AI writes the code. Chunk writes the docs.
Did you know Chunk can analyze your entire codebase and open a PR with accurate, up-to-date documentation?
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The latest News and Information on Continuous Integration and Development, and related technologies.
How to Improve Your Documentation with AI (CircleCI Chunk Tutorial)
AI coding assistants help you ship features fast, but documentation almost never keeps up. In this Ship Smarter session, we'll show you how CircleCI's Chunk autonomous CI/CD agent automatically analyzes your codebase, identifies documentation gaps, and opens a pull request with improvements. No manual writing required. In this video.
Introducing Chunk sidecars: Inner loop validation that keeps up with your agents
Local development and remote validation were always meant to work together: developers iterate on their machine, run a few manual checks, then push to CI to clear code for production. But AI development broke that balance, flooding CI with a volume of commits no developer has read, let alone tested. Chunk sidecars restore the balance: lightweight, preconfigured environments that run alongside your local workflow and validate changes as they happen.
Introducing Chunk sidecars
Fast, pre-configured environments that bring validation and feedback into the inner loop in 60 seconds or less.
AI debugging your CI pipeline
From failing pipeline → fixed PR Here's how Chunk analyzes logs, finds real bugs, and ships working fixes automatically.
Inside Atlassian's Merge Queues: How we ship faster with fewer incidents
At Atlassian, we use Merge Queues to ship frequent changes with confidence and streamline pull request merges. Across some of our busiest codebases, Merge Queues have sharply reduced incident frequency and turned merging from a stressful bottleneck into a background task. Today, most of our largest repositories rely on Merge Queues—over 70 large repos across products like Jira, Rovo, Trello, and others—having safely landed 30,000 pull requests since adopting Merge Queues Beta last quarter.
The 2026 software supply chain security gap
AI-generated code is now nearly universal. Enforcement is not. That gap is where your software supply chain is most exposed. Cloudsmith's CEO Glenn Weinstein, Co-Founder & CTO Lee Skillen, and VP of Product Alison Sickelka join Product Marketing Manager Meghan McGowan to unpack the 2026 State of Artifact Management report – a survey-based look at how AI development is reshaping the threat landscape, what organizations are getting wrong, and what the highest-leverage fix actually looks like.
Accelerating AI Agent Development on Google Cloud with JFrog MCP Registry
Developers building agentic AI on Google Cloud have powerful infrastructure at their fingertips: Gemini 3 for reasoning, Google’s Agent Development Kit (ADK) for orchestration, and a rapidly expanding ecosystem of Model Context Protocol (MCP) servers that connect agents to data and tools. So why are so many teams still waiting weeks to ship their first agent to production?
Shipping trustworthy code with Chunk CLI
AI coding agents are fast. They generate functions, refactor modules, and wire up boilerplate faster than any human. What they don’t do by default is enforce the conventions a specific team has agreed on: the lint rules, the review patterns that senior engineers flag on every PR. A generated diff looks clean until someone runs CI or reads it carefully.
The Hidden Cost of DIY DevOps: Why Growing Companies Bring in the Experts
Companies are scaling faster than ever, but infrastructure rarely keeps up with the product. When developers take on operational work on top of everything else, it feels like a smart way to cut costs. In practice, it's one of the most expensive mistakes a growing software team can make. This article breaks down what DIY DevOps actually costs and how a structured approach changes the equation.