Backlinks

• CSS Primer for the AI Era
• 05. When AI Suggests a Refactor (How to Decide What to Accept)
• 02. How AI Sees Code (and What It Cannot See)
• 19. When AI Overgeneralizes (How to Bring the Work Back to the Specific)
• 16. When AI Over‑Explains (How to Bring the Work Back to Clarity)
• 11. When AI Misunderstands a Pattern (How to Correct the Shape and Preserve the Intent)
• 06. Safe Refactoring — How to Guide AI Toward Minimal, Predictable Changes
• 35. When AI Misreads the Context of the Change (How to Keep the Work Aligned With the Situation Around It)
• 32. When AI Misreads the Intent of the Code (How to Keep the Work Aligned With What the Code Is For)
• 26. When AI Misreads the Level of Risk (How to Keep Changes Safe and Proportionate)
• 34. When AI Misreads the History of the Code (How to Keep the Work Aligned With Why the Code Became What It Is)
• 31. When AI Misreads the Boundaries (How to Keep Components Separate and Responsibilities Clear)
• 25. When AI Over‑Documents (How to Keep Comments Useful, Minimal, and Honest)
• 24. When AI Over‑Explains the Obvious (How to Keep the Work Focused and Respectful of the Reader)
• 20. When AI Over‑Corrects (How to Keep the Work Stable and Minimal)
• 23. When AI Invents a Convention (How to Keep the System Grounded in Reality)
• 18. When AI Misjudges Priority (How to Keep the Work Aligned With What Matters)
• 30. When AI Misreads the Dependencies (How to Keep the Work Coherent Across the System)
• 27. When AI Misreads the Cost of Change (How to Keep the Work Efficient and Sustainable)
• 28. When AI Misreads the Impact of a Change (How to Keep the Work Focused on What Actually Improves the System)
• 29. When AI Misreads the Stability of a Change (How to Keep the Work Future‑Proof and Maintainable)
• 33. When AI Misreads the Constraints (How to Keep the Work Within the Real Limits of the System)
• 21. When AI Misreads the Audience (How to Match the Explanation to the Reader)
• 14. When AI Invents Features (How to Prevent Hallucinated Behavior)
• 13. When AI Breaks the Architecture (How to Re‑Assert the System’s Rules)
• 15. When AI Misreads Intent (How to Re‑Center the Goal)
• 09. When AI Gets Lost (How to Reset, Re‑Anchor, and Regain Control)
• 12. When AI Over‑Refactors (How to Restore Simplicity)
• 22. When AI Misses the Hidden Dependency (How to Reveal What the System Relies On)
• 17. When AI Misses the Edge Case (How to Reveal the Hidden Risk)
• 04. Temporary Hacks (Like !important) — How to Use Them Without Creating Noise
• 36. Closing — Working With Existing Code Is an Act of Stewardship
• 01. Preface: This is a long topic, but easy to read
• 03. Showing AI the Right Parts of the Code (and Only the Right Parts)
• 10. When AI Misunderstands the System (How to Reveal the Missing Context)
• 07. Working With Legacy Code (How to Guide AI Through Older Patterns)
• 08. Working With Themes and Plugins (How to Keep AI Inside the Boundaries)

• 01. Preface: This is a long topic, but easy to read
• 02. How AI Sees Code (and What It Cannot See)
• 03. Showing AI the Right Parts of the Code (and Only the Right Parts)
• 04. Temporary Hacks (Like !important) — How to Use Them Without Creating Noise
• 05. When AI Suggests a Refactor (How to Decide What to Accept)
• 06. Safe Refactoring — How to Guide AI Toward Minimal, Predictable Changes
• 07. Working With Legacy Code (How to Guide AI Through Older Patterns)
• 08. Working With Themes and Plugins (How to Keep AI Inside the Boundaries)
• 09. When AI Gets Lost (How to Reset, Re‑Anchor, and Regain Control)
• 10. When AI Misunderstands the System (How to Reveal the Missing Context)
• 11. When AI Misunderstands a Pattern (How to Correct the Shape and Preserve the Intent)
• 12. When AI Over‑Refactors (How to Restore Simplicity)
• 13. When AI Breaks the Architecture (How to Re‑Assert the System’s Rules)
• 14. When AI Invents Features (How to Prevent Hallucinated Behavior)
• 15. When AI Misreads Intent (How to Re‑Center the Goal)
• 16. When AI Over‑Explains (How to Bring the Work Back to Clarity)
• 17. When AI Misses the Edge Case (How to Reveal the Hidden Risk)
• 18. When AI Misjudges Priority (How to Keep the Work Aligned With What Matters)
• 19. When AI Overgeneralizes (How to Bring the Work Back to the Specific)
• 20. When AI Over‑Corrects (How to Keep the Work Stable and Minimal)
• 21. When AI Misreads the Audience (How to Match the Explanation to the Reader)
• 22. When AI Misses the Hidden Dependency (How to Reveal What the System Relies On)
• 23. When AI Invents a Convention (How to Keep the System Grounded in Reality)
• 24. When AI Over‑Explains the Obvious (How to Keep the Work Focused and Respectful of the Reader)
• 25. When AI Over‑Documents (How to Keep Comments Useful, Minimal, and Honest)
• 26. When AI Misreads the Level of Risk (How to Keep Changes Safe and Proportionate)
• 27. When AI Misreads the Cost of Change (How to Keep the Work Efficient and Sustainable)
• 28. When AI Misreads the Impact of a Change (How to Keep the Work Focused on What Actually Improves the System)
• 29. When AI Misreads the Stability of a Change (How to Keep the Work Future‑Proof and Maintainable)
• 30. When AI Misreads the Dependencies (How to Keep the Work Coherent Across the System)
• 31. When AI Misreads the Boundaries (How to Keep Components Separate and Responsibilities Clear)
• 32. When AI Misreads the Intent of the Code (How to Keep the Work Aligned With What the Code Is For)
• 33. When AI Misreads the Constraints (How to Keep the Work Within the Real Limits of the System)
• 34. When AI Misreads the History of the Code (How to Keep the Work Aligned With Why the Code Became What It Is)
• 35. When AI Misreads the Context of the Change (How to Keep the Work Aligned With the Situation Around It)
• 36. Closing — Working With Existing Code Is an Act of Stewardship