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· 7 min read

One amazing benefit that modern LLMs come with is using them as a linter, or a pair programmer. You can easily get feedback on your code: just share it with the AI tool and ask a question. If the feedback is solid, your code is improved. If the feedback is poor, you can just disregard it. But overall with very little effort you can gain a lot.

In this article we are going to focus on code review done with AI tools. We are going to explore a few solutions available as of February 2026 and how they compare based on our experience. This is not a thorough analysis nor are we doing any evals.

· 2 min read

There are upstream projects that have multiple release streams and, for example, regularly release patch versions for every active minor version. With pull-from-upstream you have been able to follow only the highest stream, but that now changes. By switching Monitoring status of your package from Monitoring to Monitoring all, you enable triggering pull-from-upstream for every released version, not only the highest. This means you can use options such as version_update_mask, upstream_tag_include or upstream_tag_exclude (those require upstream_project_url to be set) to filter a specific release stream you want to follow, or have multiple pull-from-upstream jobs, each matching different releases and targeting different dist-git branches.