More Prompts Won't Fix Your CI Failures
Turns out telling coding agents what to do over and over again doesn't actually make them better at fixing CI failures.
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Ship faster, improve reliability, and control CI costs with Datadog CI/CD Optimization
AI-assisted development can increase the rate at which teams produce code, but teams only realize those velocity gains if CI can keep pace. More pull requests (PRs) mean more builds, tests, and pipeline executions. Slow jobs leave developers and coding agents waiting for feedback, flaky failures consume time in reruns and investigations, and unnecessary test execution increases runner demand as delivery volume grows.
Watch an AI Agent Fix a Failed CI Build | Harness Worker Agents
What happens when an AI agent can do more than suggest a fix — and actually take action inside your CI pipeline? See Harness Worker Agents in action as an AI agent identifies a failed CI build, determines what went wrong, creates the fix, and gets the pipeline moving toward production again. Worker Agents bring AI-powered reasoning directly into your software delivery pipelines while maintaining the controls enterprises need, including sandboxed execution, scoped credentials, policies, and RBAC.
Our CEO is writing specs again
When the industry moves this fast, the only way to figure it out might be by doing it yourself.
Intent-driven development: How to guide agents from idea to implementation
Intent-driven development (IDD) is an approach to AI-assisted software development where teams make the desired behavior, constraints, and criteria for success explicit, then give an agent freedom to determine how to achieve the result. As agents take on larger and more autonomous development and maintenance tasks, the implementation itself becomes easier to replace. The important question is whether the software still behaves the way the team intended.
Android belongs in your CI/CD pipeline
How on-demand Android environments turn validation into a repeatable pipeline stage In the first article, we looked at automation: how Android environments can be created and managed programmatically. In the second, we looked at scaling: how shared infrastructure can make those environments available to more developers, tests, and workloads. This third article looks at the next step: integrating those environments directly into CI/CD.
Smarter Testing is here: 9,716 tests 44
One file changed. 9,716 tests in the suite. Only 44 needed to run. See how Smarter Testing uses Test Impact Analysis to cut the unnecessary tests and get to feedback faster.
How to Connect Cursor to CircleCI: AI-Powered CI/CD Debugging
Stop manually pushing branches, hunting for logs, and pasting errors back into your editor. This video shows you how to connect Cursor to CircleCI using the CircleCI CLI so your AI agent can trigger pipelines, read build output, and fix failures autonomously without you ever leaving the IDE. In this demo, we introduce a bug, let CI catch it, and watch the agent diagnose and fix it on its own, monitoring the pipeline until it comes back green. No tab-switching. No copy-pasting logs.
CI/CD Security Best Practices: A 2026 Checklist
CI/CD security best practices for 2026: secrets management, scoped access, dependency scanning, signed artifacts, and audit logging in one checklist.
Being Uncomfortable Is the New Normal
CircleCI’s CRO on why this moment calls for learning faster, getting better, and embracing a little discomfort.