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Most read news & articles within last 7 days
Anaconda Doesn’t Want to Be Just the Python Company Anymore
The question is no longer whether Anaconda wants to be more than the Python company. It is how much of the AI development stack DeSanto ultimately intends to own ...
Atlassian Extends AI Reach of Jira Into Agentic Engineering Workflows
Atlassian today extended the scope of tasks that artificial intelligence (AI) can automate directly from its Jira project management software, including assigning work to an AI coding agent. Initially, Jira integration with ...
xAI Open-Sources Grok Build Coding Agent After Cloud Upload Exposes SSH Keys, Repos
Tom Smith | | AI agent governance, AI coding agent, Apache 2.0, credential exposure, developer privacy, devops security, github, Grok Build, open-source coding agent, Repository Security, source code security, xAIxAI has published the full source code for Grok Build, its terminal-based AI coding agent, on GitHub under an Apache 2.0 license. The release lands three days after a security researcher showed ...
SmartBear Tightens Integration Between AI Coding and Testing Tools
SmartBear this week revealed it is narrowing the divide between coding and testing by integrating its platform with artificial intelligence (AI) coding tools. Sheryl Koenigsberg, senior vice president of product marketing at ...
HashiCorp Introduces tfpolicy, a Native Policy Framework for Terraform
Tom Smith | | Cloud Security, compliance automation, Hashicorp, HCL, HCP Terraform, infrastructure as code, Infrastructure Governance, OPA, Open Policy Agent, platform engineering, policy as code, Sentinel, Terraform, tfpolicyHashiCorp’s new tfpolicy framework brings native policy-as-code governance to Terraform using HCL and lifecycle-aware infrastructure checks ...
Why You Need AI Agent Security Validation in Software Testing
Engineering teams have been racing for the last two years to deploy AI agents that can find bugs faster than any QA team ever could. Autonomous testing agents can crawl through codebases, ...
From AI Hype to AI Assurance: How Engineering Teams Can Safely Ship AI-Enabled Software
Olamilekan Lamidi | | AI assurance, AI Governance, AI testing, generative AI, MLOps, software engineeringAI has moved very quickly from experimentation to production. A few years ago, many organizations were still asking whether AI could improve their products or internal workflows. Today, the question is different: ...
AI-Generated Code Is Cheap But the Context Infrastructure Behind It Is Not
Saqib Jan | | AI coding, context engineering, Enterprise AI, RAG, retrieval-augmented generation, vector databasesThe cost curve for generating code with AI has moved in one direction, and it has moved fast. What used to require a senior engineer's full attention for an afternoon can now ...
Ten Great DevOps Job Opportunities
DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience. Our goal in these ...
AI Moved the Bottleneck From Writing Code to Understanding and Trusting It
Ted Julian | | AI code generation, AI code security, AI coding tools, AI investment ROI, AI-generated code, application security, automated code review, code quality, code review, codebase visibility, compliance, dependency risk, developer productivity, devsecops, Engineering leadership, engineering metrics, engineering ROI, production incidents, pull request review, SCA, software composition analysis, software delivery, software development productivity, software governance, technical debtAI coding boosts velocity, but without stronger review, governance and codebase visibility, teams risk higher costs, security gaps and production failures. TL;DR ...
