Technology Innovation Workshops (Intermediate Level)

DAY 1: FOUNDATIONS OF INNOVATION IN THE AI ERA

 

Module 1. OPENING AND CONTEXT

 

Introduction, agenda, and workshop principles

• Getting to know each other and agreeing on ways of working
• Quick poll: participants’ experience with innovation and AI in their organizations

What is innovation? — A broader perspective

Definition of innovation: value, feasibility, and time to market

• Types of innovation: incremental vs. breakthrough vs. disruptive
• How AI has transformed the third dimension — time: from months to hours
• But: AI is a random machine — creativity remains on the human side
• The new economics of experimentation — the cost of failure has dropped dramatically
• Case studies: companies that have accelerated innovation through AI
• Exercise: Mapping your own innovation process — where are the bottlenecks?

 

Module 2. THE CREATION PHASE — IDEA GENERATION

 

Idea generation techniques — traditional methods + AI

Brainstorming: principles, pitfalls, and how to run it effectively

• De Bono’s Six Thinking Hats — six perspectives on thinking
• Creativity in three steps
• NEW: AI-assisted brainstorming — ChatGPT as an idea generator, Claude as an analyst
• NEW: Prompt chaining — how to build complex chains of reasoning with AI

Workshop 1: Creative Session

Groups of 4–5 participants work on a real-world challenge.

• Round 1: Traditional brainstorming (15 min)
• Round 2: AI-assisted brainstorming using ChatGPT and Claude (15 min)
• Comparing and discussing the results of both approaches (15 min)

 

Module 3. THE SELECTION AND VALIDATION PHASE

 

From idea to decision — selection and validation

• The Tenth Man — the principle of deliberate dissent
• NEW: “AI as the Tenth Man” — using Claude to systematically challenge assumptions
• The OODA loop (Observe–Orient–Decide–Act) in the context of AI
• NEW: Research with Gemini and Perplexity — real-time market validation
• Value/effort matrix supported by AI-based estimation
• Discussion on moving from an idea to implementation and estimation

Workshop 2: Idea Selection and Validation

Each group selects one idea from the creative session.

• Applying The Tenth Man + AI Tenth Man to challenge and test the idea
• Using Gemini/Perplexity for rapid market research
• Presenting a “go/no-go” decision with justification

 

Module 4. PLANNING AND MEASUREMENT

 

From idea to plan — making it realistic

How to move from a “brilliant idea” to a realistic action plan.

• AI-assisted estimation: different cost and time perspectives
• Defining measurable success criteria
• NEW: Using AI to identify risks and blind spots

Day 1 Summary and Introduction to Day 2

Key takeaways — what works and what is surprising

• Evening assignment: reflect on the idea to be prototyped
• Preview of Day 2: “Tomorrow, we build.”

 

DAY 2: AI-POWERED INNOVATION — FROM IDEA TO PROTOTYPE

 

Module 5. AI TOOLS IN PRACTICE

 

Recap of Day 1 and plan for Day 2

A quick summary and warm-up.

Overview of AI tools for innovation — deep dive

Guiding principle: humans = creativity, AI = rapid execution

• AI as a statistical machine — what this means in practice and why it hallucinates
• Language models — which one to use and when?
• Gemini + Perplexity: research, trend analysis, and fact gathering
• ChatGPT (OpenAI): creativity, brainstorming, and content generation
• Claude (Anthropic): coding, document analysis, and precise reasoning
• Prototyping tools: Claude Code, Cursor, GitHub Copilot, v0.dev, Bolt, Lovable
• Research tools: Gemini Deep Research, Perplexity, Claude with web search
• Hands-free prompting — dictation on macOS as a natural way of working with AI
• SNAG — visual debug capture for AI agent workflows (live demo + installation)
• Live demo: a complete cycle — idea → research → prototype in 20 minutes

 

Module 6. PROMPT ENGINEERING FOR INNOVATORS

 

Prompt engineering — how to communicate with AI

The anatomy of a good prompt: context, task, format, and constraints.

• Advanced techniques: chain-of-thought, few-shot, role prompting
• System prompts and Custom Instructions — configuring AI for a specific task
• Differences in prompting: Claude vs. ChatGPT vs. Gemini
• Hands-free prompting — dictation on macOS as a natural interface for AI
• Hands-on: participants optimize prompts for their own use cases

Exercise: Prompt Battle

Pairs of participants compete to see who can prompt a better solution.

• Voting for the best approach

 

Module 7. THE MAIN WORKSHOP — FROM IDEA TO PROTOTYPE

 

Workshop briefing

• Dividing participants into groups and selecting challenges/ideas
• Rules: what we want to achieve in 2.5 hours

Phase 1: Idea Generation and Selection

• AI-assisted brainstorming with ChatGPT (using techniques from Day 1)
• Rapid validation with the AI Tenth Man (Claude)
• Selecting one idea for prototyping

Phase 2: Research and Market Validation with AI

• Competitive analysis using Gemini and Perplexity
• Defining the target audience and value proposition
• Identifying risks and assumptions that need to be validated

Phase 3: Building a Prototype with AI

• Technical groups: building a prototype with Claude Code / Cursor (working code)
• Non-technical groups: creating a landing page, mockup, or presentation using AI
• Testing with SNAG — capturing bugs and feedback in real time
• Hands-free prompting in practice — dictating instead of typing
• The trainer moves between groups, providing live mentoring

 

Module 8. PRESENTATIONS, REFLECTION, AND CLOSING

 

Demo Day — Prototype Presentations

Each group presents:

Problem → Idea → Prototype (7 minutes per group)

• Feedback from the other groups and the trainer
• Voting for the “Most Innovative” and “Best Executed” prototype

Risks and Limitations of AI in Innovation

• AI is a random machine — hallucinations, false confidence, and fabricated facts
• Controlled creativity: humans guide the process, AI is the tool
• Verification techniques: cross-validation, fact-checking, and “trust but verify”
• The “vibe coding trap” — a prototype ≠ a product. What comes next?
• Data privacy, intellectual property, and compliance when using external models
• Bias in AI — how not to be led astray
• AI ethics in the context of organizational innovation

Summary and Action Plan

• Key takeaways from both days
• Individual action plan: “3 things I will implement on Monday”
• Resources for further learning and experimentation
• Q&A session and closing