The Problem

Software Development Is Broken

Most projects drown in accidental complexity, lose sight of business goals, and deliver at exponentially growing cost. Here is why.

Typical Issues

What goes wrong in every project

These problems are not exceptions. They are the norm across the industry.

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Exponential Complexity and Cost

Fast at start, then slower and more expensive as the codebase grows. Eventually you hear: "We need to refactor." "We need to start over." Every new feature costs more than the last.

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Lack of Business Focus

Too much time spent on technical decisions, too little on business value. The process is difficult to follow and predict. Developers struggle to explain the business problem they are solving.

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Overengineering

Microservices, complex architectures, exotic technologies, high cloud bills. You are not Netflix. Complicated stuff that nobody asked for, built because it seemed like best practice.

Death by Jira

Methodology-focused cargo cults. Ceremony over substance. For non-technical stakeholders: death by Jira tickets they cannot parse. Process replaces progress.

AI Without ROI

Difficult to leverage and scale AI in existing codebases. No measurable return on investment. The architecture was never designed for it.

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Long Sprint 0, No Value

Weeks or months of setup, tooling, and infrastructure before a single line of business logic ships. Sprint 0 stretches on with zero business value delivered.

Root Causes

Industry "best practices" that make things worse

The conventional approaches are not just ineffective. They actively cause the problems they claim to solve.

Shared Information Modeling

Organizes coupling, explodes complexity, and kills agility. Current-state modeling abstracts the past and hampers future evolution.

Layered Architecture and Clean Code

Organizes coupling and diminishes cohesion. Changes ripple across layers instead of staying contained. The opposite of what you need.

Shift Left Obsession

Decide everything upfront. Creates cognitive load, complexity, and overengineering. Locks in decisions before you understand the problem.

Aggregates

Carving in stone with the understanding and requirements of today. Kills agility by coupling your model to current assumptions.

TDD

Generates working tests but does not support proper design. Tests pass, but the architecture degrades. Confidence without quality.

Current-State Modeling

Abstracts away the past and blocks future evolution. You lose the history of how you got here and the flexibility to go somewhere new.

There is a better way

We solve these problems with a fundamentally different approach: business-first, AI-native, and built for linear cost.