For as long as we’ve been humans, we’ve told stories. Stories to entertain us, stories to guide us, stories to connect us. The media change, but the human thirst for stories stays the same.
When stories became recorded, the narrative decoupled from the creator. We sacrificed the adaptability of live dialogue in exchange for the scalability of recorded media. Today we are revisiting that tradeoff.
Recent AI advances enable adaptability at scale. It’s an unprecedented paradigm shift in the history of human communication: live dialogue at global scale.
Imagine a typical podcast: a recorded conversation between a few individuals. Millions of people listen to such conversations each day. What if each listener got the power to participate? To ask their questions. To clarify their confusions. To expand the work into something unique to them.
What if this was true for every form of media? Every book, every film, every song, every lecture, every game? Each one able to respond, adapt, change shape.
In such a world, the interplay among creator, work, and audience becomes an additional dimension to design. An interactive dimension; expressed in but still orthogonal to the text, images, audio, and videos of today. We belive all the necessary pieces to explore the interactive dimension are here.
We intend to put them together.
The Necessary Pieces
First, language models now support long contexts, multimodal reasoning, and low-latency inference. Second, and more critically, audience expectations are shifting. Daily interaction with conversational AI is establishing participatory habits. Audiences increasingly assume that what they read, watch, and hear can be queried, redirected, and revisited. Just as kids today try to touch every screen they see, we expect the kids of tomorrow to participate in the creative works around them.
The research community is converging on the same direction. Recent work in human–computer interaction treats the interface itself as adaptive material: documents that reorganize around a reader's goals, conversational systems that generate visual controls on demand, interfaces that restructure in real time as intent becomes clear.
Model capability, audience expectations, and the research community are converging on a single point. So the question is not whether this medium is possible — it's what it makes possible.
The Possible
Distribution has always imposed a limiting condition on creative work: to reach an audience, the expression must become a discrete, finished object. The resulting work may preserve language, images, sound, and narrative structure, but the creator's part in the communication effectively ends at publication. From that point, the work must speak for itself: whatever the creator would have clarified, expanded, or answered survives only as traces in the fixed form, and the labor of interpretation passes entirely to the audience. In addition, a published work receives no information from its audience; regardless of their confusion, objection, or curiosity, the work remains unchanged.
AI makes it possible to carry more communicative structure into the audience's experience. Creators can represent not only the finished expression, but also the knowledge, intent, perspective, and constraints that shaped it. The interactive dimension allows these elements to activate selectively as the work is experienced. Furthermore, when someone in the audience asks a question, expresses uncertainty, or introduces relevant context, that contribution can become an input to the experience itself. In response, the work may clarify an idea, reorganize an explanation, surface supporting material, or reiterate an earlier point. Meaning is no longer confined to what was fixed at publication; it can continue to develop through interaction.
This does not transfer authorship from the creator to the AI. The creator establishes the work's purpose, source material, perspective, expressive character, and conditions of participation. They do not script every possible response; instead, they author the system of intent, knowledge, and constraints from which responses emerge. The extent of audience participation is itself an authored property: some creators may permit guided exploration within carefully defined boundaries, while others may invite audiences to influence how an experience develops or contribute directly to it. Creators gain new dimensions of expression, and audiences gain the ability to follow their curiosity and engage more deeply with the creator's ideas.
The result is finished works that no longer terminate at distribution. Publication becomes the beginning of an ongoing, authored exchange between creators and their audience.
The Missing Creative Layer
However, these outcomes won't emerge automatically from more capable models. Capabilities alone don't constitute a creative medium.
Creators need tools for representing communicative intent, organizing knowledge, defining what is fixed versus adaptive, setting behavioral boundaries, and determining the audience's degree of agency. They need ways to preview how a work might behave across different encounters and to evaluate whether its responses remain consistent with their intentions. Audiences need coherent ways to interact, preserve continuity, and understand which parts of an experience are authored, generated, or adapted.
A medium also requires conventions. Creators and audiences need shared expectations about authority, consent, attribution, memory, and control. The experiences themselves must feel native to the forms from which they emerge, rather than like generic interfaces attached after the fact.
That is where we come in.
The interactive dimension is opened by AI, but we need a creative layer to make it authorable. We are building that layer through which interactive works are authored and experienced. That means creating tools that let creators define a work's knowledge, intent, behavior, and boundaries. It also means building the destination where audiences encounter those works and participate in them. The grammar of this medium doesn't yet exist. We will be developing it in collaboration with both creators and their audiences.
Our Starting Point
Synchr is our first exploration of this thesis. Currently in beta, it already lets listeners move from a recorded podcast into a low-latency and grounded voice conversation. It can answer questions, clarify ideas, discuss arguments, and explore related topics. With the creator's permission, it can speak in their voice and conversational patterns.
The experience is explicitly presented as an AI extension of the creator, not the creator themselves. Voice cloning requires the creator's consent. The purpose is not to convince listeners that they're having a private conversation with another person; it's to let a creator's work carry a capacity for explanation and response.
Through using Synchr, a podcast carries more than recorded audio to its listeners. It carries relevant context, an authored perspective, and a capacity for conversation. The listener can pursue ideas the moment curiosity arises while staying within the communicative environment established by the creator.
Podcasts are an ideal place to begin because they're already built around conversation. A host's voice, perspective, and explanatory style are central to the form, and listeners often develop lasting relationships with the people and ideas behind their favorite shows. On a technical note, audio can be generated efficiently enough for interaction to feel natural.
Different podcasts will require different knowledge, behaviors, boundaries, and degrees of participation. Producers therefore need to be co-developers of the form. By working with them, we hope to learn which kinds of interaction deepen a podcast, which compromise its intent, and what creators need in order to exercise meaningful control.
Where We're Heading
By building alongside podcast creators, we can begin developing the authoring tools, interaction patterns, and creative conventions required for adaptive, creator-directed experiences. We'll then extend those capabilities to other media, each of which will discover its own expressive uses for them. We're extremely excited about this — and the only thing we can reliably anticipate is that creators will use memory, adaptation, simulation, and co-creation to invent forms nobody can anticipate.
We are technical storytellers working at the boundary between creative practice and computational systems. We believe this medium will be developed by people who understand both the mechanics of these systems and the human purposes they should serve.
AI will not only change how existing media are produced. It will expand the forms through which people create, participate, and communicate.
If you believe what we believe, we would love to hear from you: [email protected]