Breaking Down Tasks (Task Decomposition) › Decomposing Different Types of Tasks
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Task decomposition isn't one-size-fits-all. Different kinds of requests need different kinds of breakdowns. Let's explore a few scenarios to build intuition.
Sequential Tasks
Some tasks have a natural order where each step depends on the previous one. Our presentation example is like this: you need to do research before creating slides, and you need slides before you can practice.
## Using Claude Sonnet 4.5 for agent-based applications
request = "Plan my weekend getaway to the mountains."
subtasks = decompose_task(request)
## Might produce:
## 1. Find mountain destinations within driving distance
## 2. Check weather forecast for the weekend
## 3. Book accommodation at chosen destination
## 4. Plan activities based on weather and location
## 5. Create packing list for mountain tripNotice the dependencies: you can't book accommodation until you've chosen a destination. You can't create a packing list until you know the weather. The agent needs to recognize these logical dependencies.
Parallel Tasks
Other tasks can be done simultaneously or in any order. If someone asks you to "clean up my inbox, check my calendar, and get a weather update," there's no dependency between these subtasks. The agent could do them in any sequence, or even (in a more advanced system) do them in parallel.
request = "Give me a morning briefing: check my calendar, unread emails, and today's weather."
subtasks = decompose_task(request)
## Might produce:
## 1. Retrieve today's calendar events
## 2. Count and summarize unread emails
## 3. Get current weather and forecast
## 4. Compile briefing summaryThe first three subtasks can happen in any order. Only the last one (compiling the summary) depends on the others.
Nested Tasks
Sometimes a subtask is itself complex enough to need further decomposition. This is where planning gets interesting: you might break down a task, then break down one of the subtasks, creating a hierarchy.
For now, we'll keep things simple with flat lists. But as we build more sophisticated agents, this kind of hierarchical decomposition becomes powerful.