Session 1

Session Agenda

Ad-Hoc AI Prompting Doesn't Scale

Most professionals use AI tools the same way they'd use a search engine — one-off questions, generic context, inconsistent results. Here's what that looks like:

Professional: "Hey AI, help me write my annual priorities"
AI: [generates generic priorities]
Professional: "These don't capture my impact... try again"
AI: [generates different generic priorities]
Professional: "Still missing key metrics..."

The problems with ad-hoc prompting:

• Every prompt starts from scratch — no accumulated knowledge
• No team knowledge captured — can't share what works
• Inconsistent results across attempts and team members
• Successful approaches can't be reused or improved

Key insight: Patterns matter more than format. Choose based on team needs, not dogma.

Three Valid Approaches

There is no single "right" way to do systematic prompting. Three approaches have emerged in industry practice, each suited to different team contexts:

Tier Framework for Evaluation

Use this to assess any prompt engineering approach you encounter:

Four Foundational Patterns

These patterns are research-backed and appear in all serious prompt engineering work. A well-constructed prompt uses all four.

The 325-Line Priority Builder

The Priority Builder Agent prompt uses all four patterns together. It demonstrates what a production-grade prompt looks like vs a quick one-off request:

• Persona: "You are an expert career coach specializing in professional priorities..."
• Few-shot: Built-in priority examples with ABCD reflections showing expected quality
• Template: Structured CSV output plus formatted summaries for direct submission
• Chain-of-Thought: The 20-question ABCD reflection framework that guides analysis

The result: persona-driven specificity, structured questioning that ensures completeness, and consistent output format — versus the ad-hoc alternative that generates something generic every time.

Hands-On: Build Priorities

Exercise 1 — Freestyle First (10 minutes)

Before using any systematic approach, attempt to create one priority for a demo persona using your normal prompting style.

Notice what's hard: specificity, metrics, avoiding generic language that could apply to anyone.

Exercise 2 — Priority Builder Template (15 minutes)

Now use the complete Priority Builder Agent with a different persona than Exercise 1.

1. Load the 325-line Priority Builder prompt into your AI tool
2. Choose a different persona than the freestyle round
3. Let the agent guide you through its 20-question process — answer as your persona
4. Select a version: Conservative, Balanced, or Aspirational
5. Export the CSV output (ready for submission format)

Success criteria: Complete ABCD reflections with specific metrics, CSV output ready.

Exercise 3 — Compare Three Approaches (10 minutes)

Same Spring Boot 2→3 migration task, three different approaches. Observe the difference in structure and maintenance overhead — not the result.

"Following .github/copilot-instructions.md,
migrate UserController to Spring Boot 3"

What You Accomplished

• Learned the Three Approaches evaluation framework and when each applies
• Recognized all four foundational patterns in a real 325-line production prompt
• Generated priorities using a systematic approach vs freestyle
• Compared structured vs unstructured methodology on the same task

Cross-Domain Application

The patterns you practiced in this session work across domains:

Same systematic thinking, different domain. Session 2 demonstrates this across the full range.