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Most AI features are a chatbot stapled to software built before agents existed. AI-native means the whole thing assumes an agent from line one. Here is a checklist that tells the two apart.
Cloud was the default because the heavy compute lived elsewhere. Capable agents now run from a CLI on your own machine, so sending your code and keys to a vendor's cloud is a choice, not a requirement.
Most AI tools wrap a chatbot around a model you could call directly, then charge on every run forever. There is another way to build: let AI do the work once, then own an artifact that runs without it.
When every team can call the same frontier model, the model stops being the moat. The engineering that matters moves to the harness: the tools, grounding, and verification around the agent.
Bolting a chatbot onto old software is not AI-native. Rebuilding from line one is. Here is what that actually means, and why open and local-first are part of it.
Let AI do the expensive exploratory work once, then crystallize it into a durable artifact that runs forever without the AI tax. The pattern behind everything we build.
How Hover drives your real Chrome to verify a flow you describe in plain English, then crystallizes it into a standard @playwright/test spec that runs in CI with zero AI.