A Contract-Centered Architecture for Scalable and Manageable Agentic Runtimes

• URL: http://arxiv.org/abs/2608.27086v1
• Date: Thu, 27 Aug 2026 13:09:49 GMT
• Title: A Contract-Centered Architecture for Scalable and Manageable Agentic Runtimes
• Abstract summary: We present four responsibility objects as shared organizational contracts.<n>The central contribution is one bounded, falsifiable hypothesis, P1.<n>This paper contributes a contract-bounded runtime architecture, a source-preserving data substrate, and a falsifiable measurement protocol.
• Score: 4.078233224301927
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Enterprise AI deployment is a coordination problem across business units, application and AI teams, testing, platform engineering, infrastructure, security, operations, and data governance. Use-case benchmarks show whether one agent completes one task, but not how changing capabilities, models, runtime mechanisms, capacity, and enterprise data should be owned, changed, admitted, or evidenced together. We present four responsibility objects as shared organizational contracts: Skill (reusable, versioned capability and workflow asset), Harness (runtime compiler and governor), Scaffold (execution/control boundary and NFR owner), and a stack-external data substrate under independent CIO-governed semantics and telemetry. The runtime core is A = <S, H, X>, with the data substrate outside that stack. The central contribution is one bounded, falsifiable hypothesis, P1 (cost-aware capability-capacity separability): within a declared operating region, changing activated capability preserves the capacity-response interaction within a preregistered equivalence margin, while changing compatible Scaffold capacity preserves capability semantics up to a non-inferiority margin, and the required controls stay within a declared enforcement budget. Six design conditions become measured obligations whose coverage, violations, uncertainty, cost, and exclusions determine whether P1 is decidable. We propose a cluster-period randomized crossover experiment (balanced order, reset/washout, repeated seeds and failure regimes, cluster-aware uncertainty) with a four-state verdict: supported, falsified, conditional-engineering, or inconclusive. This paper contributes a contract-bounded runtime architecture, a source-preserving data substrate, and a falsifiable measurement protocol. It reports no completed implementation, experiment, dataset, or measured result.

Related papers

• Software Engineering in the Agent Era From Trustworthy Change to Human Agent Software Organizations [4.180009544319738]
  Software agents make digital execution elastic.<n>Problem framing, semantic commitment, verification, integration, attention, and residual-risk acceptance remain bounded by human cognition.
  arXiv  Detail & Related papers  (2026-09-04T02:05:35Z)
• EMERGE-Policy: A Robot Mind Emerges Beyond a Single Policy [48.898967774856466]
  EMERGE-Policy coordinates both capability invocation and information exchange.<n>Main Agent retains task-level state within an active context window.<n>Role-specific Sub Agents process perception, execution monitoring, verification, and memory consolidation.
  arXiv  Detail & Related papers  (2026-08-30T16:46:06Z)
• $Z^2$-ACT: End-to-End Verifiable Agentic Intent Control for Open 6G RAN [43.15181031994434]
  We propose a zero-knowledge auditable control and zero-trust verifiable agentic intent architecture.<n>A live large language model is used in the non-real-time path to translate operator intents into Intent Contracts.<n>Results indicate improved actuation filtering and attack resilience at modest latency and signaling cost.
  arXiv  Detail & Related papers  (2026-08-21T12:44:03Z)
• Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels [53.63220028820581]
  Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction.<n>We define trustworthy embodied intelligence as the sustained capacity to execute specified tasks reliably.
  arXiv  Detail & Related papers  (2026-07-28T17:50:44Z)
• PhyAgentOS: A Self-Evolving Operating System for Embodied Agents with Decoupled Cognitive Planning and Physical Execution [49.776611937968]
  We present PhyAgentOS, a foundation delivering scheduling, verification, memory, benchmarking, and safety as system-level services.<n>Its Session-Centered treats a session, not an action, as the minimum unit of scheduling, compatibility, supervised execution, evidence collection, and acceptance.<n>SessionVerifier distinguishes execution termination from semantic task completion via evidence-grounded verdicts of success, failure, or replan.<n> Benchmarking reuses the deployment session and verification path, so results trace to real execution.
  arXiv  Detail & Related papers  (2026-07-18T04:46:53Z)
• ATM: CID-Brokered Pre-Write Admission for Multi-Agent Code Co-Synthesis [0.0]
  The AI-Atomic-Framework (ATM) is a specification-grounded governance substrate for software agents operating within a single governance domain.<n>ATM binds task intent, repository scope, write admission, validation, and evidence obligations into one governance chain.<n>The results support feasibility, auditability, and bounded recoverability within the observed single-domain settings, but do not claim broad comparative superiority or cross-clone governance.
  arXiv  Detail & Related papers  (2026-06-29T16:02:38Z)
• OCELOT: Inference-Leakage Budgets for Privacy-Preserving LLM Agents [32.5466552510287]
  Leakage is cumulative, as individually innocuous releases accumulate across honest-but-curious or colluding sinks.<n>We present OCELOT, a runtime mediator that budgets how much an adversary's belief about a secret may improve.<n>OCELOT attains significantly lower leakage at higher task utility, resists adaptive injection, jailbreak, cumulative inference, and sink collusion.
  arXiv  Detail & Related papers  (2026-06-10T17:13:35Z)
• A Five-Plane Reference Architecture for Runtime Governance of Production AI Agents [0.0]
  We present a reference architecture for the governance of production AI agents.<n>We define a taxonomy of six interruption primitives that generalize allow and deny, state and argue for four correctness invariants.<n>We demonstrate the foreclosure of seven production-agent threats across five concrete adjudications.
  arXiv  Detail & Related papers  (2026-06-10T16:54:47Z)
• A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance [0.22940141855172028]
  This paper presents an assurance framework for Agentic AI systems using Large Language Models (LLMs)<n>Executions are instrumented as Message-Action Traces (MAT) with explicit step and trace contracts.<n>The framework includes stress testing, formulated as a budgeted counterexample search over bounded perturbations.
  arXiv  Detail & Related papers  (2026-03-18T10:23:48Z)
• Automated Self-Testing as a Quality Gate: Evidence-Driven Release Management for LLM Applications [51.56484100374058]
  We present an automated self-testing framework that introduces quality gates with evidence-based release decisions.<n>We evaluate the framework through a longitudinal case study of an internally deployed multi-agent conversational AI system.
  arXiv  Detail & Related papers  (2026-03-13T20:44:15Z)
• To Throw a Stone with Six Birds: On Agents and Agenthood [0.0]
  Six Birds Theory (SBT) treats macroscopic objects as induced closures rather than primitives.<n>We give a type-correct account of agency within SBT.<n>We operationalize this contract in finite controlled systems using four checkable components.
  arXiv  Detail & Related papers  (2026-02-03T10:46:23Z)
• A Mathematical Framework for AI Singularity: Conditions, Bounds, and Control of Recursive Improvement [1.932555230783329]
  We develop an analytic framework for self-improvement that links capability growth to resource build-out and deployment policies.<n>We derive decision rules that map observable series into yes/no certificates for runaway versus nonsingular behavior.<n>The framework yields falsifiable tests based on how fast improvement accelerates relative to its current level.
  arXiv  Detail & Related papers  (2025-11-08T21:25:38Z)
• Trusted Uncertainty in Large Language Models: A Unified Framework for Confidence Calibration and Risk-Controlled Refusal [31.458406135473805]
  We present UniCR, a unified framework that turns heterogeneous uncertainty evidence into a calibrated probability of correctness.<n>UniCR learns a lightweight calibration head with temperature scaling and proper scoring.<n>Experiments on short-form QA, code generation with execution tests, and retrieval-augmented long-form QA show consistent improvements in calibration metrics.
  arXiv  Detail & Related papers  (2025-09-01T13:14:58Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.