AI
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 ...
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 ...
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 ...
Cline CLI 2.0 Turns Your Terminal Into an AI Agent Control Plane
Cline CLI 2.0 brings full AI coding agents to the terminal with parallel execution, headless CI/CD mode, and ACP editor support. Open source, any model ...
Google’s Conductor Now Reviews the Code it Helps You Write
Google's Conductor for Gemini CLI now reviews AI-generated code against your project standards. Agentic development just got a verification layer ...
Prompt Injection Isn’t Just a Chat Problem — It’s a DevOps Threat
Prompt injection is evolving into a serious DevOps threat, enabling AI agents to misuse tools, leak secrets and execute unauthorized actions unless governed with least privilege, sandboxing and human approval. ...
Forget the Vibe-Coders, We Need to Support Responsible AI-Assisted Development
Guillaume Moigneu | | AI in development, automated security, build pipelines, developer roles, Human Oversight, orchestration, responsible AI use, software design, Software infrastructure, spec codingWhile AI tools are increasingly used in development, they should enhance rather than replace human input. Developers must shift from merely writing code to orchestrating and validating AI-generated code. This 'spec coding' ...
Beyond Automation: How Generative AI in DevOps is Redefining Software Delivery
Albert Hilton | | AI risks management, automation, Code Generation, data privacy, DevOps transformation, DevOps workflows, GenAI in DevOps, generative AI, human-in-the-loop, productivity gains, software development, technical debtGenerative AI (GenAI) is revolutionizing DevOps by automating manual tasks, enhancing productivity, and reducing errors. By integrating GenAI, teams can streamline workflows and democratize expert knowledge. However, managing risks such as data ...
Former GitHub CEO Bets $60M That Developer Tools Need a Factory Reset for the AI Age
Tom Smith | | AI coding agents, AI-generated code, automation, Checkpoints, code governance, code review, collaboration, command-line tool, developer tools, devops, funding, software development lifecycleThomas Dohmke's new company, Entire, aims to redefine the software development lifecycle for AI-driven coding by focusing on post-code generation processes. With a $60 million seed round, Entire's first product, Checkpoints, enhances ...
CodeRabbit Adds DevOps Planning and Review Tool for AI Prompts
CodeRabbit today made available in beta a planning tool that enables DevOps teams to determine which artificial intelligence (AI) prompts to create and review before embedding them within their workflows. David Loker, ...
Will AI Kill the OSS Star?
Alan Shimel | | AI and OSS relationship, AI impact on open source, AI slop, AI-generated pull requests, apprenticeship model, coding ecosystem, collective understanding, community health, community interaction, custom code generation, documentation decline, economic shift, engagement drop, fragmentation risk, generative AI, licensing issues, long-term sustainability, open source challenges, open source maintenance, OSS market, software development trends, software security, standardization, technology evolution., vibe codingAs AI-driven development accelerates, open source software faces an uncomfortable paradox: Usage is rising while engagement, sustainability and community economics quietly erode. AI isn’t eliminating OSS, but it is reshaping how code ...
