Inversion of Initiative in Human–Agentic AI Interaction: Procedure-Aware Workflow Control for Agent-Based Simulation Development

Agentic coding systems increasingly automate repository inspection, tool use, code generation, testing, and repair, but the human commonly remains responsible for decomposing the task, directing workflow progression, and judging completion. This limits their use in specialised domains where users understand the problem but not the development procedure required to solve it. This study introduces inversion of initiative (IoI) as a human–Agentic AI interaction paradigm in which procedural and modelling initiative shifts from the user to a procedure-aware Agentic AI, while human authority over domain meaning, consequential assumptions, validity boundaries, and progression is retained. The paradigm is instantiated for agent-based simulation development. Starting from an ordinary-language account of the problem, intended use, system, and investigative questions, the Agentic AI constructs and evaluates a structured natural-language simulation specification, resolves modelling and technical gaps through encoded skills, documentation, data, and authorised retrieval, and invokes bounded coding and assurance tools without requiring the user to orchestrate development. A browser platform operationalises IoI through an eight-stage deterministic workflow, versioned artefacts, readiness gates, traceability, semantic checks, controlled returns, and remote execution. In one end-to-end session, the platform transformed a neighbourhood energy-balancing brief containing neither an agent-based model nor a development plan into an AI-authored neighbourhood energy-balancing simulation specification, a verified configurable simulation package, and executed scenario comparison. The results support the feasibility of IoI in this specific case and illustrate an interaction pattern for agentic systems in which procedural and modelling initiative can reside with the AI while accountable domain authority remains human.