So, you flipped the switch to enable Cloud Patches in GitKraken Client's experimental features. ✅ What's next? 🤷 Follow GitKraken Ambassador Kevin Bost (@kitekeboo) through naming & permissions settings for Cloud Patches, allowing you to easily share code with yourself, your colleagues, or anyone else within your org. 👍

Better visualization tools for planning, increased flexibility and control of how your integration works…actual support? This is why Jira admins, team leads, product managers, and other development stakeholders choose Git Integration for Jira over the free alternatives like GitHub for Jira and GitLab for Jira Cloud. Flexibility and customization of deployment: More control over how you integrate with your Git repository and how associated data appears in Jira.

GitKraken Ambassador Kevin Bost (@kitekeboo) takes a deep dive into this new way to share code – but first, how do you enable them in GitKraken Client? 🤨 Simply head from Preferences ➡️ Experimental, then check ✅ Use Cloud Patches. That's it! ✨ Since this is an experimental feature, feedback is needed! Try them out & share your thoughts at feedback.gitkraken.com 📝

What's a Git patch, you ask? 🤔 Let our GitKraken Ambassador, Kevin Bost @Kitokeboo, break it down for you! 💻✨ Discover how to whip up a Git patch file (with a touch of PowerShell wizardry) within the GitKraken Client.

GitKraken's CTO Eric Amodio believes it's about addressing the details that are easy to miss– the random Slack conversations, the PRs, and Issues that slip your mind, consolidating everything into a digestible 'To Do' list that keeps you productive and in-the-know.

It's painful managing multiple repos. Whether you're a developer juggling between different app windows, or a manager looking to understand what's happening – GitKraken Workspaces and Insights provide an easy way to organize the chaos into something informative and actionable. (And don't worry. If you're working with a mono-repo, we'll have insights for your use case too.) In this workshop, Trevor Polidore and Kevin Bost explore ways to save time and reduce headaches when working with a large number of repos.

What are language models good at, and where do they struggle? 🤖 While LMs are improving by the day, they still struggle with handling the "gray area" around certain tasks. But simple problems & solutions? That's where they shine. ✨