A concept, explained

Essential complexity.

On the model that outlives the tools — from business architecture to code.

My through-line

From business architecture to code — end-to-end traceability.

Four areas shaped my career: software development, methodology, IT architecture and business architecture. I know all four.

The goal is always end-to-end continuity — from the business domain to implementation. Only the path there was expensive and hard for a long time.

The standard

A model captures a problem in its essential complexity — no more.

Capture the essential, leave out the unimportant. That is the real craft.

My standard for every model, for about 15 years.

Once hard — now easier

Before

UML · SysML · your own DSL

Powerful — but hard, specialized, expensive. Few can read it.

Today

AI understands natural language.

With the right meta-model: the facts as Markdown — cheap to create and maintain, readable for everyone.

Same precision — far less friction.

My approach

The Mental Model.

A structured knowledge base — I call it the Mental Model.

Facts as Markdown  ·  structured by a meta-model  ·  machine-readable

An example — Finance in a hotel system
many many one maybe one Folio Payment OrderItem Debitor PdfInvoice

Real model from LIKE MAGIC — Markdown + Mermaid

Folio
Financial account of a reservation — bundles all line items of a stay.
OrderItem
A single line item on the folio.
Payment
Payment that settles order items fully or partly.
Debitor
Who owes the bill — person or company.
PdfInvoice
The finalized invoice at check-out.

Every term in one sentence — no more, no less.

The payoff

One model that everything can be measured against.

Requirements use only terms from the glossary — one language, no synonyms.
Implementation validated against glossary + ADRs.
New terms must land in the glossary first — otherwise no merge.

Not documentation but an artifact to validate against — so that change gets cheaper and safer.

Why it matters now

The right context makes AI far more reliable.

A model like the Mental Model gives AI the right context: it does not eliminate hallucinations — but it shrinks the space where AI has to guess, moving it from guessing to grounded reasoning. The cleaner the structure, the better the context. In practice: the Mental Model as a context layer for AI assistants.

Where it is heading

The pendulum swings — back to spec-driven development.

From “no big design up front” to spec-first — because AI makes specifications fast and affordable.

For years upfront modeling was too expensive, so agile deliberately dropped it. That math has changed.

Takeaway

Tools come and go — the model stays.

The standard stays: capture essential complexity. Only now the path is open to everyone.

That is how I still build today: close to the code, but with the model in mind. Thank you.

Robert Blust Talks

Sprecher-Notiz