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The latest News and Information on Continuous Integration and Development, and related technologies.

ACP vs MCP: What's the difference for agentic coding?

An AI coding agent holds many conversations at once. Not only is the user prompting it, the agent also talks to the IDE, showing diffs and asking before it touches a file. At the same time it talks to tools, pulling a failing build or querying a database. Two open protocols standardize those conversations. This guide compares ACP vs MCP in practical terms: what each protocol does and when each applies. ACP (Agent Client Protocol) connects a code editor to an AI coding agent.

The most dangerous window is before threat intel knows about it

When a malicious package is first published, threat intelligence sources haven't flagged it yet – and every team pulling from a public registry is exposed during that entire window. The fix isn't faster scanning; it's a policy that holds new packages for a defined cooldown period before they're eligible to pull. By the time the window closes, the threat intelligence has caught up. Teams pulling direct from npm or PyPI have no equivalent enforcement layer – which is exactly how attacks like Shai-Hulud got in.

Fix flaky tests with AI, and track future test work in Jira

In January we launched Tests in Bitbucket Pipelines – a single place to track, organize, and understand your test health over time. In April we added automatic flaky test detection so unreliable tests get flagged before they slow your team down. But spotting a problem is only half the battle. Day to day, your team still needs to act on a test – track it as work, clean it up, or route it to the right person.

Unlocking efficiency with Merge Queues in Bitbucket Cloud now GA

Earlier this year, we launched Merge Queues in open beta to help teams automate, sequence, and validate pull request merges. During the beta period, we incorporated feedback from hundreds of teams to improve reliability and simplify configuration. Today, we are excited to announce that Merge Queues is generally available for Standard and Premium plans on Bitbucket Cloud.

Agentic Pipelines now supports OpenAI Codex

Bring your Codex agent into Bitbucket Pipelines. A few weeks ago, we announced support for Claude agents in Bitbucket Pipelines. Today, we’re adding OpenAI Codex as a supported agent. If your team is already using Codex on the desktop, you can now move that same workflow into your pipeline — triggered by a merge, a schedule, a failing build, or a pull request comment.

Native Xet Protocol Support in JFrog Artifactory: How Enterprise Model Management Actually Works

Machine learning models are not like other software artifacts. A single fine-tuned LLM can weigh 70 GB. A model family may share 95% of its weights across dozens of variants. When hundreds of developers, training jobs, and GPU clusters all need the same model at the same time, the infrastructure underneath needs to be built for it.