清单(谁有这个问题/谁愿意付费/一个人能交付哪一小步)见我们的筛选方法。

04 / SIGNAL HISTORY

发现时间线