Claude.md

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Seonglae ChoSeonglae Cho
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2026 Mar 2 11:58
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  • Map vs Territory
    • Prompts/plans are the “map”
    • The real codebase/constraints are the “territory”
    • The gap between the two is where the unknowns live.
  • In Claude Fable 5, the bottleneck is how well the user clarifies unknowns—not model capability
    • If results are poor, it’s often not because the model is “dumb,” but because ambiguous parts weren’t properly identified/defined.
  • Splits unknowns into four types
    • Known knowns: things already explicitly stated
    • Known unknowns: things you know you don’t know
    • Unknown knowns: implicit preferences/criteria you’d recognize if you saw them, but haven’t articulated
    • Unknown unknowns: risks/constraints you haven’t considered at all
  • Recommended Claude Code workflow
    • Before implementation, do a blind-spot pass to surface “unknown unknowns”
    • Don’t jump straight into implementation—start with brainstorming/prototyping
    • Have Claude interview you with questions to remove ambiguities that could change the architecture
    • If you want specific behavior, provide reference code rather than just describing it
    • Before implementation, ask for an implementation plan and review the most change-prone parts first (data model, types, UX)
  • During implementation
    • Have Claude record decisions/workarounds/edge cases in a scratch doc like implementation-notes.md.
    • This makes it easier to postmortem failures or hand off to the next session.
  • After implementation
    • Write a pitch/explainer doc to convince reviewers
    • Ask Claude to quiz you to ensure you truly understand the changes
    • E.g., “No merge until I get the quiz right.”
 
 
 
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A field guide to Claude Fable 5: Finding your unknowns | Claude | Claude by Anthropic
Practical patterns for agentic coding with Claude Fable: how to find your unknowns before, during, and after implementation, from the team at Anthropic.
 

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