We're building infrastructure for adaptive systems. Software that evolves continuously at runtime as the user interacts with it. Software shouldn't become static after deployment; it should remain as fluid as it is during creation.
In that world, intelligence becomes a local utility, natural and omnipresent, always ready to respond.
AI has transformed how software is built, but not yet how it behaves.
We're in an "early iPhone" moment: first apps mimicked analog calculators and notepads instead of reimagining what was possible. While AI coding tools have enabled more people to build software, the broader ecosystem still clings to the conventions of the traditional software development lifecycle: optimized for technical experts and the familiar rhythms of two-week sprints, rigid planning cycles, and deploy-then-freeze. The infrastructure assumes software is static. We're building for software that ships and evolves.
AI coding has enabled us to turn plain language into code. Building software now feels conversational: you describe what you want, iterate through dialogue, refine in real-time.
But the intent stops at generation: once the code is produced and deployed, behavior freezes into static artifacts. The fluidity of creation doesn't extend to runtime.
Software should maintain the same adaptive nature after deployment that it had during creation. Intent should flow from prompt → code → runtime.
Build infrastructure at the creator's abstraction layer, compute that feels natural, omnipresent, conversational, and always ready. We're driving the shift:
Our journey toward ambient, intent-driven computing starts with Differ - an adaptive runtime platform. Drop your app in, and it starts evolving in production. Agents observe user behavior, infer intent, edit and redeploy the application autonomously.
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