AI
Black Duck Extends Scope and Reach of Code Scanning Tool
Black Duck has updated its Coverity static analysis code scanning tool to provide deeper integrations with artificial intelligence (AI) tools along with updates to its user interface that make it simpler to ...
The End of Manual Triage
Neel Shah | | agentic SRE, AI-powered SRE, Aiden for SRE, alert enrichment, automated diagnosis, automated incident triage, Datadog Bits AI, distributed systems reliability, incident investigation, incident response automation, machine-assisted triage, manual incident triage, MTTR reduction, observability correlation, observability-first design, on-call engineering, operational context, progressive automation, root cause analysis, Rootly, SRE architecture, SRE automation, telemetry correlationWhy SRE teams are replacing manual incident triage with AI-assisted correlation, stronger observability and controlled agentic workflows ...
AI Agents Are Writing Your Infrastructure Code. Is Anyone Governing It?
Neel Shah | | agentic infrastructure, AI agent governance, AI coding assistants, AI-generated infrastructure, cloud misconfiguration, cloud security automation, continuous drift detection, devops security, IAM misconfiguration, infrastructure as code security, infrastructure compliance, infrastructure guardrails, Kubernetes security, platform engineering security, policy as code, RBAC for AI agents, secure-by-default platforms, SRE governance, StackGen Aiden, Terraform securityAI agents now generate infrastructure code at scale, but security pass rates are stuck at 55%. Here’s how teams can close the governance gap ...
From Reactive Monitoring to AI-Driven Operational Intelligence
Sneha Gullapalli | | AI observability, Amazon Q, Apache Iceberg, automated root cause analysis, AWS CloudWatch, AWS operations, CloudWatch Logs, DevOps observability, Distributed Tracing, Five Whys, GenAI observability, incident response, LLM monitoring, log lake, MTTR reduction, operational intelligence, proactive monitoring., RAG latency, S3 Tables, token usage monitoringTraditional monitoring often meant chasing alerts and toggling between dashboards after an issue had already impacted users. AWS CloudWatch — long the backbone of metrics, logs and traces on AWS — is ...
AI-Assisted Development Under Deadline: What It Takes to Ship Production Code on an Unfamiliar Stack
Ihor Riazantsev | | AI code risk, AI coding tools, AI-assisted development, AI-generated code, Claude Code, code consistency, code review, devops teams, engineering discipline, feature isolation, manual testing, memory leak debugging, Next.js development, production readiness, production validation, production-ready code, rapid feature delivery, React development, software architecture, software engineering judgment, technical debt, TypeScript development, unfamiliar codebaseHow Claude Code accelerated development on an unfamiliar stack while proving that production-ready AI-generated code still requires human judgment ...
FakeGit Targets AI Coding Agents with Malicious GitHub Repos
Jeff Burt | | AgentBaiting, AI coding agents, AI supply chain risk, Anthropic Claude Code, fake repositories, FakeGit, github, Google Gemini, Island, MCP Server, OpenAI ChatGPT, SmartLoader, StealCThreat actors continue to find new ways to incorporate AI into schemes aimed at luring developers into downloading malware from fake repositories. The latest example involves almost 7,600 malicious GitHub repositories that ...
OpenAI’s Codex Context Cut Puts Enterprise AI Coding Workflows on Notice
OpenAI quietly trimmed the default input context window for GPT-5.6 inside its Codex CLI, dropping it from 372,000 tokens to 272,000 tokens. That's a 27% cut, and developers noticed fast. The change ...
VS Code 1.129 Moves Agent Sessions Out of the Editor Window
Microsoft has released Visual Studio Code 1.129, and the headline change isn't a new feature so much as a new foundation. The update introduces the agent host, a dedicated process that runs ...
Security Risks from AI Coding Agents Expand Beyond the Sandbox: Pillar
Jeff Burt | | AI code assistants, AI coding agents, AI Developers, AI sandbox, AI security risks, Cursor, Cymulate, Google Antigravity, Google Gemini, OpenAI Codex, Pillar Security, prompt injectionAI coding assistants have become an essential part of developers’ work, automating many of the repetitive tasks – think boilerplate coding and scaffolding – that in the past ate up a lot ...
Signed, Attested, and Malicious: The Software Supply Chain Has a Deepfake Problem
Nigel Douglas | | AI coding agents, AntV packages, behavioural analysis, continuous scanning, dependency security, Developer Security, GitHub Actions compromise, malicious packages, Miasma worm, Mini Shai-Hulud, npm malware, OIDC tokens, open source security, package provenance, package quarantine, policy as code, Red Hat npm attack, registry scanning, Shai-Hulud worm, SLSA provenance, software attestation, Software Supply Chain Security, TanStack compromise, trusted pipeline attacksA developer pulls a package from a reliable repo. It is signed, has provenance, and has been scanned. And then…it contains malware. That is no longer hypothetical. When the Miasma worm tore ...
Harness Extends DevOps Reach to the Realm of AI Agents
Harness today extended the reach of its core continuous integration/continuous delivery (CI/CD) platform to enable DevOps teams to build and deploy artificial intelligence (AI) agents. At the core of that capability are ...
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 ...
