Onboarding Email Sequence
Defining the activation metric upfront ensures every email drives toward the moment users realize the product's value, not just feature awareness.
Write a {{sequence_length}}-email onboarding sequence for {{product_name}}, a {{product_description}} SaaS tool.\n\nTarget user persona: {{persona}}\nCore value proposition: {{value_prop}}\nKey activation metric ("aha moment"): {{activation_metric}}\nTone: {{tone}}\n\nFor each email in the sequence, provide:\n1. Subject line (and one A/B variant)\n2. Send timing (days after signup)\n3. Goal of this email (what action should the user take)\n4. Body copy (150-200 words)\n5. Primary CTA button text\n6. Fallback plain-text version\n\nThe sequence should progress from welcome → first value → deeper features → social proof → upgrade nudge.\nDo NOT be pushy. Focus on helping the user succeed.
Variables to customize
Why this prompt works
Defining the activation metric upfront ensures every email drives toward the moment users realize the product's value, not just feature awareness.
Save this prompt to your library
Organize, version, and access your best prompts across ChatGPT, Claude, and Cursor.
Related prompts
Forcing the agent to plan before acting prevents premature execution and wasted steps. Explicit dependency mapping enables parallel execution and catches logical gaps early.
Tool Selection AgentThe ReAct pattern (Reason + Act) creates an explicit reasoning trace that improves tool selection accuracy. The error-handling rule prevents infinite retry loops.
Prompt CompressorExplicitly requiring all functional requirements to be preserved prevents the model from over-compressing and losing critical instructions.
Memory Management AgentExplicit memory read/write instructions create agents that improve over time. Categorization keeps memories organized, and the deduplication rule prevents context bloat.