Patrick presents a framework of four patterns that describe how AI is fundamentally transforming the developer role beyond simple code completion. As AI technology has progressed from basic LLM prompts through RAG, function calling (MCP), and into agentic workflows, the talk argues that we are moving from “sprinkling AI on top” toward a genuinely AI-native way of working — one that reshapes the tasks developers perform day to day.
The first pattern, “From Producer to Manager,” addresses how developers increasingly review and supervise AI-generated code rather than writing it themselves. Patrick highlights the rising cognitive load of code review and emerging approaches to reduce it — including summary-style diffs, diagram-based change visualization, and the concept of a “moldable development environment” that adapts its interface to the review at hand. He also discusses auto-commit workflows, agent checkpoints, cost management for long-running agents, and setting constraints on what AI can and cannot touch.
The second pattern, “From Implementation to Intent,” describes the shift toward specification-driven development. Rather than typing code, developers define what they want through markdown specification files, task-oriented plans, and even fully specification-centric tools where the code itself becomes secondary to the requirements.
The third pattern, “From Delivery to Discovery,” explores how rapid prototyping tools like Lovable and Bolt enable developers — and even customers — to quickly explore ideas, generate multiple design variations, and iterate on product concepts before committing to implementation. The fourth pattern, “From Data to Knowledge,” focuses on capturing the lessons, decisions, and institutional memory that emerge during development. Patrick describes how AI can help preserve feature histories, onboarding context, and incident learnings as durable knowledge rather than letting them dissipate across tickets and Slack threads.
Together, these four patterns show that AI-native development pushes developers toward the work that senior engineers have always done — managing, specifying, discovering, and curating knowledge — rather than merely accelerating typing speed.
Watch on YouTube — available on the jedi4ever channel
This summary was generated using AI based on the auto-generated transcript.