Event Details

Description:

Stop debugging AI-generated code that "looks right but doesn't work." Join ArchitectNow for an essential exploration of spec-driven development—the methodology transforming how engineering teams work with AI coding assistants like GitHub Copilot and Claude Code. In this hands-on session, you'll discover how to turn vague ideas into detailed specifications that AI agents can reliably implement, eliminating the costly iteration cycles and technical debt that plague traditional "vibe coding" approaches.

Using GitHub's open-source Spec Kit toolkit, we'll demonstrate the complete workflow: establishing constitutional principles that encode your team's standards, creating executable specifications that serve as the source of truth, generating technical plans that respect architectural constraints, and breaking down work into focused tasks that AI agents implement consistently. You'll see a real application built from scratch in under 20 minutes—not a toy demo, but production-quality code with testing, security, and maintainability baked in from the start. We'll cover how to integrate this approach with your existing Git workflows, how specifications become living documentation that survives team turnover, and how early adopters are achieving 3-10x development speed improvements while maintaining architectural consistency.

Whether you're frustrated with inconsistent AI output, struggling to maintain quality as your team adopts AI tools, or looking to scale AI-assisted development across your organization, this webinar provides the practical framework and proven toolkit you need. Learn why organizations from AWS to financial services are adopting specification-driven approaches, and walk away with actionable strategies you can implement immediately to transform your AI coding assistants from unreliable generators into reliable implementation partners.

Who Should Attend:

Software developers and engineers using or evaluating AI coding assistants, engineering managers seeking to improve team productivity and code quality, technical leads responsible for architectural standards and governance, and technology decision-makers exploring sustainable approaches to AI-assisted development.