AIF-Planner
Task Decomposition & Dependency Resolution Engine — Converts high-level objectives into executable directed acyclic graphs with resource estimation and constraint validation.
Capabilities
- Objective Parsing: Natural language to structured task graph
- Dependency Resolution: Automatic ordering with cycle detection
- Resource Estimation: Token count, time, and cost projections per task
- Constraint Validation: Policy and capability checks before dispatch
- Plan Optimization: Merge parallelizable tasks; eliminate redundant steps
- Alternative Generation: Produce multiple execution strategies with cost/benefit analysis
Planning Pipeline
Objective → Decompose → Resolve Dependencies → Estimate Resources → Validate → Optimize → DAG
Integration
The Planner feeds directly into the AIF-Orchestrator for execution. Plans are versioned and stored for audit replay.
from runtime.enterprise_control_plane import Planner
planner = Planner()
plan = planner.decompose("Build and deploy a customer-facing chatbot with Stripe integration")
# Returns: DAG with 12 tasks, 4 parallel branches, estimated 850 tokens
Repository
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