# [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.

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## 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)