What are task dependencies in agent systems?

Task dependencies in agent systems are relationships where one task depends on the result, completion, or state of another task before it can proceed correctly.

Dependencies determine which subtasks can run immediately, which must wait, and which can be executed in parallel.

Why task dependencies matter

When a complex goal is broken into multiple subtasks, those tasks are not always independent.

For example:

> Recommend the best software tool for a team.

Possible subtasks might include:

• identify candidate tools
• collect pricing
• compare features
• evaluate suitability
• prepare recommendation

The agent cannot meaningfully compare pricing or features until candidate tools have been identified.

So:

Identify candidates → Collect information → Compare options → Recommend

Each arrow represents a dependency.

A task may depend on another task's output

A common dependency occurs when one subtask needs data produced by another.

For example:

Task A: Find three available flights.

Task B: Compare the prices of those flights.

Task B depends on the output of Task A because there is nothing to compare until the flights have been found.

A task may depend on completion status

Sometimes a later action should not begin until an earlier task has been successfully completed.

For example:

Verify payment → Create order

The order should only be created after payment verification succeeds.

If payment verification fails, the dependent task may need to be skipped or handled differently.

A task may depend on a condition

Dependencies can also be conditional.

For example:

Check account status

If the account is active:

→ continue with password reset.

If the account is locked:

→ start account-unlock process.

The next task depends on the result of the previous task, not simply on whether it finished.

Sequential dependencies

Some tasks must happen in a specific sequence.

For example:

1. Retrieve customer record.
2. Verify account ownership.
3. Update account information.
4. Confirm the update.

Each step requires information or successful completion from the previous one.

This creates a sequential dependency chain.

Parallel tasks

Tasks without dependencies between them may be able to run in parallel.

For example, after selecting three software tools, an agent might independently:

• collect pricing
• check integrations
• review security features

These tasks may not need to wait for one another.

Once they are complete, another task can combine their results.

Multiple dependencies

A task may depend on several earlier tasks.

For example:

Final recommendation may require:

• pricing comparison completed
• feature comparison completed
• integration analysis completed

The final task should wait until all required inputs are available.

This is sometimes called a join in workflow or graph-based systems.

Dependencies can form a task graph

For complex workflows, tasks and dependencies can be represented as a graph.

For example:

Select candidates

↓

Collect pricing  Check integrations  Compare features

↘    ↓    ↙

Prepare recommendation

The tasks are nodes, while the dependencies define which task can follow another.

This structure helps orchestration systems decide what is ready to run.

What happens when a dependency fails?

If a required dependency fails, the agent should not blindly execute the dependent task.

It may instead:

• retry the failed task
• use an approved fallback
• skip dependent tasks
• ask for missing information
• re-plan the workflow
• escalate to a human
• stop execution

For example, if the agent cannot retrieve an order record, a later task that updates that order should not continue as if the record existed.

Tracking dependencies in state

The agent or orchestration system may track task status such as:

• pending
• ready
• running
• completed
• failed
• blocked

A task can move from blocked to ready when all of its required dependencies have been satisfied.

This helps the system determine what can safely execute next.

Dependencies and prioritization are related

Dependencies define what must happen before something else can happen.

Prioritization determines which available task should be handled first.

For example, three tasks may all be ready to run, but the agent may prioritize one because it is more urgent or more important.

Dependencies therefore constrain the available choices, while prioritization selects among those choices.

In short

Task dependencies are relationships that determine when one subtask can begin based on the completion, output, or result of another task.

They help AI agents and orchestration systems execute work in the correct order, identify parallel opportunities, manage blocked tasks, and avoid performing actions before their required prerequisites are satisfied.