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Are AI Tools Actually Improving Developer Experience? (Experts Cut Through the Hype)

AI tools are spreading across the entire software development lifecycle - but are they actually making developers more productive, or just adding noise? In this panel from Context Conference, Najla Elmachtoub (Squadformers) moderates a sharp, no-fluff conversation with Nathen Harvey (Google, DORA program), Bill Harding (GitClear), and Jeremy Castile (GitKraken) on what's really working when it comes to AI and developer experience.

Introducing Kepler | GitKraken's Agentic Development Environment (ADE)

Kepler is GitKraken's agentic development environment: mission control for running parallel coding agents at scale. Running one agent is easy. Running five of them across three repos is where things break: scattered terminals, no shared view, no idea what's done or stuck. Kepler puts every agent session on one surface so you can plan work, write code, and review what ships without losing track of anything.

GitKraken: The Code Flow Company

From plan to main. Software is no longer just a tool. It is the infrastructure of modern life. Software keeps airplanes in the sky and power flowing into our homes. It helps doctors save lives, scientists discover cures, farmers feed cities, and astronauts navigate space. It powers economies, protects supply chains, and connects billions of people across the world. Every major system humanity depends on now depends on software. Which means developers are no longer just building applications.

Introducing Kepler: The Delivery Engine for Agent-Driven Development

You’re no longer writing code. You’re managing a pipeline of agents writing it for you. If you’ve been running two, three, or four AI coding agents in parallel, you already know the problem. The agents are fast. The orchestration is chaos. You’re bouncing between terminal windows, manually rebasing branches, cleaning up messy commits, and trying to remember which agent is touching which repo.

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

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.

AI Dev Tools: What 100K Engineers at Google Really Taught Us

AI developer productivity, agentic workflows, and the lessons learned running engineering tools for 100,000+ software engineers at Google. John Montgomery, CCO at GitKraken, sits down with Asim Hussain, co-founder of Alterion AI and former Google VP of Engineering Productivity, to get real about what AI actually changes for engineering teams in 2025.

Are AI Tools Actually Improving Developer Experience? (Experts Cut Through the Hype)

AI tools are spreading across the entire software development lifecycle - but are they actually making developers more productive, or just adding noise? In this panel from Context Conference, Najla Elmachtoub (Squadformers) moderates a sharp, no-fluff conversation with Nathen Harvey (Google, DORA program), Bill Harding (GitClear), and Jeremy Castile (GitKraken) on what's really working when it comes to AI and developer experience.

Healthy PR Lifecycle Time: Benchmarks & Targets (2026)

Your pull request has been open for three days. Your reviewer hasn’t commented. You’re starting to wonder if anyone will ever look at it—and whether the code you wrote on Monday still makes sense on Thursday. This feeling is common. PR lifecycle time—the duration from first commit to merged code—directly impacts how quickly you ship features, how fresh your code stays, and how engaged your reviewers remain.

How to Use Git Blame in Your Editor in 6 Steps (2026)

Tracking down who made a specific change in your codebase can feel like detective work. Whether you’re debugging an issue or trying to understand why a particular piece of logic exists, knowing the history behind each line is invaluable. GitKraken makes this process simple with tools like GitLens for VS Code and GitKraken Desktop, which bring blame annotations directly into your workflow.

10 Privacy-First Engineering Intelligence Platforms 2026

Engineering leaders need more than raw metrics, they need actionable insights they can trust with their data. When evaluating engineering intelligence platforms, privacy controls and centralized repository oversight should top your criteria list. The platforms on this list each offer distinct approaches to tracking DORA metrics, developer productivity, and code quality while keeping your data secure.