Reddit Prompting Techniques: Long-form Analysis, Counterarguments, and Concise Execution

One-sentence takeaway

This user test offers several short, reusable task instructions: ask the model “what would you ask about,” make it properly argue the other side, tell it not to explain but simply execute, and proactively ask it to search for webpages that may have changed.

Use cases

• Suitable tasks: Risk-oriented questioning for long contracts or documents, decision analysis, execution-oriented tasks with clearly defined goals, and research that requires the latest web materials.

• Unsuitable tasks: Treating a personal experience as a controlled benchmark, or expecting the model to accurately imitate a personal writing style without context.

• Applicable model version: The author explicitly discusses Claude Fable 5.1; other versions can only be treated as hypotheses to validate.

• Applicable client, Agent, or API: The original post does not specify API parameters; the phrases can be used in the Claude client or as user messages for a self-built Agent.

• Recommended reasoning tier and parameters: Not disclosed in the original post; compare the default tier with higher tiers on a task set rather than inferring fixed parameters from a personal experience.

Ready-to-use content

The original post makes short instructions public, not a complete system prompt. The following preserves three short, directly reusable lines from the original and notes their uses:

what would you ask about if you were me
argue the other side properly
dont explain, just do it

As a reusable workflow, they can be combined as follows:

Read the material first, rather than just summarizing it: from my position, list the key questions you would ask and explain why each one matters.
Properly argue the strongest opposing case against the current proposal, listing the strongest objections, the conditions under which they hold, and the evidence I need to provide.
If the task goal and acceptance criteria are already clear, execute directly and report the result; do not repeat the plan or leave the next step for me to complete manually.
For facts that may have changed within the past week, search first and cite the original page; do not draw conclusions from memory.

Usage suggestions

1. For a long document, use “what would you ask about” to build a question list and then answer each question; this is better than directly asking for a “summary” when the goal is to find omissions and risks.

2. For decision tasks, use the “strongest opposing case” as a separate stage to prevent the model from merely confirming the user's original proposal.

3. “Execute directly” applies only when the scope and acceptance criteria are already defined; external publishing, deletion, and other irreversible actions still require human confirmation.

4. The author specifically cautions that when webpage content may have changed recently, you should explicitly require a search; the output still needs to be checked manually against the source and date.

Original evidence and data

• The original post's author says they gave Fable 5.1 about 40 files and asked “where exactly is the money being calculated”; the model traced back through the call chain rather than guessing from file names.

• The original post suggests asking about a 90-page contract or set of terms, “what would you ask about if you were me,” rather than only asking for a summary.

• The original post lists three short instructions: ask the model to argue the other side, tell it “dont explain, just do it,” and proactively search for webpages that may change.

• The original post also states the boundaries clearly: when an instruction is ambiguous, the model may still confidently get it wrong; to imitate a user's writing style, it is best to provide about three examples of their own; and the author did not provide API configuration, tokens, or controlled comparison data.

Applicability boundaries

• This is the experience report of a single Reddit user and cannot be treated as evidence of Fable 5.1's general capabilities or as an evaluation result.

• “Better” in the original post is a subjective judgment; long documents, call chains, and web search should be rechecked on your own dataset.

• “Don't explain, just execute” may reduce process visibility; for high-risk tasks, retain key assumptions, evidence, and verification results.

• The post does not disclose a complete long prompt, so it is categorized as prompting-guide rather than presented as a complete prompt.

Source excerpts or observations (for compliant short quotations only)

• “what would you ask about if you were me”

• “argue the other side properly”

• “dont explain, just do it”