Harness today launched a code repository service that is specifically designed for DevOps teams that are relying on artificial intelligence (AI) agents to generate code. Martin Reynolds, Field CTO for […]
How to Build a Durable Change-Control Gate for AI Agents
AI agents that trigger real-world changes need more than confidence scores. A durable change-control gate should recheck policy, require approval for consequential actions, enforce idempotency and verify the result before retrying.
Production Validation: The Missing Layer in Enterprise Releases
Production validation adds a critical business-control layer between testing and deployment, combining data checks, exception review, approvals, reconciliation and operational readiness before a release reaches production.
Tricentis Preps Wave of Additional AI Testing Capabilities
Tricentis is providing early access to multiple artificial intelligence (AI) capabilities that it is gearing up to roll out later this year via a Tricentis Transform initiative, including an autonomous […]
The Missing Runtime for Long-Running AI Agents
Enterprise AI agents need more than stronger models. They need durable execution environments that can coordinate multi-step workflows, survive failures, pause for human review and resume reliably after disconnects or […]
Automated Diagnosis Isn’t Automated Understanding: What Postmortems Teach Us About Building Trustworthy Incident AI
AI incident tools can reduce alert noise, but real root-cause diagnosis requires causal reasoning, live dependency context, uncertainty handling and strong postmortem data.
AI Can Generate Your Infrastructure. Can Your CI/CD Pipeline Trust It?
AI-generated infrastructure code is exposing a growing security gap, pushing platform teams to add stronger automated gates, provenance tracking and human review before Terraform, Kubernetes and CI/CD changes reach production.
Your AI Coding Budget Is Becoming a Variable Cloud Bill
AI coding assistants are becoming a variable, usage-based engineering cost, forcing platform and DevOps teams to apply FinOps practices to models, credits, utilization and multi-vendor spend.
Is Java Enterprise Ready for AI? Absolutely
AI is transforming software engineering. For enterprise Java developers, the key question is whether Java and Jakarta EE are prepared to integrate AI into enterprise applications. The answer is yes. […]
CI/CD for AI-Enabled Applications: Why Traditional Deployment Pipelines Need to Evolve
Traditional CI/CD pipelines are optimized around a familiar assumption: source code changes, automated tests validate the change, a build artifact is produced, and the application is promoted through environments. AI-enabled […]
