Introduction
- Welcome, course context and objectives
- Participant goals and expectations
- Overview of the spec-driven approach
Module 1: Foundations of Spec-Driven Thinking
- Common pitfalls of vague or unstructured prompting
- How structure and constraints influence AI outputs
- The role of specifications in reducing ambiguity
- Demonstration: comparing unstructured vs structured inputs
Module 2: Writing Effective Product Specifications
- Key components of a lightweight product specification
- Defining scope, user needs, flows and constraints
- Writing acceptance criteria that support reliable outputs
- Using templates to standardise how intent is expressed
Module 3: Spec-Kit Demonstration – From Specification to Artefacts
- Live walkthrough: inputting a structured specification into Spec-Kit
- Generating core artefacts:
- User flows
- User stories
- Acceptance criteria
- Task breakdowns
• Understanding traceability from specification to output
• Identifying gaps and inconsistencies in generated artefacts
Module 4: Applying the SPTI Workflow in Practice
- Introduction to the SPTI loop: Specify, Plan, Tasks, Iterate
- Translating specifications into actionable product work
- Using AI tools to support backlog structuring and refinement
- Generating test scenarios to validate product intent
Wrap-Up and Reflection
Exams and assessments
There are no formal exams in this course. Participants will complete a series of guided exercises and practical challenges, culminating in a fully worked example that demonstrates the end-to-end spec-driven workflow. Feedback is provided throughout by the instructor.
Hands-on learning
- Live demonstrations showing how specifications drive AI-generated outputs
- Guided exercises to create and refine product specifications
- Structured activities to generate and evaluate product artefacts
- Group discussions to analyse output quality and identify improvements
Why this course matters
AI tools are only as effective as the inputs they receive.
Teams that rely on loosely defined prompts often produce inconsistent or low-quality outputs. In contrast, teams that adopt a spec-driven approach create clarity, improve alignment, and generate outputs that are significantly more reliable and usable.
This course provides the practical skills needed to make that shift.
Outcome
Participants leave with a clear, structured approach to defining product ideas and generating aligned product artefacts using AI, enabling more consistent, efficient and reliable product development practices.
