Course Objective & Scope
When employees write ad-hoc prompts from scratch, outputs across a department vary wildly in structure, depth, and tone. This focused training teaches teams how to standardize the three pillars of repeatable prompting: Domain Persona, Operational Instructions, and Deterministic Output Templates.
Participants move beyond superficial 'Act as an expert' openers to encode real evaluation criteria into personas, write unambiguous instruction checklists, and lock down output formats using Markdown skeletons, tables, and JSON schemas. Attendees leave with a ready-to-use pack of fill-in-the-blank departmental templates.
Who Should Attend?
- Team leads and specialists aiming to standardize reports, client communications, and analyses across their units
- Operations, quality assurance, sales enablement, and HR professionals designing reusable team playbooks
- Business users who need AI outputs formatted cleanly for spreadsheets, CRMs, or corporate document templates
- No programming experience required
Key Takeaways
- Design substantive domain personas anchored in specific evaluation criteria, priorities, and communication styles
- Write modular instruction blocks combining step-by-step directives, boundary conditions, and negative rules
- Enforce consistent output structures using Markdown skeletons, fixed-column tables, and JSON schemas
- Use multi-persona critique templates (e.g., CFO, Legal Counsel, Customer Buyer) to stress-test proposals
- Package prompts with clear `{{VARIABLE}}` placeholders so colleagues can execute them reliably
Curriculum
Designing Functional Personas and Perspectives
- Why generic 'Act as an expert' openers fail—and how to specify domain priorities and decision lenses
- Contrasting constructive drafter personas with skeptical auditor and compliance reviewer personas
- Multi-perspective prompting: evaluating a proposal simultaneously through CFO, Legal, and Buyer lenses
Engineering Crisp Instruction and Rule Blocks
- Replacing vague adjectives ('brief', 'professional', 'thorough') with measurable rules
- Writing conditional instructions (If input contains X, perform A; otherwise perform B)
- Eliminating conversational filler and preambles for clean, copy-ready corporate outputs
Deterministic Output Templates and Schemas
- Locking down document structure with Markdown skeletons and fixed-column tables
- Formatting outputs as clean CSV, JSON, or YAML for downstream spreadsheets and workflows
- Embedding positive and negative examples to prevent structural drift
Building Variable-Driven (`{{Variable}}`) Team Templates
- Separating immutable template logic from user-supplied `{{INPUT_VARIABLES}}`
- Documenting template usage notes: required inputs, expected output, and verification steps
- Workshop: Creating 6 standardized Persona-Instruction-Output template cards for your team
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