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A prompt-building cheat sheet. Keep this open while writing your first prompts.

When to use structured vs. natural language

Use structured format when…Use natural language when…
The task has multiple conditions or edge casesThe task is simple and unambiguous
Output format must be exact (picklist, date, score)Detection or extraction is self-evident
You need precise silence and attribution rulesYou’re iterating quickly and testing scope
You’re configuring a Summary or Coaching competencyYou’re writing a Signal trigger or Smart Tag

Silence patterns — by feature

FeatureWhen nothing is found…
Autopilot (CRM field)Return nothing. Silence = no write. Never fill with placeholders. If Momentum is the only writer to that field, output an explicit value (e.g. N/A) so you can validate the prompt ran.
Signal triggerOutput FALSE. Zero explanation.
Signal follow-upOutput an explicit “No [X] found.” — confirms the prompt ran and prevents a blank Slack block.
Summary sectionOutput a defined fallback (e.g. None identified). Never skip or leave a section blank.
Coaching competencyNote that the call was too short or lacked sufficient context to evaluate.

Word precision cheat sheet

Weak phrasingStronger alternativeWhy it matters
”You should…""You MUST…”Suggestions can be overridden by the AI when uncertain. Hard constraints cannot.
”Summarize""Extract”Summarize invites paraphrase and interpretation. Extract pulls what’s explicitly stated.
”Look for""Identify only”Look for is a broad search that surfaces tangential mentions. Identify only narrows scope and reduces false positives.
”If not found, say nothing""Complete silence is the correct output. Outputting any text when no qualifying data exists is a critical error.”Weak silence rules are routinely ignored. Raising the stakes forces compliance.

The five most common prompting mistakes

MistakeFix
Trigger prompt extracts content instead of TRUE/FALSERewrite as binary detection. Output TRUE or FALSE only.
No silence rule definedAdd: “If [condition] not present, output nothing.” Or define an explicit value if intentional (see Silence Patterns above).
Picklist allows freeform outputList exact allowed values. State: return one value only, character-for-character.
Summary sections do too muchOne extraction goal per section. Split complex ones in two. Keep to 4–7 sections total.
Coaching rubric uses vague languageDefine observable behaviors — specific actions the rep took or didn’t take, not subjective impressions.