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Your Metrics Look Fine. Your Engineers Are About to Quit.

May 13, 2026 By GitKraken In GitKraken
Developer experience predicts what's coming 3 to 6 months before it shows up in your delivery metrics. So why are most engineering leaders measuring it last? In this session, GitKraken VP of Developer Research Jeremy Castile breaks down what developer experience (DevX) actually is, how to measure it across 6 key dimensions, and how it connects to velocity, code quality, and AI impact data your team is already tracking.
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Why Mandating AI Tools Backfires on Engineering Teams

May 11, 2026 By GitKraken In GitKraken
Responsible AI adoption for engineering teams starts with culture, not compliance. In this GitKon talk, Rizel Scarlett (Tech Lead of Open Source DevRel at Block) shares how Block helped thousands of engineers actually want to use AI tools, including Goose, Cursor, Claude Code, and more, without mandates, vibe coding disasters, or security gaps.
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Founder keynote: Human-AI collaboration at scale | Team '26 | Atlassian

May 7, 2026 By Atlassian In Atlassian
It’s time to reimagine teamwork for the AI era. Join Atlassian leaders to hear how human-AI teams collaborating in one system of work will propel your entire organization forward. About Atlassian: Behind every great human achievement, there is a team. From medicine and space travel to disaster response and pizza deliveries, we help teams all over the planet advance humanity through the power of software. Our mission is to help unleash the potential of every team.
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How to Ship AI-Generated Code to Production

May 7, 2026 By GitKraken In GitKraken
AI writes code. But shipping to production? That still takes a software engineer. In this GitKon talk, Chris Kelly from Augment Code breaks down what it actually means to use AI-assisted development to write production-ready code, not vibe code. If you've been using AI coding assistants and wondering why the output doesn't always make it past code review, this is for you. Chris covers: Key takeaway: The engineers who will thrive aren't the ones who let AI do everything. They're the ones who know how to review, direct, and architect around what AI produces.
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Rovo makes AI-native teamwork real for the enterprise

May 6, 2026 By Atlassian In Atlassian
AI-native teamwork is here. With your team's context connected via the Teamwork Graph, Rovo moves beyond “answer this” to “take this on” with: Max mode in Rovo Chat that completes complex tasks autonomously (coming soon!) The new, unified builder experience in Rovo Studio is now generally available to put your AI to work. Teamwork Graph-powered agents are now available across your entire stack. New enterprise-grade controls to manage and secure agents at scale.
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The Role of AI Chatbots in Modern DevOps Incident Response

The Role of AI Chatbots in Modern DevOps Incident Response

May 6, 2026 By OpsMatters In OpsMatters
Modern DevOps environments demand speed, accuracy, and continuous availability, especially when incidents disrupt critical systems. As organizations scale their infrastructure, traditional response methods often struggle to keep pace with the volume and complexity of alerts. This is where intelligent AI chatbots for customer support are becoming essential, as they provide real-time conversational interfaces that connect teams to automated workflows, incident data, and resolution tools, much like the capabilities showcased in advanced enterprise conversational AI platforms.
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AI Enablement for Dev Teams: The 6-Pillar Flywheel

May 4, 2026 By GitKraken In GitKraken
AI adoption is already happening on your team, whether you have a strategy or not. Tracy Lee (CEO of This Dot Labs, Microsoft MVP, Google Developer Expert) breaks down the AI Enablement Flywheel — a 6-pillar framework used by successful engineering organizations to move from scattered experimentation to scalable, ROI-positive AI workflows.
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DORA Metrics in the AI Era: Why Deployment Isn't Faster

Apr 30, 2026 By GitKraken In GitKraken
DORA metrics in the AI era reveal a paradox: PR volume is climbing, but deployment frequency is staying flat. In this talk, GitKraken's Director of Product Jeff Schinella breaks down why AI-accelerated code generation is creating a review bottleneck that your DORA metrics can't fully explain on their own. Jeff walks through how PR metrics (cycle time, first response time, code churn, and PR size) serve as the leading indicators behind your DORA data. If your deployment frequency is flat while PR counts go up, the bottleneck isn't your devs. It's your review capacity.
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GitKraken Desktop in 6 Minutes: Open a Repo, Run an Agent, Ship the Change

Apr 29, 2026 By GitKraken In GitKraken
The fastest way to get up and running in GitKraken Desktop. In this tutorial, you'll open a repo, start an AI coding agent in its own worktree, review the agent's changes against your own work, and ship a pull request without leaving the app. What you'll learn: Chapters Help Center: help.gitkraken.com.
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Share artifacts between parent and child pipelines | Bitbucket Blitz | Atlassian

Apr 29, 2026 By Atlassian In Atlassian
Bitbucket Pipelines lets you build reusable pipelines and share them across repositories. These reusable, shared pipelines need a way to share artifacts. Otherwise, we’ll have to repeat expensive steps such as downloading and installing dependencies and building the application code. You can now specify an artifacts section for child pipelines, with upload and download keywords. Artifacts listed under upload will be moved from the parent pipeline into the child pipeline, where they can be used and potentially modified.
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