資料來源#
摘要#
Fiona Fung 對 AI-native org 的知識分享重寫是:當 coding bandwidth 很高時,documentation 會比任何人能維護的速度更快過期,所以 codebase 變成 source of truth,而任何你想保持真實的東西都要 check into codebase。 Specs 會變成 committed to repo 的 skills;onboarding 不是把工程師拉進 tech deep-dives,而是請 Claude 教你 surface area。「Our code is our source of truth.」
為什麼 docs 會在 AI-native org 中腐壞#
這個機制是 Verification as the New Bottleneck 的直接後果:更高的 coding throughput 意味著 code 變動更快,所以任何在 update loop outside 的 documentation 幾乎立刻就會 drift 過期。Fung 的處方是:「whatever is your source of truth — whether it's a spec — change that into a skill you check into the codebase, so you can keep it up to date.」repo 是唯一會保持 current 的 artifact,因為它就是正在被改動的東西。
Specs-in-repo enable spec-drift verification#
把 spec check into codebase 不只是 freshness hygiene,更是讓 mechanical verification 成為可能的東西:「Claude is very good about verifying against spec drift.」一份 committed spec 同時是 human-readable intent,也是 review agent 用來對照 diff 的 machine-checkable reference。(這和 Symphony 的 WORKFLOW.md 以及 Claude Code 的 CLAUDE.md 是同一招:repo-versioned plaintext 作為 control plane;見 Symphony、Claude Code Best Practices。)
透過 Claude onboarding,而不是透過同事#
Fung 自己 onboarding 到 Claude Code 的方式是:不是(只)和工程師做 tech deep-dives,而是第一次 deep-dive with Claude:「before I dive into this bug fix, can you teach me about the surface area and the areas around this bug?」她回報的效果是:onboarding ramp-up time 下降,對 other team members 的成本也下降,new joiners 不再為了 context 消耗 senior engineers 的時間。作為 manager,這也讓她能無負罪感地重新進入 codebase(「I don't feel like I'm wasting anybody's time」)。codebase + Claude 就是 onboarding doc。(見 Managers as ICs。)
與 CLAUDE.md 和 agentic debt 的關係#
Code-as-source-of-truth 是正面的 program;Agentic Technical Debt 是它防範的 failure mode。Persistent、committed context(CLAUDE.md、checked-in skills/specs)會阻止每一次 agentic session 重新推導 architectural decisions。這個 wiki 自己的 LLM-as-Compiler Knowledge Base 是更高階的實例:它是 compiled, current artifact,而不是重新推導出來的 knowledge。
相關連結#
- Building Is Cheap, Arguing Is Expensive — 如果 code 贏得 debates,那麼 repo(不是 docs)就是 source of truth
- Fiona Fung —「our code is our source of truth」
- Verification as the New Bottleneck — 原因:high throughput 讓 docs 變 stale;spec-in-repo 啟用 spec-drift checks
- Agentic Technical Debt — 當 context isn't persisted in repo 時會 compound 的 debt;這就是 antidote
- Claude Code Best Practices — CLAUDE.md 是 canonical repo-versioned-context pattern
- Symphony —
WORKFLOW.md/SPEC.md作為 orchestration layer 的 repo-versioned control plane - Managers as ICs — Claude-as-onboarding-doc 讓 manager-into-codebase re-entry 變便宜
- LLM-as-Compiler Knowledge Base — compile-and-keep-current vs. re-derive;knowledge-management principle 往上一層
- Claude's Constitution / Model Spec — spec-as-load-bearing-document,位於 alignment layer
待解決的問題#
- 什麼 knowledge 真的 can't live in codebase(org strategy、「why」、cross-team context),因此仍然需要 durable doc?又該如何讓那一小塊保持 current?
- 如果 onboarding 是「ask Claude」,那些過去在 deep-dives 中透過社交方式傳遞的 tacit knowledge 會發生什麼事?它有被 capture 在任何地方嗎,還是安靜地 lost?
衍生內容#
- Where Does the Why Live? — 接續本頁第一個 open question;本頁排除在 codebase 外的「why」沒有乾淨的 home,只有 richer-artifact 和 compiled-knowledge-base 這些 partial patches
資料來源#
Cited by 13
- Agentic Technical Debt
Debt that *compounds* (not just accumulates) because each agentic-coding session re-derives architectural decisions wit…
- Anthropic
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- Building Is Cheap, Arguing Is Expensive
"In technical debate, code wins": generate three PRs vs whiteboard; prototype over design doc; reduce design docs
- Claude Code
Anthropic's agentic coding product; created by Boris Cherny late 2024; TypeScript/React; CLI/desktop/web/mobile/IDE sur…
- Where Does Agent Harness Work Remain Durable as Models Improve?
Durable harness work lives at external-reality boundaries: repo-local source of truth, mechanical verification, context…
- Fiona Fung
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- LLM-as-Compiler Knowledge Base
Karpathy's architecture: LLM incrementally compiles raw docs into a persistent interlinked wiki, replacing RAG with a 4…
- Managers as ICs
Every Claude Code manager starts as an IC; flat org; agentic coding collapsed the onboarding cost that pushed managers…
- AI Engineering & Agent Tooling
Map of Content for the ai-engineering domain — 36 concepts. Curated entry point; see Home for all domains.
- Open Questions Backlog
_96 pages with open questions, as of 2026-06-14._
- The PRD-Replacement Spectrum at AI-Native Speed
Four positions (grill-then-PRD → lighter-PRD → build-to-decide → prototype-is-spec) are one spectrum once you decompose…
- Verification as the New Bottleneck
Fiona Fung: coding is no longer the bottleneck — verification, review, maintenance are; shift-left; TDD loses its tax;…
- Where Does the Why Live?
Rationale (the 'why') is well-homed at authoring time — it's the recorded why-not-what conversation and the grilling se…
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