Human in the loop - Autumn AI

clarify is the only planning knob. By default (clarify=false) the agent infers reasonable defaults and executes without asking. Set clarify=true when a human is present and a missing answer would materially change the work.

Value	Agent behavior
`false`	Plan, infer defaults, and execute without asking. The default for automation.
`true`	Allow one blocking planning question before execution.

from autumn_sdk import AutumnClient

client = AutumnClient()
result = client.run(
    "Build a list of fintech companies",
    clarify=True,   # may ask one question, e.g. geography or target count
)
print(result.output)

import { AutumnClient } from "autumn-sdk";

const client = new AutumnClient();
const result = await client.run("Build a list of fintech companies", { clarify: true });
console.log(result.output);

Review, then continue

A common pattern: run the first part, let a human review the rows, then continue the same task with corrections.

Python

client = AutumnClient()

task = client.tasks.create("Find Series A fintech companies in the US")
rows = client.tasks.output(task.id)["rows"]

# ... human reviews rows ...

client.tasks.continue_(task.id, "Drop anything past Series A and add the CEO name column")

Because the task_id is durable, you can interleave agent turns and human review as many times as you need. See Follow-up tasks.

Guidance

For background automation, keep clarify=false.
Use clarify=true only when the user is present.
When continuing after review, restate the current goal as a clear instruction rather than passing the user’s raw words.