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How to Use AutoGen for Human-in-the-loop approvals
Learn AutoGen human-in-the-loop approvals with step by step workflows, realistic examples, and verified plan notes.
AutoGen works well for human-in-the-loop approvals when you run it like production work: locked brief, SOURCE facts, then review before publish. AutoGen is an open-source Microsoft framework for multi-agent applications where agents converse, plan, and execute tools collaboratively with human-in-the-loop options. Confirm current docs on the official AutoGen site. Start at /explore/autogen.
This guide focuses on human-in-the-loop approvals in detail. Related AutoGen articles: /blog/how-to-use-autogen-for-tool-using-agent-teams, /blog/how-to-use-autogen-for-sandbox-test-before-scale, /blog/how-to-use-autogen-for-role-separated-quality-control.
When this workflow is the right job
Use human-in-the-loop approvals when the deliverable is specifically this AutoGen job. Switch to coder and reviewer agent pairs when that workflow already owns the asset.
Step by step workflow
1. Brief Human-in-the-loop approvals
Write what must stay true for human-in-the-loop approvals in AutoGen before settings or spend.
Brief: Human-in-the-loop approvals Keep: verified SOURCE facts only Avoid: invented pricing or features Success: one reviewable output
2. Open AutoGen for Human-in-the-loop approvals
Use the AutoGen surface that owns human-in-the-loop approvals. Do not mix a neighboring workflow in the same pass.
Surface: Human-in-the-loop approvals Start: pilot with one representative input Plans: microsoft.github.io/autogen
3. Pilot Human-in-the-loop approvals
Run a single human-in-the-loop approvals pilot. Score clarity, grounding, and whether the output is reviewable.
Pilot: Human-in-the-loop approvals [ ] SOURCE facts match [ ] Output reviewable [ ] Settings logged
4. Refine Human-in-the-loop approvals
Change one human-in-the-loop approvals dimension only. Save a template from the best run.
Refine: Human-in-the-loop approvals Change: one control only Keep: SOURCE and success criteria
Practical human-in-the-loop approvals examples
Role charter
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Role charter". Objective: Define a multi-agent or agentic run for Role charter with human gates. Inputs: - Goal for Role charter - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Role charter → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Role charter with roles, gates, and a successful pilot log.
Edge-case check
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Edge-case check". Objective: Define a multi-agent or agentic run for Edge-case check with human gates. Inputs: - Goal for Edge-case check - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Edge-case check → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Edge-case check with roles, gates, and a successful pilot log.
Decision log
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Decision log". Objective: Define a multi-agent or agentic run for Decision log with human gates. Inputs: - Goal for Decision log - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Decision log → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Decision log with roles, gates, and a successful pilot log.
Rate limit
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Rate limit". Objective: Define a multi-agent or agentic run for Rate limit with human gates. Inputs: - Goal for Rate limit - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Rate limit → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Rate limit with roles, gates, and a successful pilot log.
Error alert
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Error alert". Objective: Define a multi-agent or agentic run for Error alert with human gates. Inputs: - Goal for Error alert - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Error alert → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Error alert with roles, gates, and a successful pilot log.
Stop condition
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Stop condition". Objective: Define a multi-agent or agentic run for Stop condition with human gates. Inputs: - Goal for Stop condition - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Stop condition → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Stop condition with roles, gates, and a successful pilot log.
Shared memory note
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Shared memory note". Objective: Define a multi-agent or agentic run for Shared memory note with human gates. Inputs: - Goal for Shared memory note - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Shared memory note → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Shared memory note with roles, gates, and a successful pilot log.
Code exec off
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Code exec off". Objective: Define a multi-agent or agentic run for Code exec off with human gates. Inputs: - Goal for Code exec off - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Code exec off → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Code exec off with roles, gates, and a successful pilot log.
Human approve send
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Human approve send". Objective: Define a multi-agent or agentic run for Human approve send with human gates. Inputs: - Goal for Human approve send - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Human approve send → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Human approve send with roles, gates, and a successful pilot log.
Eval rubric
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Eval rubric". Objective: Define a multi-agent or agentic run for Eval rubric with human gates. Inputs: - Goal for Eval rubric - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Eval rubric → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Eval rubric with roles, gates, and a successful pilot log.
Multi-turn plan
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Multi-turn plan". Objective: Define a multi-agent or agentic run for Multi-turn plan with human gates. Inputs: - Goal for Multi-turn plan - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Multi-turn plan → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Multi-turn plan with roles, gates, and a successful pilot log.
Failure branch
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Failure branch". Objective: Define a multi-agent or agentic run for Failure branch with human gates. Inputs: - Goal for Failure branch - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Failure branch → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Failure branch with roles, gates, and a successful pilot log.
Owner per step
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Owner per step". Objective: Define a multi-agent or agentic run for Owner per step with human gates. Inputs: - Goal for Owner per step - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Owner per step → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Owner per step with roles, gates, and a successful pilot log.
Trace export
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Trace export". Objective: Define a multi-agent or agentic run for Trace export with human gates. Inputs: - Goal for Trace export - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Trace export → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Trace export with roles, gates, and a successful pilot log.
Pilot then scale
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Pilot then scale". Objective: Define a multi-agent or agentic run for Pilot then scale with human gates. Inputs: - Goal for Pilot then scale - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Pilot then scale → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Pilot then scale with roles, gates, and a successful pilot log.
Coder agent
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Coder agent". Objective: Define a multi-agent or agentic run for Coder agent with human gates. Inputs: - Goal for Coder agent - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Coder agent → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Coder agent with roles, gates, and a successful pilot log.
Reviewer agent
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Reviewer agent". Objective: Define a multi-agent or agentic run for Reviewer agent with human gates. Inputs: - Goal for Reviewer agent - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Reviewer agent → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Reviewer agent with roles, gates, and a successful pilot log.
HITL gate
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "HITL gate". Objective: Define a multi-agent or agentic run for HITL gate with human gates. Inputs: - Goal for HITL gate - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for HITL gate → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for HITL gate with roles, gates, and a successful pilot log.
Tool allowlist
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Tool allowlist". Objective: Define a multi-agent or agentic run for Tool allowlist with human gates. Inputs: - Goal for Tool allowlist - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Tool allowlist → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Tool allowlist with roles, gates, and a successful pilot log.
Sandbox sample
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Sandbox sample". Objective: Define a multi-agent or agentic run for Sandbox sample with human gates. Inputs: - Goal for Sandbox sample - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Sandbox sample → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Sandbox sample with roles, gates, and a successful pilot log.
Retry cap
Scenario: A builder configures Human-in-the-loop approvals in AutoGen with focus "Retry cap". Objective: Define a multi-agent or agentic run for Retry cap with human gates. Inputs: - Goal for Retry cap - Agent roles - Tool allowlist - Stop/approval conditions Workflow: Define roles → Connect tools → Pilot Human-in-the-loop approvals for Retry cap → Review → Cap retries → Scale Requirements: - Stay within verified AutoGen capabilities; do not invent features. - Confirm live plan notes on microsoft.github.io/autogen before promising volume. - Change one variable between iterations. - Human-review before external publish, send, billing, or clinical/legal use. - Test on sandbox data before production volume. Expected output: A documented Human-in-the-loop approvals setup for Retry cap with roles, gates, and a successful pilot log.
How to improve human-in-the-loop approvals
Cut noise from human-in-the-loop approvals by removing extra adjectives while preserving SOURCE facts in AutoGen.
Raise quality by insisting on a single success check before debating style.
Make review easier by labeling fields that must never change.
Speed iteration by cloning the last good run and altering only one control.
Stabilize outputs by pinning settings after the pilot is approved.
Reduce rework by rejecting drafts that invent claims.
Improve handoffs by recording which control produced the best result.
Harden the workflow by testing an incomplete input before trusting defaults.
Prompting and usage guidance
Name the human-in-the-loop approvals job, audience, and success check before opening AutoGen.
Paste only verified facts under SOURCE so AutoGen cannot invent details.
Specify the deliverable shape up front.
Call out fixed details versus flexible style choices.
Ask AutoGen to flag unsupported claims before you accept the draft.
Limitations to respect
Check AutoGen plan gates for human-in-the-loop approvals on microsoft.github.io/autogen before you promise timelines.
Keep drafts unpublished until a human confirms SOURCE facts.
AutoGen can be wrong. Treat human-in-the-loop approvals as provisional until review.
If documentation is silent on a claim, leave it out rather than guessing.
Practical tips for this workflow
Pilot once before batching human-in-the-loop approvals in AutoGen.
Keep a reusable template with variables for human-in-the-loop approvals.
Separate creative instructions from SOURCE facts.
Log settings from the best run.
Common mistakes
- Skipping the pilot run before scaling volume
- Inventing pricing, quotas, or features not on official pages
- Mixing unrelated workflows in one session
- Publishing without a human review gate
Treat human-in-the-loop approvals in AutoGen as a production workflow: brief, pilot, refine, then ship with review. Related reading: /blog/how-to-use-autogen-for-tool-using-agent-teams, /blog/how-to-use-autogen-for-sandbox-test-before-scale, /blog/how-to-use-autogen-for-role-separated-quality-control.