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AI adoption is nearly universal. So why are most teams still struggling? In this session from GitKon, Nathen Harvey, head of DORA at Google Cloud, shares findings from the 2025 DORA State of AI-Assisted Software Development report, drawing on data from nearly 5,000 developers worldwide. The answer isn't more AI. It's what surrounds it.

What does a meaningful developer career look like in the age of AI? We brought together four experts to answer exactly that. In this GitKon panel, GitKraken CMO Kate Adams moderates a conversation with Leon Noel (Managing Director of Engineering, Resilient Coders), Danny Thompson (Director of Technology and host of The Programming Podcast), Maggie Hunter (Recruitment Lead, GitKraken), and Dimitry Fonarev (CEO, Testkube) to explore how software engineers can future-proof their careers, grow their skills, and navigate an industry that is changing fast.

What happens when you give an AI agent hundreds of API endpoints and hope it figures out the right workflow? Spoiler: it nearly gets it right... but never reliably. In this talk, Frank Kilcommins (Head of Enterprise Architecture at Jentik and co-author of the Arazzo Specification) breaks down why API documentation quality is the core knowledge problem holding agentic systems back (and how Arazzo solves it).

Spec-driven development with AI coding agents could change how you build software. In this GitKon 2025 talk, Erik Hanchett, Senior Developer Advocate at AWS, breaks down why AI coding assistants perform dramatically better when they start with structured specifications instead of raw prompts. If you've been vibe coding your way through complex features and wondering why your AI keeps going off the rails, this is the video for you.

AI can write code fast, but it makes mistakes humans often don't. In this session from Ole Lensmar, CTO of Testkube, breaks down the real quality risks of AI-generated code and how engineering teams can build guardrails before those bugs hit production. What you'll learn: Common mistakes LLMs make (and which ones are unique to AI) Whether you're a developer leaning on AI to ship faster or a QA lead trying to keep up with the pace of AI-generated code, this talk gives you a practical framework for staying ahead of quality issues.

AI-assisted merge conflict resolution is changing how developers handle Git workflows. Watch GitKraken Ambassador Kevin Bost demonstrate AI-powered features that eliminate merge conflict dread, clean up messy commit history, and generate contextual commit messages in seconds.

What does a meaningful developer career look like in the age of AI? We brought together four experts to answer exactly that. In this GitKon panel, GitKraken CMO Kate Adams moderates a conversation with Leon Noel (Managing Director of Engineering, Resilient Coders), Danny Thompson (Director of Technology and host of The Programming Podcast), Maggie Hunter (Recruitment Lead, GitKraken), and Dimitry Fonarev (CEO, Testkube) to explore how software engineers can future-proof their careers, grow their skills, and navigate an industry that is changing fast.

AI commit message generation is fast, accurate, and consistent. It's also missing the most important thing: the why. AI-assisted Git workflows can summarize a diff in seconds, but they optimize for description, not decision-making. In this video, we break down what AI commit messages do well, where they fall short, and how to use them without quietly erasing the context future teammates (and future you) actually need.