What Is AI-Driven Software Development and How Does AI Coding Work?
At its core, AI coding is based on the interplay between powerful language models and specialized coding assistants. The models – currently most notably Claude Opus by Anthropic – provide linguistic and logical understanding. The coding assistant orchestrates these models, integrates tools such as tests, builds, or logs, and retrieves project-specific context.
For successful AI coding, several factors are crucial:
- the quality and freshness of the model
- the ability to understand large codebases
- tool integration (tests, build pipelines, logs)
- support for project-wide rules and instructions
The most widely known AI coding tool is GitHub Copilot. Other common solutions on the German market include Cursor, Claude Code, Windsurf, Kilo Code, Tabnine, and JetBrains AI Assistant.
An AI coding assistant can:
- create implementation plans
- search for and integrate suitable libraries
- implement features and tests
- analyze and fix bugs based on logs
- extend documentation, and much more
Coding assistants support developers throughout the entire development process. As a result, roles are shifting: instead of manually writing every single line of code, developers can focus on creative work. Meanwhile, the coding assistant continues working while the team tests new ideas in parallel. This makes it possible to drive multiple features forward at the same time – human and machine as a “perfect match.”
How companies can benefit from AI coding and which success factors are key is explained in the full blog post by our IoT specialist, Device Insight:
