In this episode of the AI Native Dev podcast hosted by Tessl, Patrick joins Simon Maple for an in-depth conversation about the emerging patterns of AI-native development. They begin by discussing what constitutes a paradigm shift – not merely adding AI on top of existing workflows, but fundamentally rethinking how software is built. Patrick draws parallels to previous shifts like cloud native and DevOps, noting that the sheer number of unknowns, the creation of new job roles, and the need to rethink established processes are hallmarks of a genuine paradigm change.
The conversation walks through the four AI-native development patterns that Patrick and the community have been refining. The first, “Producer to Manager,” describes how developers are shifting from writing code to reviewing and managing AI-generated output, with cognitive load becoming a central challenge. The second, “Implementation to Intent,” covers the move from hands-on coding to expressing specifications and requirements – a shift that pushes developers closer to the architect or product owner role. Patrick and Simon discuss how the IDE itself may need to evolve, or even be replaced by interfaces better suited to specification-centric workflows.
The third pattern, “Delivery to Discovery,” explores how cheaper and faster code generation frees developers to prototype multiple options, gather rapid customer feedback, and focus on building the right thing rather than just shipping. Patrick notes that discovery can happen not only before coding but even in production, where AI could dynamically adjust features based on real user interactions. The fourth pattern, “Content to Knowledge,” examines how organizations can capture and nurture institutional knowledge – from onboarding materials and incident learnings to mid-conversation insights flagged by tools like Devin – turning scattered content into a lasting competitive advantage.
The episode also covers the launch of the AI Native Dev landscape (landscape.ainativedev.io), a community-curated catalog of tools organized by software development activities. Patrick explains that the landscape helps developers understand what is possible, locate themselves within the ecosystem, and discover tools they might not have known about. Both Patrick and Simon emphasize that the patterns and the landscape are early-stage, community-driven efforts – explicitly inviting feedback, contributions, and constructive criticism to help refine the vocabulary and categorization of this rapidly evolving space.
Watch on YouTube — available on the jedi4ever channel
This summary was generated using AI based on the auto-generated transcript.