--- title: "Session 1 — Patterns" description: "Three Approaches, foundational patterns, priority builder." author: "Joey Lopez" date: "2026-01-15" tags: ["prompting", "teaching"] atom_id: 9 source_html: "bootcamp-session1.html" url: "https://jrlopez.dev/p/bootcamp-session1.html" generated: true --- [← home ]()[bootcamp ]()[the problem ]()[three approaches ]()[patterns ]()[exercises ]()[wrap-up ]() # Session 1 Industry Standards & Real-World Application — from ad-hoc prompting to systematic approaches Joey Lopez · Prompt Engineering Bootcamp · 60 minutes [the problem ]()[three approaches ]()[patterns ]()[exercises ]()Overview ## Session Agenda | Time || Activity || Type | | 0–5 min || Problem & Solution Overview || Lecture | | 5–15 min || Three Approaches Framework || Lecture | | 15–20 min || Foundational Patterns || Lecture | | 20–25 min || Demo: Priority Builder || Hands-on | | 25–45 min || Your Turn: Build Priorities || Hands-on | | 45–55 min || Compare: Three Approaches || Hands-on | | 55–60 min || Wrap & Session 2 Preview || Lecture | The Problem ## 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. Framework ## 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: #### ADRs + Config Architecture Decision Records plus configuration files. Example: .github/copilot-instructions.mdthat any AI tool reads automatically. Best for most teams. Low setup overhead. #### Structured Files Multi-file workflows: knowledge-base → specification → implementation-plan. Each file has a specific purpose and builds on the previous. Best for complex, repeated tasks and learning. #### Tool-Assisted Platform-native workflows like Windsurf's cascade system (290 lines). The tool manages context and sequencing automatically. Best for teams committed to one IDE or platform. ### Tier Framework for Evaluation Use this to assess any prompt engineering approach you encounter: #### Tier 1 — Proven (10+ years) Architecture Decision Records, Few-shot prompting, Chain-of-Thought. Used at scale by Microsoft, AWS, Google, Netflix. These patterns have survived real production use. #### Tier 2 — Production Ready (1–3 years) .github/copilot-instructions.md, ReAct pattern. Growing enterprise adoption. Reasonably safe to build on. #### Tier 3 — Experimental (<2 years) Spec-kit workflows, structured prompt files, tool-specific approaches. Interesting and useful, but unproven at scale. Use deliberately. Patterns ## Four Foundational Patterns These patterns are research-backed and appear in all serious prompt engineering work. A well-constructed prompt uses all four. Persona "You are an expert [role] with [specific expertise]..." Establishes the lens the AI uses for all responses. Few-shot Provide 2–3 example input/output pairs before your actual request. Shows the desired format and quality level. Template "Respond in this format: [structure]" Constrains output shape for reuse and consistency. Chain-of-Thought "Show your reasoning step by step before giving the answer." Forces deliberate reasoning, catches errors earlier. ### 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. Exercises ## 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. #### Choose a demo persona - **Option A: **Delivery Lead, Financial Services (8 years, team management) - **Option B: **Tech Lead, Banking Automation (5 years, AI/ML specialist) - **Option C: **Associate Manager, Digital Strategy (6 years, transformation) **Goal: **1 priority in any category with basic reflection. Use your AI tool however you normally would. 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. - Load the 325-line Priority Builder prompt into your AI tool - Choose a different persona than the freestyle round - Let the agent guide you through its 20-question process — answer as your persona - Select a version: Conservative, Balanced, or Aspirational - 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. #### Approach A — ADRs + Config ``` "Following .github/copilot-instructions.md, migrate UserController to Spring Boot 3" ``` #### Approach B — Structured Files Load: knowledge-base.md→ specification.md→ implementation-plan.md #### Approach C — Tool-Assisted Windsurf cascade workflow (290-line systematic methodology with built-in validation steps). Same result, different maintenance overhead. Which fits your team? Wrap-Up ## 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: #### Business Applications - Strategic planning documents - Performance reviews and goal setting - Client presentations and proposals - Training material development #### Technical Applications - Code migration and refactoring - Architecture documentation - Troubleshooting workflows - System design patterns Same systematic thinking, different domain. Session 2 demonstrates this across the full range. #### Session 2 Preview - **ReAct pattern **(Think → Act → Observe) for multi-step reasoning - **Tree of Thoughts **for decision points with real tradeoffs - **Interview prep workflow **— 4-file systematic approach - **Live technical demo **— Spring Boot migration using same patterns Bring a job description you're interested in, or use the samples in the participant materials. Joey Lopez · 2026 · [jrlopez.dev ]() [← home ]()· [bootcamp overview ]()· [participant materials ]()· [session 2 → ]()· [quick reference ]()· [facilitator guide ]()[.md ]()