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Opus 5: Useful Prompting Tips That Work - A practical before-and-after test using Anthropic’s guide

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I tested Claude Opus 5 with a real 90-day go-to-market task and compared a basic prompt with a structured framework based on Anthropic’s official guidance. The video shows five practical prompting rules, one advanced subagent tip, both outputs, and the usage from each run. You’ll see how clearer task scope, source grounding, trade-off rules, output control, and completion criteria make the final plan easier to trust, scan, and use.

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Hi Product Hunt 👋 This video is a practical test of Claude Opus 5. My first result looked reasonable, but the recommendations were difficult to verify. Sources were unclear, assumptions blended into the advice, and the channel decisions did not follow a visible framework. So I rebuilt the prompt using five rules from Anthropic’s official guidance: - Define the complete task and its constraints - Ground important claims in supplied sources - Add clear criteria for comparing options - Control analysis and final output separately - Set observable completion and stopping rules I then ran the same 90-day go-to-market task again with the same five source files, model, effort setting, and measured usage. Both runs used 9% usage. The second output was longer, but its evidence, assumptions, trade-offs, budget, ownership, and decision rules were much easier to inspect. There is also one advanced tip about subagents for Claude Code and Cowork. Claude Chat does not support that workflow yet. Curious to hear from you: which prompting rule has made the biggest difference in your own Claude workflows? Comment “AI Fire” I’ll send you the complete prompt framework.