Define Task Dependencies Across Agents in One Config

Define Task Dependencies Across Agents in One Config

Many teams lose visibility when one agent's output feeds the next without explicit rules. The Agent Command Center solves this by letting you define task dependencies inside one config object that governs every agent on your runtime.

Key takeaways:

• Store all sequencing rules in a single versioned object.
• Route dependent actions through the approvals inbox.
• Track token usage and cost estimates per execution.
• Maintain human oversight on any step that touches production systems.

Structure Task Dependencies in the Config Object

Start by listing every agent and the exact outputs it must wait for. The config object accepts a dependency map that references prior task IDs and required result fields. This structure keeps changes traceable and prevents silent failures during execution.

Use these fields when you define task dependencies:

• predecessor_task_id
• required_output_keys
• timeout_seconds
• fallback_model
• error_handling_policy
• logging_level

Place the map at the top level of the object so changes remain traceable across runs. Additional fields such as dependency_type and max_wait_time allow fine control over timing without external scripts.

Coordinate Agents with Explicit Sequencing

Task sequencing prevents parallel agents from acting on stale data. Add a sequence array that lists agents in the order they must complete. The control plane enforces these rules at runtime and surfaces any violation in the live logs.

• Agent A finishes and writes result to shared state.
• Agent B waits for Agent A result before starting.
• Agent C only activates if Agent B reports success status.
• Every transition logs intermediate outputs for later review.
• Failed predecessors automatically halt downstream tasks.
• Success metrics update the shared state object.

This approach keeps coordination inside the config object rather than scattered scripts. See how other teams handle similar setups in the guide to choosing a control plane for multi-agent coordination. Similar practices appear in ISO standards for process modeling.

Set Autonomy Levels Tied to Dependencies

Each agent receives an autonomy level that determines whether it can proceed without review. Lower levels require approval for any dependent action. The config object ties these levels directly to the dependency map so rules stay consistent.

Compare autonomy settings in this table:

Lower levels reduce token usage on simple tasks while higher levels protect production. Teams often start at level 2 and adjust after reviewing the first execution history.

Route Sensitive Dependent Actions to Approvals

Any action that follows a dependency and touches external systems must land in the approvals inbox. The config object flags these steps by sensitivity level. Human review occurs before the next agent receives the output.

Follow this checklist when you define task dependencies:

• Mark every external write as sensitive.
• Require human review before the next agent starts.
• Include cost estimates in the approval request.
• Log the approver decision with timestamp.
• Store the edited output back into the shared state.
• Verify token counts against per-role limits.
• Reject actions that exceed defined thresholds.

Review the article on defining action sensitivity levels in the config object for exact syntax. Additional guidance aligns with NIST recommendations on access control.

Monitor Execution History for Dependency Failures

Live visibility shows which tasks completed and which stalled. Inspect logs to see where a dependency broke. The Agent Command Center streams token usage and intermediate outputs so you can diagnose issues quickly.

• Filter history by task ID.
• View token usage per dependent step.
• Compare planned sequence against actual run order.
• Check intermediate outputs for data shape mismatches.
• Export logs for compliance audits.
• Set alerts on repeated dependency timeouts.

The guide to inspecting agent state changes in execution history logs explains the query syntax.

Add Retry Logic Inside the Same Config Object

Dependencies often fail due to transient errors. Define retry rules directly in the object so the control plane handles them without code changes. Each retry respects the original dependency chain and logs every attempt.

Retry rules include:

• max_attempts
• backoff_seconds
• retry_only_on_status_codes
• require_approval_after_failure
• notify_on_final_failure

Version the entire object after each change so you can roll back if retry behavior causes loops. See the retry logic implementation guide for examples.

Validate Dependencies with Runtime Checks

Before deploying a new config version, run automated validation against the current agent fleet. The control plane checks for cycles, missing predecessors, and conflicting autonomy levels.

Validation steps include:

• Scan the dependency graph for circular references.
• Confirm every required_output_key exists in predecessor results.
• Verify timeout values stay within runtime limits.
• Test fallback models against available credentials.
• Simulate one full sequence in a dry-run mode.
• Record validation results in the execution history.

This step catches configuration errors before they affect production. W3C workflow standards provide additional patterns for graph validation that teams can reference.

Compare Config Object Approach to Scripted Agents

Teams often start with scripts and later move to a central config. The table below shows the practical differences.

The comparison of config object versus scripted agents provides more detail on migration steps.

Enforce Human Oversight on Every Real-World Step

The approvals inbox remains the final gate. No dependent action reaches your runtime until you approve, reject, or edit the payload. This human-in-the-loop requirement applies to every sensitive step defined in the config object.

Next steps for your agent runtime:

• Open the config editor and add a dependency map to an existing agent.
• Set autonomy level 2 on the first dependent task.
• Enable cost estimate display in the approvals inbox.
• Run a test sequence and review the execution log.
• Version the object and schedule a weekly audit of dependency changes.
• Export validation reports for team review.
• Compare token burn rates across two config versions.

Frequently Asked Questions

How many dependencies can one config object hold?

The object supports up to several hundred task references without performance impact on your runtime.

Does defining task dependencies require code changes?

No. All rules live inside the versioned config object and apply immediately to every agent you run.

What happens if a predecessor task fails?

The control plane pauses the dependent task and routes the failure notice to the approvals inbox for review.

Can I change dependency order after the first run?

Yes. Edit the sequence array, increment the config version, and the new order applies to subsequent executions.

How do I audit past dependency decisions?

Use the execution history logs filtered by task ID and approver to reconstruct every decision path.