Method

INSODEMA begins before software begins.

The method explains how observation becomes research, how research changes understanding and how understanding drives architecture.

Research changes understanding. Understanding drives architecture. Architecture enables systems designed to evolve.

01

Observation

Reality comes before assumptions.

INSODEMA starts by observing how work actually happens: constraints, exceptions, decisions, repeated failures and patterns that are often invisible in formal process descriptions.

Input: field reality, domain experience, operational signals Output: documented problem context
02

Research

Problems are explored before solutions are defined.

Research collects observations, clarifies terminology, identifies recurring structures and separates symptoms from causes. It prevents software from being built around a weak or incomplete model.

Input: observations, documents, interviews, datasets, prior knowledge Output: structured findings and research notes
03

Understanding

Information becomes useful when it explains decisions.

Understanding connects facts, constraints and trade-offs. The goal is not to collect more information, but to know what matters, why it matters and how it changes the decision space.

Input: research findings and contextual knowledge Output: decision logic, boundaries and priorities
04

Architecture

Understanding is translated into structure.

Architecture defines the boundaries, modules, flows, data structures and responsibilities that allow a system to be implemented without losing the reasoning that created it.

Input: decision logic, constraints, operating model Output: system model, interfaces and implementation direction
05

Systems designed to evolve

Stable by design. Adaptable through controlled architecture.

The delivered system remains stable in operation. Its architecture is modular and maintainable, so an understood new requirement can be reviewed, implemented and released without rebuilding the entire system.

Input: architecture and implementation capability Output: stable systems with controlled paths for adaptation

Controlled adaptation

Evolution describes architectural readiness, not autonomous change.

Systems designed to evolve do not continuously rewrite themselves. Change remains deliberate, traceable and subject to human responsibility, review and release control.

Modular architecture shortens the path from an understood requirement to a controlled implementation while preserving operational stability.

Traceable decisions

The model comes before the code.

Important decisions are discussed, documented and translated into architecture before implementation.

This keeps the work traceable and reduces the risk of software drifting away from the underlying research.

Method references

Related principles stay close to the core method.

Principles

Public principles that explain how research, responsibility and architecture are handled.

Read principles

Method Repository

Structured public method material and deliberately limited research references.

Open repository

26 Steps Back

A thinking principle for moving backwards through assumptions, decisions, processes and architecture.

Inspect the principle

Why this matters

Systems fail when they are built around shallow understanding.

Less assumption

The method reduces the risk of building around untested assumptions, incomplete requirements or fashionable technology.

Better decisions

By making decision logic visible, systems can support judgment instead of hiding complexity behind screens.

Longer life

Architecture built from understanding can accommodate controlled change more safely than software built from disconnected feature requests.