Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goal-directed, adaptive, and tool-using computational actors. As these agents move from isolated cognitive prototypes into complex distributed workflows, they confront challenges that the Service-Oriented Computing community has studied for more than two decades: composition, interoperability, quality of service, lifecycle management, governance, security, and trust. Yet much of today's agentic AI ecosystem is developing these foundations ad hoc, without the engineering rigour required for dependable enterprise and societal deployment. This paper introduces Agentic Service-Oriented Computing (ASOC) as a new research and practice area concerned with engineering agents as services, orchestrating services through autonomous and semi-autonomous agents, and governing ecosystems of agents and services under constraints of trust, cybersecurity, compliance, performance, and accountability. We articulate six foundational principles of ASOC (harness-ability, composability, lifecycle engineering, trustworthiness by design, goal-driven orchestration, and observability/accountability) and organise a five-dimensional research agenda spanning: (i) agentic services foundations and lifecycle engineering; (ii) composition, orchestration, and interoperability; (iii) governance, observability, and accountability; (iv) security, trust, and risk management; and (v) evaluation, certification, and Agentic QoS. We argue that the Services Computing community is especially well positioned to provide the conceptual and engineering spine for this emerging field, transforming agentic AI from fragmented demonstrations into dependable, service-based systems worthy of human and organisational trust.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 8 of its 34 references that are in the map. First posted on arXiv 14 Jul 2026.
Builds on
8 of 34 references.
Closest ancestors · 3
Same direction, newest first
- 2025Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions29 Oct
- 2023A Survey on Large Language Model based Autonomous Agents22 Aug
- 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework1 Aug
Other references · 5
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2024Executable Code Actions Elicit Better LLM Agentscited by 537
- 2023ProcessGPT: Transforming Business Process Management with Generative Artificial Intelligencecited by 11
- 2024Natural Language-Oriented Programming (NLOP): Towards Democratizing Software Creationcited by 4
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- 2025Agentic Services Computing
- 2025A Survey on Agentic Service Ecosystems: Measurement, Analysis, and Optimization
- 2026Agentic Software: How AI Agents Are Restructuring the Software Paradigm
- 2026The Agent Operating System (AOS): A Reference Operating Architecture for Distributed Agentic Systems
- 2025Governed By Agents: A Survey On The Role Of Agentic AI In Future Computing Environments
- 2026The Internet of Agentic AI: Communication, Coordination, and Collective Intelligence at Scale
- 2026Designing Intelligent Enterprise Agents: A Capability-Aligned Multi-Agent Architecture
- 2026Agentic Configuration Management (ACM): A Reference Configuration Model for Governed Agentic Systems