Harness as an Asset: Enforcing Determinism via the Convergent AI Agent Framework (CAAF)

TL;DR

This paper introduces the Convergent AI Agent Framework (CAAF), a method to enforce deterministic, safe, and reliable AI behavior suitable for regulated industries, by formalizing domain invariants and structured control mechanisms.

Contribution

The paper presents CAAF, a novel framework that transitions AI workflows from stochastic to deterministic, enabling industrial-grade safety and reliability at commodity costs.

Findings

CAAF's three pillars address different failure modes effectively.

Formalized domain invariants as Harness assets improve reliability.

Empirical results show CAAF's effectiveness across benchmarks and models.

Abstract

Large Language Models produce a controllability gap in safety-critical engineering: even low rates of undetected constraint violations render a system undeployable. Current orchestration paradigms suffer from sycophantic compliance, context attention decay, and stochastic oscillation during self-correction. We introduce the Convergent AI Agent Framework (CAAF), which transitions agentic workflows from open-loop generation to closed-loop fail-safe determinism via three pillars: (1) Recursive Atomic Decomposition with physical context firewalls; (2) Harness as an Asset, formalizing domain invariants into machine-readable registries enforced by a deterministic Unified Assertion Interface; and (3) Structured Semantic Gradients with State Locking for monotonic non-regression. This paper makes two core claims. First, an industrialization thesis: once domain invariants are formalized as an executable Harness, the Harness itself becomes a first-class enterprise asset that compounds in value as foundation models commoditize, and CAAF's ability to deliver its reliability on commodity-tier models makes fully self-hosted, on-premises deployment architecturally feasible for regulated sectors where cloud APIs are not an option. Second, an architectural claim supported by ablation: CAAF's three pillars address complementary failure surfaces and none alone closes the controllability gap at commodity cost. The paper contributes entirely at the orchestration and industrialization layer. Evidence across two complementary benchmarks, three-tier UAI ablations, multi-agent baselines, and a closed-source commodity family replicated by two independent open-weight families, is reported in the body.