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.

curl -sS -X POST "https://api.autumn.ai/task" \
  -H "X-API-Key: $AUTUMN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Build a list of fintech companies", "clarify": true}'

import os, requests

AUTUMN = "https://api.autumn.ai"
HEADERS = {"X-API-Key": os.environ["AUTUMN_API_KEY"]}

# clarify=true: may ask one question, e.g. geography or target count
task = requests.post(f"{AUTUMN}/task", headers=HEADERS, json={
    "prompt": "Build a list of fintech companies",
    "clarify": True,
}).json()

const task = await fetch("https://api.autumn.ai/task", {
  method: "POST",
  headers: {
    "X-API-Key": process.env.AUTUMN_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ prompt: "Build a list of fintech companies", clarify: true }),
}).then((r) => r.json());

With clarify: true the task initializes in plan mode and can stop before execution. Stream the turn (or poll status) to see the question, answer it with POST /task/{task_id}/continue, then let it execute.

# answer the planning question on the same task
curl -sS -X POST "https://api.autumn.ai/task/$TASK_ID/continue" \
  -H "X-API-Key: $AUTUMN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"message": "US only, Series A or later, 50 rows"}'

Review, then continue

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

Python

task_id = requests.post(f"{AUTUMN}/task", headers=HEADERS, json={
    "prompt": "Find Series A fintech companies in the US",
    "clarify": False,
}).json()["task_id"]

# ... wait for the turn to finish, then fetch rows ...
rows = requests.get(f"{AUTUMN}/task/{task_id}/output", headers=HEADERS).json()["rows"]

# ... human reviews rows ...

requests.post(f"{AUTUMN}/task/{task_id}/continue", headers=HEADERS, json={
    "message": "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 to answer.
When continuing after review, restate the current goal as a clear instruction rather than passing the user’s raw words.
POST /task/{task_id}/stop returns a running task to plan if a reviewer needs to intervene mid-run.