AI & Technical question

Design the API primitives and SDK abstractions you would provide to help developers take an agent workflow from experimentation to reliable production use. What would you include, what would you leave out, and how would you balance power, clarity, and flexibility for developers?

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What this question tests

Tests platform design judgment: choosing the smallest set of API primitives that cover the agent loop, and knowing what to push into the SDK instead.

Start from the core agent loop: model call, typed tool call, state or session memory, and a human-in-the-loop interrupt point.
Decide which need first-class API primitives: a run or session object with built-in state, typed tool schemas, streaming, and a guardrail hook before tool execution.
Leave prescriptive orchestration, like multi-agent handoff or routing logic, out of the core API since it varies too much by use case, and put it in an optional SDK layer.
Keep the API surface small and composable, and push convenience like retry policies, memory stores, and eval scaffolding into the SDK where developers can override defaults.
Validate against two or three real workflows, a support agent and a coding agent, to check no primitive forces an awkward workaround.

Gives concrete primitives: typed tool-calling, a session object with persisted state, and a pre-execution guardrail hook rather than a vague list.
Draws a clear line between API, must-have, stable contracts, and SDK, convenience and opinionated defaults that can change faster.
Uses a specific tradeoff: exposing raw tool-call transcripts for power versus an abstracted agent-turn object for simplicity, and picks the primitive with an escape hatch.
Connects each primitive back to a real production failure mode it prevents, like silent tool-call drops.

Over-abstracting so advanced developers cannot reach raw model output when they need it.
Scoping primitives to the model call only and ignoring observability and evaluation tooling.
Designing only for today's workflows with no room for multi-agent patterns.