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This isn’t generic prompt engineering — These techniques are specific to working with Claude Code in real codebases. If you want general prompting advice, look elsewhere.

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Be Specific, Not Emphatic

Error messages beat adjectives. File paths beat “the auth code.” ALL CAPS doesn’t help — context does. The model responds to information, not emphasis.

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Challenge Claude

Don’t just accept the first output. Push back:
  • “Grill me on these changes and don’t make a PR until I pass your test.” — Forces Claude to verify you understand the code before shipping it.
  • “Knowing everything you know now, scrap this and implement the elegant solution.” — After Claude has explored the problem space, ask it to restart with full context. The second attempt is almost always better.
  • “What are three ways this could break in production?” — Surfaces failure modes you haven’t considered.

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Pre-Planning: Reduce Assumptions First

Before jumping into a plan, ask Claude to research the codebase and surface 5-10 clarifying questions. This eliminates assumption drift — especially critical for multi-agent work where two agents assuming different things produces code that individually passes tests but fails integration.

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Self-Reflection Loops

This is a Level 4 technique from the maturity ladder. Ask Claude to check its own work:
  • “Are you sure about this? What about edge case X?”
  • “Review this diff as if you were a senior engineer who’s skeptical of AI-generated code.”
  • “What assumptions are you making? Which ones could be wrong?”
Self-reflection uses more tokens but catches mistakes before they reach code review. The net cost is lower.

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Problem Decomposition

When one-shotting a complex task fails, break it down:
Each sub-problem is independently solvable and verifiable. Claude handles scoped tasks better than sprawling ones.

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CLAUDE.md as a Self-Updating Artifact

Every time you correct Claude, tell it:
“Update CLAUDE.md so you don’t make that mistake again.”
Claude is good at writing rules for itself. Over time, your CLAUDE.md accumulates project-specific knowledge that prevents repeated mistakes. This is the compounding advantage of agentic engineering — the context improves with every session.

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Behavior Injection for Agents

Agent behavior affects output quality as much as the prompt content. A “thinks methodically” debugging agent produces different results than a “moves fast” prototyping agent. Set behavioral constraints in agent definitions or CLAUDE.md sections: This isn’t “prompt engineering tricks” — it’s designing agent personas that match the task. A validator agent should be skeptical by default. A builder agent should be decisive. Encode these traits in the agent’s system context so they’re consistent across invocations.

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Voice Input

You speak roughly 3x faster than you type. For prompting Claude Code, that speed matters — see also the official voice dictation docs. Run /voice to enable built-in push-to-talk, then hold Space to record. You can rebind to a modifier combo like meta+k to skip the warmup delay. Don’t worry about perfect transcription. Claude handles mistranscriptions, filler words, and informal language well. The speed gain outweighs the occasional misparse.