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The OpenAI Decisions API is a narrow tool: its reference says it will “Evaluate ordered classification and scoring questions against shared input. Answers are returned in question order.” If that describes your task, you may not need an alternative. If you need a whole automated decision system, with tools, approvals, waits, retries and audits, you need an orchestration layer around any decision endpoint. This guide shows which option fits which need.
What the Decisions API does and does not cover
The Decisions API reference describes ordered predicate, choice and score questions asked against one shared input. The input can be a string or user messages containing text and inline images. The reference excludes external image URLs, files, audio, tool calls and item references.
That makes it a typed classification and scoring interface. It is not a workflow engine. It does not by itself manage state, run tools, wait for a human, or resume after a failure. Two separate needs follow from that:
- A different way to get typed decisions, when your inputs or contract don’t fit the endpoint.
- A system around the decisions, covering orchestration, approvals, durability and evaluation.
The alternatives at a glance
| Option | Who controls orchestration and state | Best fit | Source |
|---|---|---|---|
| Responses API | Your application | Direct model calls where you control the integration or build an agent from scratch | OpenAI agents comparison |
| Agents SDK | Your application owns the agent loop, tools, deployment, storage and approvals | Custom multi-step decision agents with your own infrastructure | OpenAI agents comparison |
| Agents API | OpenAI manages a long-running agent runtime and saved progress | Long-running work where you prefer a managed runtime | OpenAI agents comparison |
| Amazon Bedrock Prompt Flows | AWS visual workflow connecting prompts, supported foundation models and AWS services such as Lambda | Teams already on AWS who want visual composition and a path from testing to production | AWS decision guide |
| Temporal with the Agents SDK | A durable workflow engine | Long-running flows with waits, human-in-the-loop tasks and resumable execution | Agents SDK running agents |
Bedrock Prompt Flows is a workflow-building option. Nothing in the AWS guide shows it offers a drop-in endpoint with the Decisions API’s contract. Comparative pricing, latency, throughput and benchmark rankings are not established by these sources, so none are given here.
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Choosing by need
You only need typed answers over text or inline images
Use the Decisions endpoint. Its predicate, choice and score questions, returned in question order, are the contract. Check first that your evidence fits the supported input types.
Your evidence includes files, URLs, audio or tool results
The endpoint excludes those inputs, so use the Responses API and define your own output structure, or build an agent with the Agents SDK that gathers evidence with tools before deciding. You then own the contract that the Decisions API would have given you.
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You want full control of the loop and data
Choose the Agents SDK. Your application owns the loop, tools, deployment, storage and approvals, which suits regulated or tightly integrated systems.
You want OpenAI to run long tasks
Choose the Agents API, where OpenAI manages the long-running runtime and saved progress. You trade control for less infrastructure.
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Waits and restarts are central
Pair the SDK with Temporal. The Agents SDK documentation identifies it for durable, long-running workflows, including human-in-the-loop tasks. Use it when a decision may wait hours for an approver or must survive process restarts.
You are standardized on AWS
Evaluate Bedrock Prompt Flows. It links prompts, supported models and AWS services including Lambda, and the AWS guide says flows can move from testing to production.
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Criteria for comparing candidates
- Decision contract: do you need a predicate probability, a choice from supplied values, or a score across ordered levels, and do typed answers and ordering matter to your application?
- Input fit: text and inline images versus files, URLs, audio or tool results.
- State and ownership: provider runtime, your SDK code, or a workflow service.
- Durability: application-owned loops, managed long-running tasks, visual cloud workflows, or durable orchestration.
- Governance: where checks and approvals attach.
- Evaluation: whether you can trace and regression-test behavior.
Guardrails and human approval
The OpenAI guardrails guide maps controls to specific jobs:
- Input guardrails block disallowed requests.
- Output guardrails validate or redact final output.
- Tool guardrails check tool arguments and results.
- Human-in-the-loop approvals pause before side effects.
The scope limits matter for decision systems. Input guardrails run only for the first agent in a chain. Output guardrails run only for the agent that produces the final output. Tool guardrails run only on tools they are attached to. If every refund, account change or message must be validated, put the check beside the tool that performs it, not only at the agent boundary.
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Evaluating a decision system
The agent evaluation guide suggests starting with traces and graders while debugging, then moving to datasets and evaluation runs for repeatable comparison. Trace grading can assess whether an agent picked the right tool, handed off appropriately, followed instructions, or improved after a routing or prompt change. For decisions, keep a labeled dataset of past cases and rerun it whenever you change a model, prompt or routing rule.
Status of OpenAI’s older APIs
In its March 11, 2025 announcement, OpenAI presented the Responses API and Agents SDK as building blocks for agents. It said Chat Completions remained appropriate for developers who didn’t need built-in tools. It also said it planned to deprecate the Assistants API, targeting mid-2026, subject to a later formal announcement. Check OpenAI’s current migration documentation before building on Assistants.
The Bottom Line
Use the Decisions API when typed classification or scoring over text and inline images is the whole job. For anything larger, use the Agents SDK when you want to own the system. Add Temporal for durable waits, or the Agents API for a managed runtime. Consider Bedrock Prompt Flows if you build on AWS. Whichever you pick, attach approvals to side-effecting tools and test with a repeatable dataset. Product features change, so confirm current details in the vendor documentation.
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