# chainguard ai Published articles for chainguard ai. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How Chainguard uses AI agents to enforce engineering standards across a monorepo DevFeed: [How Chainguard uses AI agents to enforce engineering standards across a monorepo]() Original publisher: [Read original article]() Published: 2026-06-24T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Artificial Intelligence](), [Bot](), [chainguard](), [Pull Request](), [GitHub Actions]() Tags: [agentic](), [agents](), [ai](), [ai-agents](), [chainguard](), [chainguard-agent-skills](), [chainguard-agents](), [chainguard-ai](), [chainguard-containers](), [chainguard-engineering](), [chainguard-libraries](), [ci](), [engineering](), [github](), [policy](), [pull-request](), [workflow]() ### AI overview Chainguard describes a system of specialized AI agents built on DriftlessAF that continuously checks code against machine-readable engineering standards, fixes drift, and supports CI repair. Over eight weeks, it opened more than 4,700 standards-fix pull requests; 75% judged low-risk were auto-merged when AI judgment agreed with deterministic checks. ### Source excerpt Chainguard uses AI-powered agents to continuously enforce engineering standards, remediate drift, and keep codebases aligned at scale. ## 5 security myths that Mythos ended (as told by a CISO) DevFeed: [5 security myths that Mythos ended (as told by a CISO)]() Original publisher: [Read original article]() Published: 2026-05-27T00:00:00Z Content type: opinion Language: en Sources: [Chainguard: Unchained]() Topics: [Security](), [Artificial Intelligence](), [Exploit](), [Vulnerabilities](), [anthropic](), [dataset]() Tags: [ai](), [ai-security](), [anthropic](), [anthropic-mythos-preview](), [chainguard-ai](), [chainguard-containers](), [cve](), [dataset](), [exploits](), [git](), [mythos](), [project-glasswing](), [security](), [vulnerabilities]() ### AI overview The article argues that Anthropic's Mythos and broader AI-driven vulnerability discovery are invalidating long-standing security assumptions. It focuses on shrinking exploitation timelines, the growing importance of proactive vulnerability elimination, and the need for security teams to retire reactive mental models. ### Source excerpt Mythos and AI-driven exploits are breaking old security assumptions. Learn the five myths security teams must retire to survive the new era. ## Anthropic's Mythos and the acceleration of zero-day vulnerability discovery DevFeed: [Anthropic's Mythos and the acceleration of zero-day vulnerability discovery]() Original publisher: [Read original article]() Published: 2026-04-27T00:00:00Z Content type: opinion Language: en Sources: [Chainguard: Unchained]() Topics: [anthropic](), [Artificial Intelligence](), [ai-assisted attacks](), [Exploit](), [Vulnerabilities](), [Security](), [Cybercrime]() Tags: [ai](), [ai-assisted-attacks](), [ai-containers](), [anthropic](), [anthropic-mythos](), [chainguard-ai](), [chainguard-containers](), [cybercrime](), [exploit](), [firefox](), [kernel](), [linux-kernel](), [mythos](), [mythos-ai-model](), [security](), [vulnerabilities](), [web]() ### AI overview The article discusses Anthropic's Mythos Preview, an AI system described as capable of finding and exploiting previously undisclosed vulnerabilities. It presents examples involving OpenBSD, FFmpeg, the Linux kernel, and Firefox, and argues that such systems could shorten or bypass traditional vulnerability disclosure timelines. ### Source excerpt Anthropic's Mythos is reshaping zero-day threats. Learn how Chainguard helps you stay ahead with source-built, continuously secure software supply chains. ## The only rule: Don't look at the code DevFeed: [The only rule: Don't look at the code]() Original publisher: [Read original article]() Published: 2025-12-29T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Vibe coding](), [AI Development](), [container-security](), [supply-chain-security]() Tags: [ai](), [ai-assisted-coding](), [ai-engineering](), [chainguard-ai](), [chainguard-vibelympics](), [code-quality](), [container-security](), [software-supply-chain](), [vibe-coding]() ### AI overview Chainguard's Vibelympics was a vibe-coding tournament in which 59 individuals and teams built software without looking at the generated code. The article describes the competition's challenges, including an emoji-only interface and a package ecosystem security auditor, and highlights selected submissions and results. ### Source excerpt Chainguard's Vibelympics competition brought out the best and most creative ideas in vibe coding and AI-assisted software development. ## More Secure Vibes: Chainguard Academy's AI Optimizations DevFeed: [More Secure Vibes: Chainguard Academy's AI Optimizations]() Original publisher: [Read original article]() Published: 2025-07-29T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Documentation](), [Large Language Model](), [LLMs](), [chainguard]() Tags: [ai-assistants](), [ai-models](), [chainguard](), [chainguard-ai](), [chainguard-containers](), [chainguard-edu](), [chainguard-images-documentation](), [documentation](), [llm](), [llms](), [new-features]() ### AI overview Chainguard Academy describes improvements to its documentation ecosystem that make the content easier for AI assistants and models to consume. The article covers a Copy Markdown for LLMs feature and machine-readable endpoints such as AI sitemaps, concept maps, plain-text indexes, and structured metadata. ### Source excerpt Chainguard Academy has implemented several new features to make training LLMs and AI models on Chainguard documentation easier. Learn more today. ## Securing the ML supply chain with new Chainguard AI Images DevFeed: [Securing the ML supply chain with new Chainguard AI Images]() Original publisher: [Read original article]() Published: 2023-08-24T00:00:00Z Content type: release Language: en Sources: [Chainguard: Unchained]() Topics: [supply-chain-security](), [chainguard images](), [Machine learning](), [chainguard](), [Kubernetes](), [sigstore]() Tags: [ai](), [chainguard](), [chainguard-ai](), [chainguard-images](), [conda-image](), [cve-remediation](), [kubeflow-image](), [ml-security](), [ml-supply-chain](), [open-ai-image](), [openai-image](), [python-image](), [sboms](), [secure-images](), [security](), [sigstore](), [software-signatures]() ### AI overview Chainguard announces a Chainguard Images AI bundle for securing the ML supply chain across the AI workload lifecycle. The collection includes development, workflow management, deployment, and vector database images, with software signatures, SBOMs, and CVE remediation. ### Source excerpt Chainguard AI Images: Your pathway to a secure ML supply chain with hardened, efficient AI/ML lifecycle solutions.