An AI developer platform should make it possible to build on the same capabilities that users experience in the product. A single chat completion endpoint is useful, but modern applications need more: authentication, conversations, files, tool calls, asynchronous jobs, streaming, webhooks, usage reporting and predictable errors.
AELIA's API architecture is being designed around resources rather than one giant endpoint. Developers should be able to create and retrieve conversations, send messages, upload files, start research jobs, run agents, invoke media generation and manage connector permissions through documented interfaces.
Chat remains a core resource. A request can include a model, messages, tools, files and response preferences. Streaming should allow applications to display partial output rather than waiting for an entire response. The server should return stable request identifiers so developers can trace failures and support users.
Agents add asynchronous execution. An application could create an agent definition, attach permitted tools and start a run. The API would return a run identifier. Developers could poll the run or receive webhook events for queued, running, waiting-for-approval, completed and failed states.
Research should work similarly. A developer might submit a research question with a date range and source requirements, then receive a structured result containing findings, citations and unresolved questions. This keeps long-running work away from a single request timeout.
Files are another foundational resource. The API should support upload, metadata, extraction status, retrieval and deletion. Applications need to know whether a file is still processing and which project or conversation can access it. File access should never depend on a public URL alone.
Connectors are where the platform can become an ecosystem. A connector can expose tools such as repository search, document lookup, calendar operations or publishing actions. The AELIA API should treat connector credentials as sensitive server-side resources and return only safe metadata to clients.
Usage and billing must be part of the developer story from the beginning. Each request should have a measurable unit such as tokens, seconds of media generation, storage or tool executions. Usage records make invoices and quotas explainable. They also let developers set budgets before an application becomes expensive.
Webhooks are essential for asynchronous features. A developer should be able to subscribe to job.completed, job.failed, agent.waiting_for_approval, file.processed and similar events. Webhook delivery should include signatures, retry behavior and an event identifier so consumers can safely deduplicate messages.
SDKs should follow the API rather than invent a second product. The first SDKs can target JavaScript/TypeScript and Python, with generated types and examples. Authentication should use API keys or project credentials appropriate for the application. Secrets should never be placed in browser code when a server-side credential is required.
Documentation should include quickstarts and deeper reference material. A new developer needs a five-minute path to a first request. A production team needs authentication guidance, rate limits, error codes, security recommendations, webhook verification and migration notes.
AELIA also needs an explicit distinction between the public website, the end-user application and the developer platform. The website explains the product. The app performs user work. The API lets other applications build on AELIA. They can share branding and identity while remaining technically separate.
This architecture makes room for future capabilities without changing the core contract. Image generation can become a media job. Video can become a longer-running media job. Voice can expose speech and transcription resources. A browser tool can become a connector. A local desktop agent can use the same APIs.
The developer platform will be successful only if it is predictable. Clear schemas, stable identifiers, useful errors, transparent usage and strong documentation matter as much as model quality. AELIA is being built with that principle in mind: the API should be infrastructure developers can reason about, not a collection of hidden features.
