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2 changes: 1 addition & 1 deletion .github/linters/.codespellrc
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@@ -1,3 +1,3 @@
[codespell]
skip = ./.github/linters
ignore-words-list = afterall
ignore-words-list = afterall,skelton,erformance
8 changes: 4 additions & 4 deletions src/docs/Ways-of-Working/continuous-x-and-continuous-ai.md
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The cleanest authoritative taxonomy. From [DevOps Dojo White Belt Foundation](https://learn.microsoft.com/en-us/training/paths/devops-dojo-white-belt-foundation/):

| # | Practice | What it covers |
|---|----------|----------------|
| --- | ---------- | ---------------- |
| 1 | Continuous Planning | Lean product, hypothesis-driven dev, backlog management, OKRs |
| 2 | Continuous Integration | Trunk-based dev, automated build & test on every commit |
| 3 | Continuous Delivery | Every commit potentially releasable; automated pipeline to prod |
Expand All @@ -20,7 +20,7 @@ The cleanest authoritative taxonomy. From [DevOps Dojo White Belt Foundation](ht
### Full inventory with provenance

| Practice | Origin / canonical source |
|----------|--------------------------|
| ---------- | -------------------------- |
| **Continuous Integration** | Coined in Grady Booch's 1991 method; popularised by XP and [Martin Fowler's 2006 article](https://martinfowler.com/articles/continuousIntegration.html). |
| **Continuous Delivery** | Jez Humble & David Farley, [*Continuous Delivery*](https://continuousdelivery.com/), 2010. |
| **Continuous Deployment** | Every passing build deploys to prod with no human gate (vs. CD which only makes it *deployable*). |
Expand Down Expand Up @@ -73,7 +73,7 @@ Continuous AI tasks are: **automatable, repetitive, collaborative, integrated, a
### Continuous AI vs. its cousins

| Term | What it is |
|------|-----------|
| ------ | ----------- |
| **Continuous AI** | AI participating *in* the SDLC continuously (review, docs, triage, fault analysis). The AI is the actor. |
| **MLOps** | CI/CD/CT *for* ML models — training, evaluation, deployment, monitoring. The model is the product. |
| **LLMOps** | MLOps specialised for LLM apps: prompt versioning, evals, retrieval, guardrails, cost/latency monitoring. |
Expand All @@ -82,7 +82,7 @@ Continuous AI tasks are: **automatable, repetitive, collaborative, integrated, a
### How Continuous AI augments each Continuous X practice

| Traditional practice | Continuous-AI augmentation | Example tools (2025) |
|---------------------|---------------------------|----------------------|
| --------------------- | --------------------------- | ---------------------- |
| Continuous Integration | AI summarises broken builds; suggests fixes | GitHub Copilot Workspace, Sweep |
| Continuous Delivery | Agents drive multi-step deploys; AI-authored release notes | GitHub Copilot agents, Devin |
| Continuous Testing | Test generation, flaky-test detection, auto-repair | Diffblue, Qodo (CodiumAI), Meta TestGen-LLM |
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4 changes: 2 additions & 2 deletions src/docs/Ways-of-Working/devops-reference.md
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Expand Up @@ -9,7 +9,7 @@ A curated synthesis of authoritative sources, frameworks, and practices.
### The Canon (Books)

| # | Title | Author(s) | Year | Why it matters |
|---|-------|-----------|------|----------------|
| --- | ------- | ----------- | ------ | ---------------- |
| 1 | **The Phoenix Project** | Gene Kim, Kevin Behr, George Spafford | 2013 | The novel that introduced DevOps to mainstream. Source of the Three Ways. [itrevolution.com/product/the-phoenix-project](https://itrevolution.com/product/the-phoenix-project/) |
| 2 | **The Unicorn Project** | Gene Kim | 2019 | Sequel from the developer's perspective; flow state, psychological safety, Five Ideals. |
| 3 | **The DevOps Handbook** (2nd ed.) | Gene Kim, Jez Humble, Patrick Debois, John Willis | 2016/2021 | Practical companion to Phoenix Project. The reference implementation guide. |
Expand Down Expand Up @@ -57,7 +57,7 @@ All available at **[sre.google/books](https://sre.google/books/)**
The evidence-based standard for DevOps performance. Source: Forsgren/Humble/Kim research, now part of Google Cloud.

| Metric | What it measures | Elite performance |
|--------|------------------|-------------------|
| -------- | ------------------ | ------------------- |
| **Deployment Frequency** | How often you deploy to prod | Multiple per day / on-demand |
| **Lead Time for Changes** | Commit → production | < 1 hour |
| **Change Failure Rate** | % of deploys causing problems | 0–15% |
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