AI is here, but deciding what to use and how is difficult. In this fast-paced session, we'll explore 15 key decisions for coding effectively in AI including IDEs, models, harnesses, instructions, permissions, agents, and more. You'll leave this session with a variety of ideas for how to rethink your AI-related tooling, patterns, and workflows.

The panel "Will AI Change Who Gets to Be a Developer?" explores the transformative impact of artificial intelligence on the developer landscape. As AI tools become increasingly integrated into software development, they have the potential to democratize access to programming by simplifying complex tasks and enabling individuals without traditional coding backgrounds to create and innovate. This discussion will analyze both the opportunities and challenges presented by AI in reducing barriers to entry, the evolving skill sets required for modern developers, and the implications for diversity within the tech industry. Join us as we delve into the future of development and the shifting paradigm of who can participate in this dynamic field. And yes, AI wrote this abstract.

"AI writes slop" is a common concern. So how can we use LLMs to not just generate good code, but to *ensure* quality? Let's explore how to create effective "guardrails" via generated tests, spec-driven development, instruction approaches, prompting techniques, context management, and more. After this session you'll have a list of ideas for improving your AI coding workflow.