Agent-Native Apps
//COMPARISON

Agent-native app vs SaaS

Agent-native app vs SaaS is an economic comparison more than a technical one. In conventional SaaS, the publisher hosts the software, the compute, and the user's data, and charges rent on all three. An agent-native application is a portable, user-owned package the user mounts into a Host they already have, with data custody declared rather than assumed.

Last updated: 2026-08-07

What does the publisher stop paying for?

In the agent-native model, the publisher doesn't have to host frontier inference or hold user data. Intelligence comes from the user's Host; custody is declared and can stay with the user. That removes the two largest structural costs of AI-era SaaS, which is what makes specialized apps for small markets commercially viable.

This is an architecture claim, not a security promise: declared custody tells you where data lives, and the record tells you what the app did. It does not make any deployment immune to failure.

What happens when the underlying model improves?

SaaS improves when the vendor ships. An agent-native app can improve when the user's Host model improves, without the publisher shipping a migration. The honest caveat travels with the claim: model changes are logged on governed actions, because model behavior changes both ways.

The result is two independent axes of appreciation: the Host gets smarter on the provider's schedule, and the user's owned context, corrections, and state compound on theirs.

What do users keep that SaaS doesn't give them?

Continuity and exit. The user keeps data, context, customizations, and accumulated learning, and can update, diff, roll back, export, or fork within the rules. When a SaaS product sunsets, the workflow dies with the subscription. When an ANA publisher walks away, the user still holds the package and the state.

Agent-native app vs conventional SaaS, dimension by dimension
DimensionAgent-native appConventional SaaS
Who hosts inferenceThe user's Host (frontier or local model)The vendor, priced into the subscription
Who holds the dataDeclared custody; can remain with the userThe vendor, in the vendor's cloud
How it improvesInherits the user's model upgrades; publisher iterates judgmentVendor release cycle
ContinuityExport, fork, and roll back within the rulesEnds with the subscription
Viable market sizeSmall markets work; publisher carries no inference or hosting burden for themMust clear hosting and support costs
Trust surfaceInspectable package, constitution hash, recorded governed actionsVendor reputation and terms of service

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