Deep dives from building an event-first, multi-user AI platform.
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You have a capable LangGraph agent — a multi-node graph, nested subagents, its own retrieval and memory, its own persistence — running on one machine for one user. KDCube hosts it at scale without rewriting it. Your graph definition and behavior stay yours; KDCube builds a fresh graph instance for each bound turn and discards it afterward. The platform ad...
An agent can write useful code: inspect data, join records, transform files, build a chart, or assemble a report. That code needs CPU, libraries, and a workspace. Network access, provider credentials, deployment secrets, and the authority to change an external system belong somewhere else. KDCube separates those jobs. Generated code computes inside a boun...
Every integration wants to act as someone, somewhere. Send mail through the user's Gmail account. Let a script call an application on the user's behalf. Accept a Telegram message and connect its sender to the platform user who owns the work. Each journey carries a different proof, credential, and direction of authority. Connection Hub gives them one gover...
Your application already knows how to spend money on a user's behalf — an LLM call, an embedding, a web search. The question is whether the platform gets to decide, before the call runs, that this user can afford it, and to charge the real cost afterward. KDCube makes that decision the same on every surface, without your application reimplementing plans, ...
An application already owns a browser experience: source files, a build, a main view, APIs, and the platform session around them. It should not need a second web server, a hand-written reverse-proxy block, or a separate authentication implementation to become a website. Declare the site in the application; KDCube builds it, routes it, and gives a CDN one ...
A tool schema tells an agent how to call a function. It does not tell the runtime whether that call reads, writes, or can safely begin before the model has finished generating the rest of its round. KDCube tool traits add that missing policy layer — metadata the runtime reads and enforces , not prompt advice.
One tool call charters a helper agent that runs as its own scheduled turn, streams into the same chat as a thread, and reports back onto the timeline it came from — with the admin shaping who may delegate to whom, the paying user deciding, and the runtime enforcing the same economic boundary as any turn .
The complete hands-on authoring story: nouns and refs, search vocabulary, role-guarded use cases, honest guards, the presentation layer — and the test that a realm now has two readers : an agent that works it from the schema, and a user who understands and controls it from its service card.
Two ways into a running KDCube — a one-command clean bootstrap that stages a configured ecosystem, and a descriptor set that reproduces an environment as a reviewed artifact — and the one operating loop you live in afterwards.
Nineteen real problems, stated the way practitioners state them — each answered with the concrete KDCube mechanism that solves it. Problem in, solution out, links to go deeper. A living piece: new problems get appended as we meet them.