1.6 — Task Decomposition Strategies

CCAR-F Domain 1 · Task 1.6

What You Need to Know

Task decomposition breaks complex work into pieces an agentic system can handle.

Fixed Sequential Pipelines (Prompt Chaining)

Each step takes the previous step's output as input. The sequence does not change based on intermediate results.

Suits predictable, structured tasks: code reviews, document processing, data extraction, compliance checks.

Advantages: consistent results, easy debugging, easy monitoring.
Limitation: cannot adapt to unexpected findings.

Dynamic Adaptive Decomposition

The plan evolves as the agent learns. New information may change the remaining steps.

Suits open-ended investigation: legacy system exploration, security audits, research, debugging unfamiliar codebases.

Choosing a Pattern

Task Characteristics	Pattern
Steps known in advance, structured input	Fixed pipeline
Open-ended, unknown scope	Dynamic decomposition
Multi-file code review	Fixed pipeline
Legacy codebase exploration	Dynamic decomposition

The Attention Dilution Problem

Occurs when an agent processes too many items in a single pass. Symptoms:

• Detailed feedback on first few items, shallow analysis on later ones
• Same pattern flagged in one item, approved in another
• Obvious bugs missed in some items while minor issues caught in others

The Fix: Multi-Pass Architecture

1. Per-item local analysis passes — each file/document gets its own pass with full attention budget.
2. Cross-item integration pass — looks for data flow, inconsistent patterns, cross-file dependencies.

A better model or larger context window does not fix attention dilution; the structure does.

Exam Traps

• Suggesting a more powerful model / larger context / better prompt as the fix for attention dilution
• Choosing dynamic decomposition for a structured task with known steps
• Applying fixed pipelines to open-ended investigation
• Batching files without a cross-file integration pass