Artificial Intelligence
Coder Launches AI Maturity Self-Assessment To Help Enterprises Benchmark Agentic AI Adoption In Software Development
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The free assessment gives engineering teams a clear view of AI maturity so they can align leadership, manage risk and plan the next phase of software innovation
AUSTIN, Texas, Jan. 29, 2026 (GLOBE NEWSWIRE) -- Coder, the leader in self-hosted AI development infrastructure for the enterprise, today unveiled its AI Maturity Self-Assessment, along with an AI Maturity Curve, designed to help organizations evaluate how effectively they are in adopting AI within enterprise software development. Together, these resources provide a practical framework for understanding progress as engineering teams move from ad hoc AI usage to more structured, governed and scalable agent-driven workflows..
As AI tools and agents become embedded across the software development life cycle, adoption inside engineering organizations is accelerating, but often without consistent oversight. Despite increasing pressure to accelerate AI adoption, many engineering teams remain stuck in fragmented experimentation. Without a shared understanding of maturity, AI adoption in software development can quickly outpace policy, security and platform controls. This gap makes it difficult for engineering leaders to prioritize investments, demonstrate progress to executives or safely expand the use of AI agents beyond limited pilots.
“As AI agents take on more responsibility inside engineering workflows, organizations need a clearer, more tangible way to understand maturity and governance readiness,” said Eric Paulsen, Field CTO at Coder. “Without that baseline, it becomes difficult to scale agentic AI safely or predictably. Our self-assessment gives teams a concrete view of where they stand, so they can plan adoption intentionally, manage risk and scale with confidence.”
Coder’s AI Maturity Curve helps organizations frame progress from early experimentation with AI-assisted coding to more advanced, governed use of agents across development workflows. The AI Maturity Self-Assessment builds on this framework by benchmarking maturity across development practices, operational controls and governance readiness. The free, online tool maps responses to the maturity curve, helping organizations understand their current states, identify gaps and plan next steps for scaling agentic AI.
Engineering leaders and platform teams are encouraged to take the assessment and download the maturity curve resource to support internal evaluation, leadership discussions and planning for the next phase of AI-driven software development.
About Coder
Coder is the leading open-source platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows—without sacrificing security, compliance, or performance. Learn more at coder.com.
Media Contact
Jennifer Tanner
Look Left Marketing
coder@lookleftmarketing.com
Photos accompanying this announcement are available at:
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Frequently Asked Questions
What is Coder's AI Maturity Self-Assessment?
Coder's AI Maturity Self-Assessment is a free, online tool designed to help organizations evaluate their effectiveness in adopting AI within enterprise software development, benchmarking maturity across development practices, operational controls, and governance readiness.
Who should use the AI Maturity Self-Assessment?
Engineering leaders and platform teams are encouraged to use the assessment to support internal evaluation, leadership discussions, and planning for the next phase of AI-driven software development, especially for safely scaling agentic AI.
How does Coder's AI Maturity Curve complement the self-assessment?
The AI Maturity Curve helps organizations frame their progress, from early experimentation with AI-assisted coding to more advanced, governed use of AI agents across development workflows. It provides a visual guide for understanding their current state and planning future steps in conjunction with the self-assessment.
First published on Fri, Jan 30, 2026
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