The paper introduces Agent-Integrated Software (AIS), a pattern that embeds an intelligent agent within an existing application to address persistent coordination challenges. It defines Intent-Level Interaction Abstraction (IIA) as the task semantics for user inspection and control, and presents interaction contracts that constrain the relationship between AIS execution and IIA states. The authors provide a transition-system model, a compact disclosure contract, and conditional propositions to illustrate how local component validity is insufficient and how admission invariants can be separated from planning, concluding with a research agenda for making agent integration a maintainable software engineering discipline.
By Shengcheng Yu, Chunrong Fang, Zhenyu Chen
arXiv:2609.13672v1 Announce Type: new
Abstract: AI agents can be interrupted while editing files, calling tools, or carrying out multi-step tasks. Restarting repeats completed work, but continuing fr...
By Zhihui Zhang, Wei Liu
arXiv:2608. 13574v1 Announce Type: new Abstract: LLM agents increasingly operate as execution systems that invoke tools, modify local state, use persistent memory, and interact with external protocols.
By Bo Jin, Qiang Jiao, Xin Tong
AgentEval is a system that tracks a contract-bound assessment record throughout a stateful agent’s tool execution, capturing state, events, and evidence to determine whether obligations are satisfied, violated, or unresolved. In 32 tool‑world administrations, independent checks confirmed all 30 complete episodes, while controlled interventions on 48 evidence views uncovered 36 binding faults that hash‑only checks missed. A public‑benchmark study on 192 held‑out executions identified ten completed subgoals within broader task failures and highlighted the impact of missing evidence on overall task success.
By Ruiqi Gao (Alibaba Cloud, Alibaba Group)
arXiv:2606. 02965v2 Announce Type: replace Abstract: As large language models gain tool access and are deployed as autonomous agents capable of editing records, executing transactions, and modifying infrastructure, we still evaluate them based on the sole metric of task completion.
By Victor Ojewale, Suresh Venkatasubramanian
arXiv:2606. 04104v1 Announce Type: cross Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways, and observer-only integrations.
By Zexun Wang
Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions. We treat them as persistent-state systems: the operative system includes retrievable memories, but also task ledgers, permissions, credentials, commitments, provenance and audit records, shared state, trigger conditions, and externally committed effects linked to those records.
arXiv:2609.00015v1 Announce Type: new
Abstract: AI agents powered by large language models are evolving from isolated assistants into heterogeneous systems in which multiple agents, planners, control...
By Dongsheng Chen, Xiangyu Zhao, Xin Yao, Xuetao Wei
The paper introduces Aegis, a runtime governance system for agentic AI that treats model outputs as action proposals and mediates them through a trusted decision layer before tool execution. Aegis evaluates proposals against active policy, resolves provenance server‑side, fails closed under uncertainty, and routes selected cases through a Senate‑style settlement process. In a sandbox evaluation across 6,300 rows, Aegis prevented all governed mock‑tool applications and risky side‑effect completions, preserving provenance and quorum evidence for all settled cases.
By Adam Mazzocchetti
arXiv:2606. 09751v1 Announce Type: new Abstract: Foundation models are moving from response generation into operational roles.
By Arsalan Shahid, Gordon Suttie, Philip Black
Consort is a spec‑first, test‑driven agent framework that enforces engineering discipline through immutable controls, a deterministic orchestrator, and human‑approved gates. It operates on live database branches, guiding role agents through a spec‑first design lane and a test‑driven build lane. The framework claims that enforcing tests and gates in code keeps agent‑written code honest and verifiable, while specialized roles make it maintainable.
By Kevin Hartman
arXiv:2606. 30306v1 Announce Type: cross Abstract: Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions.
By Tianyu Ding, Aditya Nannapaneni, Bingfan Liu, Ling Zhang