Nexonoma Evolve

Agentic Engineering: Maturity states

Assess the maturity of agentic software engineering through observable operating practices, sustainable enablers, and early overload signals, and identify the next responsible development step.

Maturity states

Selected state · 01

Experimental

Individual, deliberately bounded use cases create room to learn without making the regular delivery process dependent on agentic workflows.

How the system operates

People select the task and context, accompany every run, and review every result. Autonomy and blast radius remain small.

Supporting enablers in the knowledge graph

CONCEPT

Context Engineering

The deliberate design of the information context an AI system receives for a task.

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CONCEPT

Agentic Coding Tools

A comparison group for tools that plan, execute, and verify software tasks agentically in a repository.

Open in Explorer

Overload signals

Agentic use expands to more tasks before the pilot's results and failures have been evaluated.

Ready for the next state when …

A valuable use case can be repeated with similar context and comparable quality.
Blast radius, approvals, and stop conditions are explicit and understood by the team.