Purpose
Prototyping converts ideas into tangible forms. It surfaces unseen challenges by making abstract assumptions visible. It allows the team to test how users react, what parts of the idea are weak, what technical/data/UX/ethical issues crop up. It reduces risk by making failure visible early.
For the organisation, a good prototype builds confidence (or disconfirms assumptions early), enhances shared understanding (because people can see and try), aids in refining direction, speeds learning, and supports more persuasive conversations with stakeholders or funders.
Outcome
-
A working prototype (mock‑up, simulation, wizard‑of‑Oz, etc.) representing the core of the selected idea.
-
A defined testing / feedback plan: who will test, what you will observe, what you will ask.
-
A list of gaps surfaced: data, technical constraints, UX or ethical issues that need addressing.
Tools
Prompt Mock-Ups What: Test AI behaviour by drafting prompts. How: Write prompts, run them, observe outputs. Why: Validates feasibility quickly.
Storyboards What: Visual user journeys. How: Sketch panels showing user, AI, outcomes. Why: Communicates flow simply.
Wizard of Oz Simulation What: Humans simulate AI behind the scenes. How: Team acts as AI engine during user testing. Why: Tests UX without building tech.
Paper/Digital Prototypes What: Low-fidelity mock-ups. How: Use paper, slides, or simple tools. Why: Cheap, flexible, fast.
KanBan / Product is People (Cloud) What: Visualise work and resources. How: Use KanBan boards to track prototype tasks. Or use Product-is-People thinking to map stakeholder involvement. Why: Keeps effort organised, highlights dependencies.
Walkrounds What: Physical review of prototypes in progress. How: Teams display outputs; others walk round, giving notes. Why: Encourages feedback culture.
Agility Adventure Maturity Model What: Gauge agility in handling prototypes. How: Self-assess team across agility dimensions. Why: Builds reflection, improves iterative working.