Coder, a platform for AI Development Infrastructure, announced today that it has achieved the Amazon Web Services (AWS) DevOps and the Generative AI Competencies in the Agentic Tools Category. This specialization recognizes Coder as an AWS Partner that helps customers and AWS Partners drive the advancement of services, DevOps tools, and infrastructure pivotal for implementing generative AI technologies.
Achieving these Competencies differentiates Coder as an AWS Partner that has demonstrated technical proficiency and proven customer success, powering secure, consistent environments where humans and AI code together, trusted by leading enterprises worldwide. Coder possesses the experience and DevOps expertise shown from successful projects for addressing customer challenges using generative AI solutions as an enabler of their digital transformation strategies for augmenting the customer experience, delivering hyper-personalized and engaging content, streamlining workflows, and delivering actionable results powered by generative AI technology from AWS.
“Enterprises need infrastructure that enables secure AI development at scale without compromising governance or control,” said Rob Whiteley, CEO of Coder. “Achieving the AWS Generative AI and DevOps Competencies validates Coder’s commitment to helping enterprises and government agencies adopt AI-driven development workflows with the security, observability, and compliance controls they require. We’re focused on making it easier for organizations to build on AWS with confidence.”
The AWS Competency Program aims to assist customers in connecting with AWS Partners who possess extensive knowledge and technical expertise in using AWS technologies and best practices. These Partners facilitate the seamless integration and deployment of solutions to meet the unique needs of both startups and global enterprises.
Achieving the AWS Generative AI and DevOps Competencies reflects Coder’s focus on enabling secure, observable, and practical AI adoption in enterprise software development. Coder Tasks allows teams to run long-lived AI agents in dedicated, isolated workspaces, reducing repetitive development work such as bug fixes, documentation, and QA while giving agents access to real source code, developer tools, and GitHub context under enterprise controls. Agent Boundaries adds network isolation and detailed logging to limit risk from unpredictable agent behavior, preventing data exfiltration, prompt injection, and unsafe command execution without relying on brittle sandboxes or constant human approval. AI Bridge centralizes all AI usage across tools, agents, and models, providing identity-aware access, audit logs, and cost visibility while reducing API key sprawl and enabling organizations to govern and measure AI use consistently across teams.
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