Agentic Coding describes the use of AI agents in software development. Unlike traditional coding assistants, they can take on entire development tasks and handle them in parallel. Developers increasingly take on the role of delegating tasks, orchestrating agents and reviewing results.
Agentic Coding can accelerate development processes, parallelize tasks and relieve development teams. The approach is especially relevant for companies that want to evolve existing software more efficiently, work through backlogs faster or scale their software development.
Yes. A key area of application is the further development of existing software. For this, repositories must provide sufficient context, clear structures and suitable testing capabilities so agents can work in them reliably.
Alongside technical infrastructure, suitable software repositories, shared development standards, governance and clear responsibilities are particularly important. Equally crucial is enabling teams to work effectively with coding agents.
The degree of autonomy should reflect the relevant risk. Clear permissions, human approvals, automated quality checks and traceable agent activities create a controlled framework for use.
Value is assessed using concrete software-development metrics. These can include development and review times, throughput, defect rates and the cost of using agents. A pilot with real development tasks provides a robust basis for deciding on further scaling.
