The 4-Stage Decomposition Pipeline
When you enter an objective into the AI Task Planner, the system initiates a structured 4-step pipeline entirely within the local browser runtime:
1. Semantic Entity Analysis
The engine evaluates keywords to classify your input into core domains (Software Development, E-Commerce, Academic Research, Digital Marketing, or General Enterprise).
2. WBS Phase Structuring
The objective is decomposed into four sequential stages: (1) Architecture & Discovery, (2) Core Production, (3) QA & Testing, and (4) Launch/Delivery.
3. Skill & Effort Modeling
Baseline hourly estimates are adjusted using empirical skill multipliers (Beginner: 1.3x buffer, Advanced: 0.75x speed).
4. Feasibility & Matrix Sorting
The total workload is matched against your timeline and daily capacity to calculate an instant Feasibility Score (%) and Eisenhower priority tags.
The Mathematical Effort Estimation Formula
Effort calculation is governed by the following deterministic equation:
Total_Capacity = Available_Timeline_Days × Daily_Work_Hours
Feasibility_Score(%) = Min( 100, Round( (Total_Capacity / Total_Estimated_Hours) × 100 ) )
Understanding Priority Allocations
Every subtask is automatically assigned an operational priority tag:
- Urgent & Important (Red Badge): High-leverage dependencies that unblock downstream stages (e.g., database schema design, regulatory compliance, payment gateway integration).
- High Priority (Amber Badge): Core production deliverables that represent primary user value (e.g., UI frontend development, ad copywriting).
- Medium Priority (Indigo Badge): Optimization, secondary asset generation, and integration tests.
- Low Priority (Slate Badge): Post-launch documentation, archive maintenance, and retrospective debriefs.
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