AI
The Risk Profile of AI-Driven Development
Ilkka Turunen | | AI-generated code, AIBOM, autonomous development, autonomous security, challenge bottleneck, CI CD gating, cloud-native security, Dependency Management, GRC engineering, hallucinations, IDE controls, license compliance, machine speed enforcement, OpenSSF Gemara, Outdated Dependencies, policy based dependency selection, prompt level governance, review bottleneck, runtime transparency, SBoM, secure by default, shift left security, Software Supply Chain, threat modeling, transitive dependencies, trusted registries, typosquattingAnalysis arguing that AI-driven code generation accelerates dependency decisions and expands supply-chain risk, requiring shift-left governance, prompt-level controls, automated SBOM/AIBOM visibility, threat-modeling as engineering, and autonomous security to match autonomous development ...
Sorry, Charlie, StarKist Wants AI With Good Taste
Alan Shimel | | Accelerate, accountability, AI alignment, AI Governance, behavioral generalization, blameless postmortems, character in AI, constitutional alignment, Culture Change, devops, emergent misalignment, ethical AI, guardrails, incentive design, incentives, insecure code, interdisciplinary alignment, model disposition, model governance, moral behavior, safety engineering, site reliability engineering, training data culture, training pipelines, trustworthiness, virtuesA surprising AI experiment showed that feeding a model sloppy code didn’t just produce bad programming, it produced bad behavior. The result points to something philosophers and DevOps engineers have long understood: ...
JetBrains Launches Air and Junie CLI to Blend Traditional IDE with AI Agents
JetBrains has launched a new “agentic” tooling stack that pairs a multi‑agent development environment, Air, with a standalone, LLM‑agnostic coding agent, Junie CLI. If you know JetBrains, you probably know it for ...
The Observability Bill is Coming Due – and AI Wrote Most of It
Alan Shimel | | agentic telemetry, AI in development, AIOps, APM (Application Performance Management), CI/CD (Continuous Integration/Continuous Deployment), data management, data quality, devops, instrumentation, Logging Standards, observability, Sawmills, Signal-to-Noise Ratio, software engineering, technology innovation, telemetry management, Telemetry OptimizationObservability has always had a data quality problem. AI coding agents just made it catastrophically worse. Shimmy sits down with the co-founders of Sawmills to dig into why unmanaged telemetry is the ...
Gemini Code Assist Gets Agent Auto-Approve, Inline Diffs, and Custom Commands to Speed Up the Core Coding Loop
Tom Smith | | Agent Mode, AI coding agents, AI-assisted development, Auto Approve, code review, Context Drawer, custom commands, developer productivity, devops, Finish Changes, Gemini Code Assist, Google Gemini, inline diff, IntelliJ, Outlines, software lifecycle, VS CodeGoogle’s latest Gemini Code Assist updates focus on workflow, not hype: Agent Mode with Auto Approve, inline diffs, a Context Drawer, custom commands, Finish Changes, and Outlines streamline how developers review, trust, ...
Microsoft Azure Skills Plugin Gives AI Coding Agents a Playbook for Cloud Deployment
Tom Smith | | agent orchestration, AI coding agents, AI in software delivery, Azure automation, Azure cost optimization, Azure Skills Plugin, Claude Code, cloud deployment, devops, Foundry MCP, GitHub Copilot, guardrails, infrastructure as code, institutional knowledge, MCP Server, Microsoft Azure, platform engineering, VS Code agent pluginsMicrosoft’s new Azure Skills Plugin closes the gap between AI-written code and production deployments by packaging expert Azure knowledge as executable skills, backed by MCP servers for real infrastructure actions and AI ...
Anthropic Code Review Dispatches Agent Teams to Catch the Bugs That Skim Reads Miss
Tom Smith | | AI code review, AI coding agents, Anthropic Code Review, Claude Code, Code Review Automation, developer productivity, devops, Engineering Velocity, GitHub integration, Logical Bug Detection, multi-agent systems, Pull Request Automation, secure software development, software quality, software reliabilityAnthropic Code Review dispatches agent teams to find bugs in PRs. Multi-agent analysis, severity ranking, and inline fixes for Teams and Enterprise ...
Report: Lower Performing Software Engineering Teams Benefit More from AI
An analysis of 2,000 organizations worldwide finds that historically lower performing software engineering teams are seeing nearly a 50% improvement in lead time to delivery, a four times greater rate of improvement ...
GitHub Copilot Coding Agent for Jira Connects Planning to Pull Requests Without Leaving Your Workflow
Tom Smith | | assign issues, coding agent, context switching, developer tools, draft PRs, GitHub Copilot, innovation, integration, JIRA, planning, Productivity, workflowGitHub Copilot, the coding agent, now integrates with Jira. Assign issues to Copilot and get draft PRs — no context switching between planning and code ...
Can QA Reignite its Purpose in the Agentic Code Generation Era?
Tzvika Shahaf | | agentic AI, AI code generation, flaky tests, QA automation, sdlc, software testingAI-generated code is accelerating development but it exposes a deeper issue. Why deterministic infrastructure is becoming the foundation of agentic QA ...
Codenotary Previews AI Platform to Autonomously Detect and Remediate IT Issues
Codenotary is previewing a software-as–a-service (SaaS) platform that enables artificial intelligence (AI) agents it has developed to autonomously detect, prioritize, and fix security, configuration, and performance issues. Company CEO Moshe Bar said ...
Sonar Unfurls Framework for Managing DevOps Workflows in the Age of AI
Sonar this week launched an Agent Centric Development Cycle (AC/DC) framework that promises to modernize continuous integration (CI) in the age of artificial intelligence (AI) coding. Announced at an online Sonar Summit, ...
