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GitLens 18.2: AI-Powered Merge Conflict Resolution for VS Code

Merge conflicts rarely make it into a sprint retrospective, but they should. They’re one of the most reliable ways to lose an hour of flow without anyone noticing it’s gone. Every developer expects them eventually, but almost nobody questions the workflow around resolving them.

AI ROI: From Adoption to Business Proof

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.

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.

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 | 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.

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.