Synapse was built around a problem that became visible as soon as different AI models became useful for different kinds of work: switching providers also meant repeatedly reconstructing the same context.
A browser-like desktop interface with AI providers in tabs and a shared project context store so information given to one provider can be available when switching to another.
The aim. Reduce the friction of switching models and repeatedly copying the same context between them.
01The problem behind the project
Different models have different strengths, but moving between them usually means repeatedly copying context and reconstructing the same working state.
The product imagined AI providers as tabs inside a shared workspace. The important object was not the chat window itself, but a project context store that could remain available as the user moved between models with different strengths.
People who intentionally use several AI providers. The API-key requirement and advanced workflow made the audience narrower than originally expected.
02How it took shape
A multi-provider desktop and web app concept with tabs, a shared context store, local testing with browser storage, and a thin Express proxy for server-side keys in the production direction.
An MVP explored the browser-like interface, shared memory, local storage, and a thin server-side direction for provider keys. The application and download site shipped, which made it possible to evaluate the experience as a product rather than only as an architecture diagram.
Josiah defined the multi-provider workflow, shared-memory concept, product direction, and product-fit evaluation, using AI-assisted development to produce and ship the MVP.
An MVP and download website shipped. The product also produced a useful negative result: the UX and target audience were not strong enough to justify continued maintenance.
03What the project means now
The negative result is part of the value. API-key friction, a narrow advanced-user audience, and the maintenance cost of provider integrations outweighed the convenience the shared context created. Synapse became an early lesson in the difference between solving a technical problem and finding a durable product.
The public download repository is thin, the exact architecture needs reconstruction, and screenshots must avoid private conversation memory or API credentials.
Shipping a technically complete MVP does not resolve a weak audience definition or the friction of asking users to manage provider API keys.
Publish a candid product-arc case study with sanitized media and a clearer architecture description.