- Preface: Bring Rotten Apples
- AI Disclosure
- 1. Automate Sales
- Something to complain about
- 2. The Cost Curve Broke
- I threw a crazy idea at AI
- The meeting is not free
- Waiting used to look like progress
- Cheaper than the PowerPoint
- The rational first step changed
- 3. A Claim Surrounded by a Plan
- Solved does not mean easy
- The Emperor’s New Architecture
- The first million euros
- Evidence before dignity
- 4. DEAD Prototypes
- Describe
- Execute
- Attack
- Discover
- 5. Describe Enough to Be Wrong
- Start from evidence, not memory
- Do not interview the universe
- Execute before the nouns become official
- Let the machine misunderstand you
- Waiting is allowed
- 6. Attack the Thing
- “wdyt?” can be a serious question
- Attack before everyone becomes polite
- Let cheap intelligence throw first
- Attack behavior, not craftsmanship
- Rotten apples come in different shapes
- Keep it cheap enough to insult
- 7. Discover the Organization You Actually Have
- Some discoveries should remain unresolved
- Unknown is not the same as unfinished
- Quality becomes consequence
- The prototype can discover that the user was asking for the wrong experience
- Discovering that nothing is needed
- 8. The Finance Tapestry
- The first prototype succeeds
- The quick win that protects the problem
- A DEAD Prototype creates the counterfactual
- The second prototype gets smaller
- Five hundred columns are a symptom, not a diagnosis
- 9. The Seven-Department Fix
- Seven good business cases can still add up to the wrong system
- The human consequence is larger than headcount
- Strategy starts at the level above the use case
- 10. Slice Until the Question Is Cheap
- Slice the hypothesis before the solution
- Slice the solution independently
- A seam is not technical debt
- Slice by consequence
- Slice by context
- The next cheapest question
- 11. Brent Is Two Different Problems
- Six hours can become an email
- Sometimes the email exposes a line-management problem
- Unblocking the project does not remove the risk
- 12. CARE: Turning the Crazy Idea Into a Feature
- Give me the process
- Agent Not Ready and Generate Anyway
- Rotten apples that can be rerun
- The product changed while I was building it
- 13. Heroes of Legends: When the Wrong Category Works
- The card deck that should have been an army
- “Why does this view exist?”
- The enterprise version has better vocabulary
- 14. Self-Service Understanding
- Lara reaches Architecture with a real question
- Business is very good at noticing wrongness
- The handover can be almost embarrassingly small
- Kill the code; keep whatever mattered
- 15. Consulting When the Client Can Ask the Machine Too
- Your PowerPoint now has competition
- “AI competence” is too small
- Strategy has to survive execution
- Weak consulting is about to become painfully visible
- 16. Practicing DEAD Prototyping Without Killing It
- Start with the thing that is bothering you
- Give the machine enough rope
- Attack before you beautify
- DEAD requirements are the best requirements
- Do not turn every discovery into a backlog item
- Let brainfarts die cheaply
- Stop when the conversation became better
- 17. The Potential You Are Leaving on the Table
- Your project plan was shaped by an expensive Build phase
- Handoffs become harder to justify
- Scarce people can stop attending meetings just in case
- Budget can move to the right of evidence
- Engineering starts trespassing into management
- If all you got was faster coding, you left most of it there
- 18. Give Me a DEAD Prototype
- Epilogue: Do Not Start a DEAD Transformation
- Ask for evidence without asking for ceremony
- Ask which Brent problem you have
- Keep brainfarts socially cheap
- Do not measure DEAD Prototyping adoption
- And please do not make this book a requirement
- Appendix A: A Pocket Reminder, Not a Standard
- Appendix B: What Might Survive
- Appendix C: This Did Not Start With AI
Prototyping is DEAD
AI is Killing it
This book is 95% completeLast updated on 2026-09-13
Your manager calls you into a meeting. Everyone is cheerful. The Head of Sales is there. “We heard AI is really useful for boosting productivity. We’d love to explore how it can help us in Sales.” Your manager agrees. “This is the perfect pilot. Please give us a concept until next week so we can see what we can do.”
The follow-up arrives quickly. Sales is overloaded. Everyone is busy serving customers. Nobody has time for a workshop, but they do have Sales.xlsx. That is what you get. The clock is ticking.
And then you open Sales.xlsx.
You have nothing. No requirements, no workflows, not even a proper data model. What you have is a snapshot of the messy reality Sales is dealing with every day. Customer names, contacts, opportunity values, dates, products, notes, colors that apparently mean something, and a field called Status_Final_2, which tells you enough about its history that asking about Status_Final_1 would probably ruin the afternoon.
And then it strikes you: they are not even using the CRM. You do not know why. Nothing you know from IT seems to apply in Sales, and they do not particularly care. They have customers to serve. Whatever happened between the shiny CRM rollout and this spreadsheet happened years ago. Today, Sales.xlsx is the truth.
And now, just because AI promises productivity, they are asking for the benefits.
How is that even supposed to work?
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About
About the Book
Prototyping is DEAD is about what happens when AI changes the economics of software development.
AI turns the entire rationale behind the traditional Software Development Lifecycle upside down. We're not aiming at "cheaper development," or "faster delivery" in the existing process.
We're not selling AI as some form of black magic that makes professional development disappear: We're targeting all of the stuff that was only necessary because building software was the most expensive and risky part.
And that's only possible if we challenge the how and why behind every activity in traditional development.
We're talking systemic leverage - not token economics versus hourly rates.
For decades, building was the most expensive activity. So organizations optimized everything that happened before Build: feasibility study, scoping, discovery workshops, solution analysis, architecture, estimation, budgets and approvals. The goal was to remove as much uncertainty as possible before scarce engineering capacity was consumed - to avoid the waste of building the wrong thing.
AI breaks that logic.
What if building software is faster than getting a budget?
What if tests are conclusive before there's a requirement?
What if users could tell you where the solution is wrong when nobody knows what is right?
When it becomes cheaper to build something executable enough to discover that you are wrong than to spend weeks discussing the theory, the sensible starting point changes. Plan → Build → Run becomes Build → Run → Plan.
That is the idea behind DEAD Prototypes: Describe. Execute. Attack. Discover.
A DEAD Prototype is not an early product. It is a cheap executable interpretation of what you currently think is true. You build it so people can attack it, expose bad assumptions, reveal missing knowledge, discover category errors and kill stupid solutions before they become projects.
The book draws from enterprise software, consulting, product development and the strategy game Heroes of Legends. Along the way it looks at overloaded Sales teams, broken support processes, hidden factories, key-person bottlenecks, useless-but-functional software, AI coding, and why organizations often polish details while ignoring the fact that they are solving the wrong problem.
The point is not to introduce more AI.
It's to stop wasting expensive human attention on ideas that should have died cheaply.
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Author
About the Author
Michael Küsters
Michael Küsters has seen most sides of business: startup, SME, scale-up and enterprise; developer, consultant, manager and C-level executive.
His work includes TOP Structure, CARE, VXS, Heroes of Legends, and several books about Agile and organizational change. Across all of them, the recurring theme is the same: ideas are cheap, systems are messy, and bad ideas become dangerous once they acquire momentum, status and budget before reality gets a chance to object.
He takes most things with humor.
Waste and institutionalized stupidity are not on that list.
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