Standardize multi-agent AI coding behavior with one config file

Many engineering teams and individual developers—part of an estimated 20 million professional developers globally—now use multiple desktop AI assistants and agent frameworks, which creates inconsistent coding behavior, mismatched prompts, and reproducibility problems across tools and CI. That inconsistency wastes time in debugging and prompt re‑tuning, increases context switching, and raises audit and IP risks for compliance‑sensitive organizations that must trace how code and decisions were produced. You could build a lightweight, single-file standard (for example, “.agentconfig”) that declaratively specifies persona, prompt templates, tool access rules, memory and state policies, API mappings, and audit/logging settings, along with a reference CLI/SDK and thin adapters for major agent frameworks and LLM vendors. Offer an open‑core approach: a free spec and reference implementation to drive adoption, with paid enterprise features for signed configs, centralized policy management, SSO, and long‑term audit storage. The timing is favorable—developers spend roughly $420/year on productivity tooling (an $8.4B addressable market), agent usage is accelerating, and firms are actively seeking auditable, reproducible prompt governance. To stand out, focus on cross‑agent compatibility, a minimal surface area that maps to existing developer workflows (CLI, editor plugins, CI), and high‑quality adapters so the single file actually produces consistent behavior across environments. Strengths include clear enterprise appeal and fast initial uptake if you ship an easy-to-use reference implementation; challenges include building and maintaining many adapters, aligning with evolving vendor APIs and security expectations, and driving enough adoption to overcome network effects—realistic traction will require both developer goodwill and enterprise sales.