Specialized AI Agents via API 2026
How to assemble a specialized AI agent on providers' direct APIs rather than a framework. A running online-store support agent lives as a provider-agnostic business contract and works the same on OpenAI Responses, Anthropic Messages, and Google Gemini Interactions.
In 2026 an agent is a product cycle, not text, and it must be assembled like an engineer, not like an author of clever prompts. The model makes probabilistic decisions - which tool to call, what to clarify, when the work is done. Your server code holds the rights, the facts, and the irreversible actions. Confuse those two roles and you get an agent that "agreed" to issue a refund because of a phrase in someone else's message.
Everything is checked on one agent - support for an online store. It answers policy questions (through RAG), reads the current user's order (with an ownership check), prepares a refund calculation (preview - approval - commit), and hands the conversation to an operator. It's built once as a provider-agnostic business contract and runs on three APIs: OpenAI Responses, Anthropic Messages, and Google Gemini Interactions. That way you can see what's common across agents and what's a detail of a specific SDK.
The technical claims are verified against the primary sources of OpenAI, Anthropic, and Google as of July 31, 2026; the call shapes are checked by the TypeScript compiler. From here we walk the whole path - from narrowing the task boundary and the unified contract to tools, a short observable loop, an autonomy budget, RAG, a refund split into preview/approval/commit, three provider adapters, the final prompt, evals, and shipping a version. Every chapter is not a paraphrase of the docs but a breakdown of the engineering decision behind it.