[dev_260101_04] Level 3 Task & Workflow Design Decisions
Date: 2026-01-01 Type: Development Status: Resolved Related Dev: dev_260101_03
Problem Description
Applied Level 3 Task & Workflow Design parameters from AI Agent System Design Framework to define task decomposition strategy and workflow execution pattern for GAIA benchmark agent MVP.
Key Decisions
Parameter 1: Task Decomposition → Dynamic planning
- Reasoning: GAIA questions vary widely in complexity and required tool combinations
- Evidence: Cannot use static pipeline - each question requires analyzing intent, then planning multi-step approach dynamically
- Implication: Agent must generate execution plan per question based on question analysis
Parameter 2: Workflow Pattern → Sequential
- Reasoning: Agent follows linear reasoning chain with dependencies between steps
- Execution flow: (1) Parse question → (2) Plan approach → (3) Execute tool calls → (4) Synthesize factoid answer
- Evidence: Each step depends on previous step's output - no parallel execution needed
- Implication: Sequential workflow pattern fits question-answering nature (vs routing/orchestrator-worker for multi-agent)
Parameter 3: Task Prioritization → N/A (single task processing)
- Reasoning: GAIA benchmark processes one question at a time in zero-shot evaluation
- Evidence: No multi-task scheduling required - agent answers one question per invocation
- Implication: No task queue, priority system, or LLM-based scheduling needed
- Alignment: Matches zero-shot stateless design (Level 1, Level 5)
Rejected alternatives:
- Static pipeline: Cannot handle diverse GAIA question types requiring different tool combinations
- Reactive decomposition: Less efficient than planning upfront for factoid question-answering
- Parallel workflow: GAIA reasoning chains have linear dependencies
- Routing pattern: Inappropriate for single-agent architecture (Level 2 decision)
Future experimentation:
- Reflection pattern: Self-critique and refinement loops for improved answer quality
- ReAct pattern: Reasoning-Action interleaving for more adaptive execution
- Current MVP: Sequential + Dynamic planning for baseline performance
Outcome
Established MVP workflow architecture: Dynamic planning with sequential execution. Agent analyzes each question, generates step-by-step plan, executes tools sequentially, synthesizes factoid answer.
Deliverables:
dev/dev_260101_04_level3_task_workflow_design.md- Level 3 workflow design decisions
Workflow Specifications:
- Task Decomposition: Dynamic planning per question
- Execution Pattern: Sequential reasoning chain
- Future Enhancement: Reflection/ReAct patterns for advanced iterations
Learnings and Insights
Pattern discovered: MVP approach favors simplicity (Sequential + Dynamic) before complexity (Reflection/ReAct). Baseline performance measurement enables informed optimization decisions.
Design philosophy: Start with linear workflow, measure performance, then add complexity (self-reflection, adaptive reasoning) only if needed.
Critical connection: Level 3 workflow patterns will be implemented in Level 6 using specific framework capabilities (LangGraph/AutoGen/CrewAI).
Changelog
What was changed:
- Created
dev/dev_260101_04_level3_task_workflow_design.md- Level 3 task & workflow design decisions - Referenced AI Agent System Design Framework (2026-01-01).pdf Level 3 parameters
- Documented future experimentation plans (Reflection/ReAct patterns)