Human Gate Designer

Designs human-in-the-loop review points in DAG workflows: what to present, how to collect feedback, how to route decisions back into the DAG.

When to Use

✅ Use for:

• Deciding WHERE in a DAG to place human gates

• Designing WHAT the human sees at each gate

• Defining HOW feedback routes back (approve/reject/modify)

• Balancing automation speed with human oversight

❌ NOT for:

• Runtime execution of human gates (use dag-runtime

• Temporal signals)

• General UI/UX design (use design skills)

• Chatbot conversation flow (different pattern)

Gate Placement Decision Tree

flowchart TD A{Is the action irreversible?} -->|Yes| G1[Gate BEFORE the action] A -->|No| B{Is output user-facing?} B -->|Yes| G2[Gate AFTER generation, BEFORE delivery] B -->|No| C{Cost > $0.50 for remaining nodes?} C -->|Yes| G3[Gate at the cost threshold] C -->|No| D{Confidence score < 0.7?} D -->|Yes| G4[Gate on low-confidence outputs] D -->|No| N[No gate needed]

Where to Place Gates

Situation Gate Position Why

Irreversible action (deploy, send email, submit) Before the action Can't undo

User-facing deliverable (report, website, PR) After generation, before delivery Quality check

High cost remaining (>$0.50) Before expensive phase Budget confirmation

Low confidence output (<0.7) After the uncertain node Expert judgment needed

Ambiguous task decomposition After planning, before execution Validate the plan

First run of a new template DAG After each phase Build trust gradually

Gate Presentation Design

What the Human Sees

┌──────────────────────────────────────────────────────┐ │ 🔍 Human Review: [Node Name] │ │ │ │ Context: [1-2 sentences: what happened so far] │ │ │ │ Output to Review: │ │ ┌──────────────────────────────────────────────────┐│ │ │ [The node's output, formatted for readability] ││ │ │ [Key decisions highlighted] ││ │ │ [Confidence: 0.82] ││ │ └──────────────────────────────────────────────────┘│ │ │ │ Cost so far: $0.08 / $0.50 budget │ │ Remaining nodes: 4 (est. $0.12) │ │ │ │ [✅ Approve] [✏️ Modify] [❌ Reject] │ │ │ │ If modifying, what should change? │ │ ┌──────────────────────────────────────────────────┐│ │ │ [text input for human feedback] ││ │ └──────────────────────────────────────────────────┘│ └──────────────────────────────────────────────────────┘

Presentation Principles

• Show context, not just output: The human needs to understand what the DAG has done so far, not just the current node's result.

• Highlight decisions: Bold or annotate the choices the agent made. These are what the human is actually reviewing.

• Show confidence: If the agent was uncertain, say so. Low-confidence outputs need more scrutiny.

• Show cost: The human should know what they've spent and what's remaining.

• Make "Modify" easy: A text input for feedback that gets injected into the retry prompt.

Feedback Routing

flowchart TD H[Human decision] --> A{Decision?} A -->|Approve| C[Continue to next wave] A -->|Modify| M[Re-execute node with human feedback injected] M --> V[Validate modified output] V --> H A -->|Reject| R{Reject scope?} R -->|This node only| RN[Re-plan this node with different approach] RN --> H R -->|Entire phase| RP[Re-plan from last successful phase] RP --> H R -->|Abort DAG| AB[Stop execution, return partial results]

Feedback Injection

When the human selects "Modify," their text becomes part of the re-execution prompt:

Original task: [same as before] Previous output: [the output the human rejected] Human feedback: "[the human's modification text]"

Revise your output to address the human's feedback. Preserve the parts they didn't comment on.

Anti-Patterns

Gate After Every Node

Wrong: Requiring human approval after every single node. Right: Gate only at irreversible actions, user-facing outputs, and low-confidence decisions. Most internal nodes need no gate.

Binary Approve/Reject Only

Wrong: The human can only approve or reject, with no way to provide specific feedback. Right: Always include a "Modify" option with a text input for targeted feedback.

No Context in the Gate

Wrong: Showing the human a raw JSON output with no explanation. Right: Show: what the DAG is doing, what happened so far, what this output means, what happens next if approved.