AI Core Competency Series

AI Prototyping
Bootcamp

A two-day intensive that turns your PMs, designers, and other non-technical roles into AI-enabled builders — closing the gap between ideas and working software, and accelerating time to clarity across your product org.

2-Day Intensive On-site only Up to 10 participants
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team_outcomes

What Your Team Walks Away With

Lasting capability — not just awareness. Every participant leaves with working software, sharper judgment, and artifacts that immediately accelerate the work back at the office.

capabilities
✓

Practical experience building and iterating real ideas with AI coding agents — safely

✓

Working understanding of core delivery mechanics: versioning, environments, and deployment concepts

✓

Codebase literacy: review a codebase with an AI agent to validate feasibility, surface edge cases, and bring higher-fidelity options to engineering

✓

Living documentation: AI-assisted runbooks derived from the prototype and codebase, reducing tribal knowledge and drift between PRDs and what actually ships

decision_quality
✓

Clearer judgment on when work is ready for engineering or regulatory review

✓

Ability to identify where AI adds value vs. where it introduces risk

artifact_production
✓

Concrete, reviewable prototypes and handoff-ready materials: requirements, scenarios, and test cases

✓

Reusable playbooks and templates — prompts, skills, and workflows your teams can replicate to accelerate responsible AI adoption

curriculum

Workshop Agenda

Four focused sessions across two days — from foundations to a demo-ready prototype and delivery artifacts.

Day 1, Morning — Foundations & Tools
3 sessions
2h 50m
Orientation & Workstation Setup
Verify tool access (IDE + coding agent, GitHub, Netlify/Vercel, BaaS, AI tools), pick your prototype idea, and download starter materials. Checkpoint: everyone logged into every required tool.
60 min
What AI Prototyping Is (and Isn't)
Prototype vs. production scope, the language → working software loop, and building a reliability mindset. Micro-exercise: write 3 prototype success signals + 2 non-goals. Output: personal success-signal card.
40 min
Tools & Concepts
GitHub 101 (repo, commit, branch, PR in plain language) · Preview deploys & environment variables · Database basics (tables, seed data, schema) · Coding agents & IDE for non-devs (personalities, token usage, context windows, best practices). Checkpoint: explain each tool in your own words.
70 min
Day 1, Afternoon — Prompting, PRD & Build Sprint 1
4 sessions
4h 05m
Prompting Playbook
Prompt patterns: explore → decide → plan → execute → verify. Build and save 3 system prompts: CPO (problem framing + PRD slices), Design Lead (flows + UI assumptions), CTO (architecture + step plan + review). Output: personal prompt kit.
50 min
Idea → PRD → Design System
PRD slice: user + pain + hypothesis, MVP scope + non-goals, acceptance criteria, assumptions. Design System v0: tokens (colors, type, spacing), component inventory (button, input, card, modal, table), form patterns, loading/empty/error states, and the "design system contract" in the repo. Outputs: PRD slice + Design System v0 spec.
60 min
Build Sprint 1 — Planning & Execution
Guided flow: clone starter repo → create branch → review CTO plan → implement thin slice (basic page/flow, seed data, /design-system route stub) → push changes. Output: local running app + first commits pushed (ideal: preview deploy live).
90 min
Day 1 Share-out & Retro
Each person (60–90s): what you built, what's unclear, your Day 2 AI feature goal.
45 min
Day 2, Morning — Build Sprint 2 & Codebase Mapping
3 sessions
3h 10m
Day 2 Orientation
Recap Day 1 and align on Day 2 definition of done: AI workflow integrated, repo/system map completed, delivery packet produced, demo ready.
10 min
Build Sprint 2 — Agent-Driven Iteration
Evolve Sprint 1 into a demo-ready prototype: complete the happy path + loading/empty/error states, tighten the data model with realistic seed data, apply the Design System in code (tokens + shared components), and if AI is used, add guardrails (structured output, fallbacks, user messaging) + a debug view to inspect prompts/outputs during demos. Output: demo-ready prototype.
120 min
Codebase Exploration & System Mapping
Build a repo orientation page (how to run, entry points, routing, data flow, env vars, design system locations), a dependency inventory, and an impact map for one change. Outputs: repo orientation page + dependency/impact map.
60 min
Day 2, Afternoon — Delivery Artifacts & Personal Playbook
3 sessions
3h 20m
Generating Delivery-Ready Artifacts
Use AI to produce: test cases (happy/edge/error/accessibility), production-ready acceptance criteria, and implementation notes (files likely touched + risks). Output: delivery packet.
75 min
Day 2 Share-out & Retro (Demo-Heavy)
Each person (~8–10 min): problem + success signals, live demo (including AI feature), show one artifact (repo map or tests), and what you'd do next. Output: clear next steps and reusable artifacts.
95 min
Personal AI Operating System
Finalize default prompts (CPO/Design/CTO + codebase explainer + PR reviewer), finalize checklists (kickoff, design system, AI feature, PR hygiene), and write your 2-week action plan. Output: personal playbook + 2-week plan.
30 min
ideal_participants

Built for Non-Technical Teams

Designed to be run with a cross-functional cohort — the roles that shape what gets built, but don't write the production-ready code.

Product Managers

Stop waiting on engineering to validate ideas. PMs leave able to prototype, pressure-test assumptions, and hand off specs that engineers can actually build from.

Designers & Researchers

Go beyond static mockups. Designers and researchers leave able to build interactive prototypes and AI-enhanced flows that communicate intent far more clearly than Figma alone.

Strategists & Program Managers

Gain firsthand fluency in what AI can — and can't — do. Leave with the language and tools to drive AI adoption across your org without depending on technical translators.

delivery_options

Workshop Format

Two ways to run the workshop — pick the one that fits your team's setup.

option_a

Turnkey Delivery

You show up and build, zero IT lift, maximum reliability.

we_provide
  • MacBooks for all participants
  • Wireless network connection (workshop-ready)
  • Tool account setup & access provisioning
  • Full on-site setup, tear-down & troubleshooting
client_provides
  • Boardroom, power & projector
option_b

Collaborative IT Enablement

Your IT owns access; we run the workshop.

we_provide
  • Enablement checklist & readiness requirements
  • IT working session(s) to validate setup and access
  • Workshop delivery & in-session build support
client_provides
  • Approved laptops with required software installed
  • Network access, including allowlist/denylist adjustments as needed
  • IT point-of-contact during the readiness window
facilitated_by

Product Orchard Experts

PO

Product Orchard

// Product & AI Strategy Partners

We embed inside teams — not just teach at them. Our facilitators bring decades of product leadership across startups and Fortune 500 companies, and have helped organizations at every scale build AI-enabled workflows that stick. Every session is grounded in your real products, your real problems, and your actual roadmap.

get_started

Ready to make AI a core
team competency?

We run this on-site at your location, tailored to your org's context and roadmap. Up to 10 participants — small enough to stay hands-on, focused enough to drive real change.

Bring This to Your Team