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By Melese M
Visualize branches and commits, manage parallel work and agents, and run your entire Git workflow from one view. AI changed how code gets written. It also changed what developers spend their time doing. Today, developers are reviewing AI-generated changes, coordinating parallel work across branches and worktrees, cleaning up commit history, resolving conflicts, and getting everything ready to merge.
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By Jade Nangah
Most companies will tell you they’re customer-obsessed. Fewer can point to the actual mechanism. At GitKraken, it isn’t a quarterly survey or a roadmap council. It’s a Slack channel where developers vent about their Git workflow, and the desktop team is already in there reading it.
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By Chris Griffing
The secret sauce that powers Agentic Development Environments (ADEs) like Kepler is a little thing called the Agent Client Protocol (ACP). In this context, Kepler is the Client and harnesses like Claude Code and the Codex CLI are the Agents. We’re going to go over some of the details about how it works, how we use it at GitKraken, and how the protocol may be changing for the better.
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By Jade Nangah
Leadership has stopped asking whether your team is using AI. They’re asking what you’re delivering with it. That’s a harder question, because most of the numbers teams have been reporting, adoption rate, seats activated, prompts run, don’t actually answer it.
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By Jade Nangah
Adding a second AI agent to a project feels like doubling your output. In practice, it usually means doubling your bookkeeping too. Every agent needs its own worktree so it can work without touching the branch someone else, human or otherwise, is using. Multiply that by five agents across three repos, and the isolation that made parallel work possible starts generating its own kind of work: which worktree goes with which branch, which ones are stale, which upstream nobody remembers creating.
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By Jade Nangah
Most teams adopting AI agents are making a bet on which one wins. Claude or Codex, Copilot or something newer next quarter. That bet is the wrong one to make. The agent you use will keep changing. The workflow around it is what actually needs to hold up.
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By Chris Griffing
The frontier models have led the pack for a while now. It seems like the big players of Anthropic and OpenAI keep leapfrogging each other by a couple points in benchmark scores every other month. But, a trend we are starting to see is that open weight models are improving by leaps and bounds. They don’t hold the lead and probably won’t for a while, but the fact that open models are scaring the leaders is something to think about.
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By Jade Nangah
GitKraken Desktop 12.4 gives developers running several worktrees and AI agent sessions a single graph to see it all, plus an inline way to approve or deny what each agent wants to do. It ships August 4, 2026, with updates carried forward from 12.1 through 12.4.
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By Jade Nangah
Every so often we sit down with someone from our support team and turn their week into a blog post. First up: Roberto Vizcarra, on four things generating tickets lately, AI credits, student plans, integrations, and Mac performance. Here’s what changed and what to do about it.
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By Jade Nangah
A faster car doesn’t get you home faster if the freeway is still jammed. That is the problem most teams run into once they add a second, third, or fourth AI coding agent to the mix. More agents generate more code. They do not automatically generate more finished work, because someone still has to track which agent is waiting on input, which one just opened a pull request, and which one has been quietly stuck for twenty minutes. Kepler is GitKraken’s answer to that traffic jam.
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By GitKraken
GitLens 19 is here, with a reimagined Commit Graph built to be your workbench for modern parallel development. See what’s happening across branches, worktrees, and supported coding agent sessions, then move the work forward without constantly jumping between views and tools.
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By GitKraken
Code Flow is what we call the shift happening across every engineering team right now: AI can generate code faster than ever, but that doesn't mean it ships any faster. In this clip from our Code Flow Live stream, our team unpack why adding AI coding agents to a team is a lot like adding lanes to a highway that's already jammed. More lanes, more cars, same traffic.
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By GitKraken
Everyone's betting on which AI agent wins. Wrong bet. The agent you use will keep changing. The workflow around it is what needs to hold up. That's why Kepler connects to any agent, Claude, Codex, Copilot, instead of locking you into one.
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By GitKraken
What if you could counterspell an agent action? GitKraken Desktop 12.4 pulls the whole AI agent workflow into one place, so you stay in the flow. Back in 12.0 we shipped Agent Sessions, where you kick off AI coding agents right inside the context of your repo. GitKraken 12.4 builds on that. What's new in 12.4: This release is not about handing more of your work to agents. It's about seeing everything they do, and deciding what actually changes.
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By GitKraken
Running Claude in one terminal and Cursor in another isn't a workflow. It's a juggling act. We talked to the engineer who got tired of it and built Kepler instead: one place to run agents, review PRs, and stay in control.
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By GitKraken
AI didn't just change how fast code gets written. It exposed a new bottleneck: everything around the code. Reviews slow down. Context gets lost. Planning drifts from implementation. Teams move fast and still feel stuck. That's the problem GitKraken is built to solve, and this Friday we're going live to walk through what's changed. We'll cover the latest Code Flow Company features we've shipped, how they connect developers, AI agents, and production into one system, and what it actually looks like to go from plan to main without the chaos.
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By GitKraken
New data from our VP of Dev Research on The Programming Podcast. 84% of devs feel more productive with AI coding tools 43% feel MUCH more productive The kicker: productivity feeling scales directly with how agentic your workflow is. The more agents do, the better it feels.
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By GitKraken
AI didn't just change how fast code gets written. It exposed a new bottleneck: everything around the code. Reviews slow down. Context gets lost. Planning drifts from implementation. Teams move fast and still feel stuck. That's the problem GitKraken is built to solve, and this Friday we're going live to walk through what's changed. We'll cover the latest Code Flow Company features we've shipped, how they connect developers, AI agents, and production into one system, and what it actually looks like to go from plan to main without the chaos.
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By GitKraken
New: launch a Claude Code or Codex CLI session straight from the Agents panel. One click → isolated worktree → setup commands run → agent starts. Your other worktrees don't even notice. Parallel AI agents without the chaos. That's code flow.
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By GitKraken
AI adoption is easy to report. Business impact is harder to prove. Engineering leaders are under pressure to show what AI is actually changing — not just who is using it, but whether it is improving delivery, quality, developer experience, and business outcomes. This discussion between 3 engineering leaders explores how to move beyond vanity metrics, build a practical measurement approach, and communicate AI’s value to executives and CFOs with more credibility and less hype.
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GitKraken is on a mission to make Git easier, safer and more powerful across multiple surfaces and environments that development teams use.
Over 10 million developers from more than 100,000 organizations worldwide rely on GitKraken to get their work done. Since 2014, we've been rapidly developing the legendary cross-platform tools while reimagining an intuitive, visual approach to Git. Our team is dedicated to making tools that help software developers be more productive using Git, it's truly our passion. We develop software that's in use by the world's most elite companies like Apple, Google, Microsoft, Amazon, and thousands of other leading organizations.
We Make Git Tools Devs Love.