GitHub Next focuses on creating AI-powered prototypes to enhance developer experience, productivity, and happiness.
Large language models function by predicting the most probable next word, a probabilistic nature that can lead to incorrect or fabricated outputs known as hallucinations.
The original GitHub Copilot uses inline suggestions and a "ghost text" UI to automate boilerplate code without disrupting a developer's state of flow.
ChatGPT's mainstream success created a user expectation for chat-based AI interfaces, which are better suited for planning and exploration than for maintaining coding flow.
Copilot Workspace provides a structured workflow that uses AI to brainstorm, generate an implementation plan, and apply code changes directly from a GitHub issue.
GitHub Spark is a tool and runtime that allows developers to rapidly generate and modify small applications using natural language prompts.
Effective AI tools should function as controllable "co-agents" that enhance user capabilities and are designed defensively to handle inevitable failures gracefully.
The next frontier for AI developer tools includes creating UIs that sync natural language with code, focusing on code understanding, and carefully considering the ethics of AI application.
Two recommended books cover the practical skills of prompt engineering for LLMs and the critical process of implementing observability for AI systems.
32:26Krzysztof Cieślak
31:39Rainer Stropek
58:06Anna Fritsch-Weninger
43:05Kenneth Auchenberg & Christian Heilmann
25:17Scott Hanselman
47:35Laurie Voss, Rey Bango, Hannah Foxwell, Rizel Scarlett & Thomas Steiner
31:56Prashanth Chandrasekar, Alejandro Saucedo, Jakob von Lindern & Demetris Cheatham
35:01Angie Jones, Kent C Dobbs, Liran Tal & Chris Heilmann
Jobs that call for the skills explored in this talk.
