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By Jade Nangah
AI coding tools were supposed to mean developers work less. On a recent webinar recorded with LeadDev, senior engineering manager Vernon put words to something a lot of teams are quietly noticing instead: “It’s concerning because it’s the opposite of what was promised. We were supposed to be working less.”
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By Jade Nangah
Splitting one big pull request into five smaller ones doesn’t automatically make review faster. It just moves the complexity from the diff to your head, unless something keeps track of the order for you.
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By Jade Nangah
Most companies buy AI tools for developers and hope the impact shows up somewhere. A faster sprint. Fewer escaped bugs. Something. What they don’t have is a way to actually see it happening, which means adoption becomes a leap of faith instead of a measured bet. That’s the gap Kepler and GitKraken Insights close together, and it’s worth understanding as one story, not two separate product updates.
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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 GitKraken
Kepler is GitKraken's new agentic development environment (ADE), and it's now in public preview for Windows, Mac, and Linux. If GitKraken Desktop is built to go deep on one repository, Kepler is built to go wide: one task, multiple repositories, multiple AI agents, tracked in a single place instead of a dozen open terminals.
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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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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.
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