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Claude Code Security Finds the Bugs That Static Analysis Can’t — and Wall Street Noticed
Claude Code Security scans code like a human researcher, not a rule engine. Anthropic found 500+ decade-old bugs — and cybersecurity stocks felt it ...
Five Great DevOps Job Opportunities
Mike Vizard | | DevOps architect jobs, DevOps careers, DevOps integration specialist, DevOps job market, devops jobs, high paying DevOps roles, senior DevOps engineer jobsBrowse our weekly DevOps jobs report highlighting high-paying DevOps roles from leading companies including Pax8, JPMorgan Chase, Major League Baseball and more. Explore current opportunities and insights into the DevOps job market ...
Survey: Adoption of AI Software Testing Slowed by Trust Issues
A new global survey from Leapwork underscores a growing tension in software development: while AI is widely viewed as essential to the future of testing, many teams remain hesitant to rely on it for ...
AWS Just Turned “Deploy to AWS” Into a Five-Word Prompt
AWS Agent Plugins give coding agents the skills to architect, estimate costs, and deploy to AWS. Type "deploy to AWS" and the agent handles the rest ...
When DevOps Meets the Cloud: A Real-World Transformation Story
Yashwanth | | CI/CD Automation, cloud migration, DevOps transformation, infrastructure as code, observabilityA real-world DevOps and cloud transformation story showing how automation, observability, and cultural change improved reliability and delivery ...
Why AI Makes Requirements a Runtime Artifact
Tom Hollowell | | AI behavior, AI Governance, AI requirements, continuous verification, MLOps, model drift, production monitoring, requirements traceability, runtime constraintsIn traditional software, requirements are static design-time artifacts. In AI-enabled systems, they must be continuously observed and enforced in production. Learn how AI collapses the boundary between design-time and runtime, shifting requirements ...
What to do About AI’s Forced Rethink of Reliability in Modern DevOps
Leo Vasiliou | | Agentic Workflows, AI monitoring, AI observability, AI reliability, AI. analytics, business impact, CDNs, customer churn, devops, digital experience, experience-driven resilience, incident response, internet stack, KPIs, latency, LLM applications, model drift, monitoring tools, NPS, observability, performance, performance degradation, reliability, reliability strategy, revenue, SaaS, site reliability engineering, SLIs, SLOs, SRE Report 2026, Third-party Dependencies, trust, uptime, user experienceAs systems become more distributed and AI-driven, traditional uptime metrics are no longer enough. The 2026 SRE Report shows how reliability is shifting toward user experience, speed, and business impact, and how ...
Test Automation Strategy for Growing Software Teams
Build a scalable test automation strategy that improves release speed, reduces defects, and supports growing software teams ...
Checkmarx Extends Vulnerability Detection to AI Coding Tool from AWS
Checkmarx this week revealed it has added support for the Kiro artificial intelligence (AI) coding tool provided by Amazon Web Services (AWS) to its Checkmarx Developer Assist that leverages AI to surface ...
GitHub Tests AI Agents to Handle Repository Upkeep
GitHub is introducing a new approach to streamline developer workflow, offering AI agents that can shoulder the repetitive tasks that accumulate inside code repositories. Known as Agentic Workflows, the feature is available ...
What a ‘Good Plan’ Really Means for AI Coding Agents
Michael Parker | | Agile methodologies, AI coding agents, application delivery, CI/CD pipelines, coding efficiency, context retention, continuous improvement, Engineering best practices, error management, modernization, planning in development, software development, task execution, validation processesExplore how AI coding agents are transforming software development. This article discusses the importance of clear objectives, runnable tasks, and continuous validation in planning to ensure that the transition from idea to ...
Tool Fragmentation is Breaking Delivery Context — Here’s What Teams are Learning
Arul Watson | | access control, application security, automation, CI/CD pipelines, Cloud Security, credential exposure, Cybersecurity, devsecops, incident response, risk management, secrets management, security best practices, supply chain security, token managementExplore the emerging crisis in application delivery caused by tool fragmentation in modern software development. This article discusses the need for semantic interoperability, context preservation, and a shift from linear pipelines to ...
