agentic-engineering

Eval-first execution defines acceptance criteria before starting implementation and verifies outcomes after each step. It enforces rigorous evaluation loops across design, coding, and review phases to maintain safety and quality in complex software projects.

Task decomposition partitions complex software projects into modular, agent-sized units. It applies specific rules to break down implementation work, ensuring each unit is appropriately sized for AI agents to execute under strict evaluation loops.

Tiered model routing controls costs by directing task complexity to appropriate model tiers. It tracks per-task metrics and cost data, ensuring computational resources match the difficulty of each decomposed unit within the agent workflow.

Agentic engineering supports large projects by implementing risk, cost, and quality controls. It includes regression checks and guardrails across design, coding, and review phases to maintain safety and quality throughout the workflow.

To kick off the workflow, provide an initial agent decomposition and evaluation plan. This establishes the modular task breakdown and acceptance criteria needed to begin AI-driven implementation under cost and quality controls.

Agent-based workflows require strict guardrails and per-task cost tracking to manage limitations. Without rigorous eval-first execution and tiered model routing, complex code generation tasks may bypass safety checks or exceed budget constraints.