Pattern #3 in the Four Patterns of AI Native Development series. As AI handles coding tasks, developers shift from delivery-focused work to discovery and exploration — building products that better serve customer needs.
Building the right things
With AI automating code generation, teams can collaborate more on “building the right thing” rather than just “building the thing right.” With affordable compute, we can leverage AI to generate and deliver multiple ideas simultaneously, accelerating feedback loops and product validation.
Vibe coding as exploration
Exploratory development where teams accept AI-generated code and iteratively refine it — similar to improvisational jazz. This approach prioritizes discovery over perfection during initial exploration phases, deferring engineering rigor for later iterations.
Incident-driven innovation
Rather than using AI merely for issue triage, teams can generate multiple potential fixes and test solutions rapidly, closing feedback loops faster than traditional ticket-based workflows.
Customer empowerment
Moving beyond A/B testing by enabling customers to personalize applications themselves, democratizing innovation and generating insights that flow back to product teams. Customers might eventually build custom solutions independently, shifting service providers toward platform management.
The shift
Swapping code for curiosity. Developers focus on higher-order thinking and architectural decisions rather than implementation details.
Full article at tessl.io. Part of the Four Patterns of AI Native Development series. Originally posted on LinkedIn.