Building with AI
AI-native development is not about asking a chatbot to write code. It is a workflow where specifications drive everything: a human defines what to build, AI agents handle the implementation, and senior engineers verify the output. The spec is the asset. The code is derived from it and can be regenerated at any time.
This approach compresses timelines dramatically. A project that would take a traditional team two weeks can ship in two days, not because corners are cut, but because the bottleneck shifts from typing to thinking. The hard work is deciding what to build and writing a spec clear enough that an agent can execute it without ambiguity.
These articles cover the practical mechanics: how spec-first development works, where AI tools like Lovable and Cursor hit their limits, what happens when execution becomes nearly free, and how the role of the engineer changes when agents handle the implementation layer.
Featured
When Your Cursor Project Needs a Real Engineer
Cursor got you to 80%. Here's how to recognize you've hit the wall, and what it takes to get the last 20% done right.
What to Do After You've Built a Prototype in Lovable
Your Lovable prototype works but can't go further. Here's how to evaluate what you have, extract a spec, and get to production.
Why Specs Matter More Than Code
A well-written spec can be rebuilt into a working application in minutes. Code is a derived artifact. How the spec-first philosophy changes project management and reduces risk.