Modern development workflow

AI-assisted software development

Modern development. Less effort. Fair costs.

I use modern AI support in software development in a targeted and responsible way. This allows suitable programming tasks to be completed faster and more efficiently without compromising quality, control or experience.

When a solution can be created, reviewed and implemented cleanly with AI support, I am happy to pass the resulting time and cost advantage on to my customers.

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My approach

Long-term collaboration instead of maximum billing

My philosophy is simple: not to bill as much as possible, but to gain as many satisfied customers as possible.

I see software development as a long-term collaboration. Fair prices, transparent communication and clean results are more important to me than short-term maximum billing.

The goal is a win-win situation: the customer receives a functional and economical solution, while I gain customers who are happy to return and recommend my work.

Experience and responsibility

AI does not replace experience

For me, AI is not a replacement for expertise, but a tool within the development process. I also work with AI agents and MCP-based workflows, define tasks and requirements deliberately, and always review generated code and proposed changes in their technical context.

My many years of experience in software development, databases, interfaces, Windows applications, web systems and business software help me assess results correctly and implement them appropriately.

Targeted use

Where AI can provide useful support

Final responsibility for the technical solution, its quality and its use always remains with the developer.

Code generation for recurring tasks
Extensions to existing software
Troubleshooting and technical analysis
Code refactoring and modernization
Documentation and clear explanations
Database queries and interface logic
Creation and extension of tests
Development of technical solution approaches

Tools

AI and development tools, for example

Depending on the project, I use suitable tools as support. Product names are examples, not promises of a particular tool or outcome.

Area	Examples
AI-assisted development & agents	Cursor, OpenAI Codex, Claude Code, GitHub Copilot, MCP-based workflows
Analysis and conception	ChatGPT, Gemini, Claude
Development environments	Visual Studio, Visual Studio Code, Cursor
Quality assurance	Code review, tests, debugging, manual review
Version control	Git, GitHub, GitLab
Interfaces and automation	APIs, JSON, REST, database connections

Benefits for customers

Efficiency with professional control

Faster implementation of many suitable tasks
Lower costs for appropriate work
Modern, considered development methods
Review by an experienced developer
Transparent and fair billing
Practical solutions without unnecessary effort

Quality and data protection

Responsibility remains personal

Customer data, credentials and confidential information are not entered into AI systems without careful consideration. Data protection and confidentiality are considered when choosing an approach.

AI-generated code is reviewed, tested and adapted to the project. Not every task automatically becomes cheaper through AI: for complex requirements, analysis, architecture, quality assurance and experience remain essential.

Using AI where it provides real value

Not as a gimmick, but as a tool for efficient, modern and economical software development: with fair costs, good quality and reliable collaboration.

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