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Software development · Architecture · AI agents · Quality

Software development with AI agents.

Coding agents now support planning, implementation, revision and verification – even in extensive codebases. This allows custom applications to be developed significantly faster. The prerequisites are clear requirements, a robust architecture and consistent quality control.

Software architecture, engineering management and hands-on delivery work together – so higher development speed results in reliable software.

Discuss your software projectSee the approach

Coding agents are changing software development.

Code is produced faster. Architecture and technical leadership determine its quality.

Modern coding agents handle complex implementations, analyse existing codebases and support reviews and testing. This makes code available faster. Whether it becomes good software still depends on clear requirements, a robust architecture and consistent quality control.

  • 01

    More delivery in the same time

    Multiple agents can implement features in parallel, examine existing systems, fix defects and keep technical documentation up to date.

  • 02

    Agents need direction

    Clear goals, bounded work packages and binding quality rules ensure that agents work in a coordinated and traceable way.

  • 03

    Architecture before prompting

    Module boundaries, data models and interfaces shape software over the long term. A good prompt cannot replace missing technical decisions.

  • 04

    Review and accountability

    Results are checked against requirements, architecture, security policies and tests. Accountability for the production solution remains human.

New possibilities

Custom software becomes economical for more tasks.

Coding agents reduce development effort. Where SaaS products or no-code platforms represent a business process inadequately, a purpose-built solution can now be the more sensible alternative.

  1. 01

    Internal tools

    Applications for calculations, approvals, data maintenance or reporting represent internal workflows directly – without introducing an additional standard product.

  2. 02

    Domain-specific web apps

    Web applications represent domain workflows with precisely the functions and data that employees or customers need in their daily work.

  3. 03

    Mobile applications

    Mobile apps for field service, logistics and support, as well as consumer apps for end customers – developed for the specific use case and straightforward operation.

  4. 04

    APIs and integrations

    Clearly defined APIs connect existing systems and make data and functions available wherever other applications need them.

  5. 05

    Agent-supported workflows

    Applications provide context, data and tools. AI agents use them to coordinate clearly bounded work steps within defined limits.

  6. 06

    From prototype to production solution

    Prototypes start on an extensible technical foundation and can be expanded step by step – without having to start again later when platform limits are reached.

Testing pyramid

Trust grows when quality becomes verifiable.

Coding agents generate a great deal of code in a short time – and can consistently carry incorrect assumptions forward. A layered test suite therefore verifies functions, interactions and user journeys at several levels.

Review✓

Broad unit tests form the foundation, integration tests verify how components work together, and business-verified end-to-end tests protect the critical user journeys.

  1. 01

    Unit tests

    Unit tests examine business rules, functions and edge cases in isolation. Coding agents can build this foundation quickly and broadly. Meaningful test cases matter more than high code coverage alone.

  2. 02

    Integration tests

    Integration tests examine interfaces, databases, external services and modules working together. They expose defects at transitions and within data flows.

  3. 03

    End-to-end tests

    Focused end-to-end tests with Playwright examine the most important user journeys across the complete system. Agents support their creation; people verify the business acceptance criteria.

Approach

Develop faster. Protect quality systematically.

Coding agents accelerate delivery, but they need a clear framework. Binding specifications, a robust architecture and verifiable results keep development under control.

  1. 01

    Clarify requirements and acceptance criteria

    Business requirements, relevant data and measurable acceptance criteria are clarified together. The resulting specification provides a binding foundation for people and agents.

  2. 02

    Define the architecture and structure the work

    Technologies, system boundaries, interfaces and security requirements form the technical framework. Tasks are bounded so agents can handle them independently and integrate them reliably.

  3. 03

    Implement and verify iteratively

    Coding agents implement bounded features, tests and documentation. Results are continuously integrated, reviewed from a business perspective and evaluated against architecture and quality standards.

  4. 04

    Put into operation and evolve

    Automated deployment, monitoring and telemetry make behaviour and defects visible. New requirements can then be implemented in a controlled way on this foundation.

Technologies

Technology follows the product.

The stack is determined by usage, integration needs and long-term operation. For mobile applications, the specific use case determines whether to use a shared Flutter codebase or direct development with Apple’s or Google’s native frameworks.

More about AI agent development

  • Web apps with Angular

    Developed by Google, this web framework is suitable for substantial applications that represent complex business processes and need to evolve over the long term.

  • iOS and Android apps with Flutter

    Developed by Google, this app framework enables iOS and Android applications from a shared codebase. Both versions can be developed and maintained in coordination.

  • Native iOS apps with SwiftUI

    SwiftUI is Apple’s own framework for native user interfaces. It directly supports Apple’s recommended interaction and design concepts. Fewer external dependencies also reduce potential maintenance and security risks.

  • Native Android apps with Jetpack Compose

    Jetpack Compose is Google’s own framework for native Android user interfaces. It supports current Android concepts and recommended best practices close to the platform. Reliance on external frameworks is deliberately kept low.

  • Backend services with .NET

    ASP.NET Core is an established backend framework with a large ecosystem, extensive documentation and proven architectural patterns. It is a solid choice for long-lived applications that need to be maintained and evolved reliably.

  • Services and automation with Go

    Go combines simple, readable code with high execution speed. Its low memory requirements and short startup times are particularly well suited to cloud services. The clear language also simplifies development with coding agents and the subsequent review of generated code.

Selected projects

Software development in practice.

Examples of modern web, app and backend architectures from real projects.

First step

Let us clarify what makes sense for your initiative.

In the initial conversation, we consider the process, the desired outcome and the systems that need to be integrated. This reveals whether custom software is the right solution and where coding agents can meaningfully accelerate development.

Discuss your software project
Roberto De Simone
“Coding agents make software development faster. What matters is ensuring that architecture, quality and long-term maintainability keep pace with that speed.”
Roberto De Simone