Global Journal of Engineering and Technology Research (GJETR) · Research article · Open access
Building Scalable and Reliable Agentic AI Systems: A Technical Blueprint for Autonomous Intelligence
Dr. Sanjay Nakharu Prasad Kumar
28 November 2025 · Vol. 1, Issue 3, pp. 153-162
DOI: 10.65150/EP-gjetr/V1E3/2025-07
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What is this article about?
Agentic AI systems represent a significant evolution beyond traditional reactive models by enabling autonomous, goal-directed behavior that integrates perception, planning, decision-making, tool use, and continuous learning. This paper synthesizes research and industry advances from 2022–2025 to outline the foundational design principles, technical architectures, and real-world case studies that characterize effective agentic AI.
Article at a glance
- Published
- 28 November 2025
- Volume / issue / pages
- Vol. 1, Issue 3, pp. 153-162
- ISSN
- 3051-3782 (online) · 3051-3774 (print)
- Licence
- CC BY 4.0 — free to read and reuse with attribution
- Peer review
- Double-blind, at least two independent reviewers
- Publisher
- EP Journals Group
Abstract
Agentic AI systems represent a significant evolution beyond traditional reactive models by enabling autonomous, goal-directed behavior that integrates perception, planning, decision-making, tool use, and continuous learning. This paper synthesizes research and industry advances from 2022–2025 to outline the foundational design principles, technical architectures, and real-world case studies that characterize effective agentic AI. We highlight core principles such as outcome-aligned goal formulation, governed autonomy through guardrails and constraints, human oversight and accountability, transparency and auditability, iterative self-improvement, and modular system design. These principles are mapped to concrete architectural components including memory and knowledge systems, planning and reasoning modules, tool-use interfaces, reflection and feedback mechanisms, and multi-agent orchestration frameworks. Through an analysis of key systems—AutoGPT, CICERO, Generative Agents, and Voyager—we illustrate how these components enable long-horizon reasoning, strategic negotiation, lifelike social behavior, and autonomous skill acquisition in open-ended environments. The review emphasizes both the opportunities and the reliability, safety, and alignment challenges inherent in deploying autonomous agents. By integrating interdisciplinary insights across AI engineering, cognitive architecture, and responsible AI governance, this paper provides a roadmap for designing agentic systems that are effective, adaptive, and safe for real-world applications.
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Cite this article
Dr. Sanjay Nakharu Prasad Kumar (2025). Building Scalable and Reliable Agentic AI Systems: A Technical Blueprint for Autonomous Intelligence. Global Journal of Engineering and Technology Research, 1(3), 153-162. https://doi.org/10.65150/EP-gjetr/V1E3/2025-07
@article{Dr2025,
title = {Building Scalable and Reliable Agentic AI Systems: A Technical Blueprint for Autonomous Intelligence},
author = {Dr. Sanjay Nakharu Prasad Kumar},
journal = {Global Journal of Engineering and Technology Research},
year = {2025},
volume = {1},
number = {3},
pages = {153-162},
doi = {10.65150/EP-gjetr/V1E3/2025-07},
url = {https://doi.org/10.65150/EP-gjetr/V1E3/2025-07}
}Questions about this article
Who wrote this article?
Dr. Sanjay Nakharu Prasad Kumar.
Where and when was it published?
In Global Journal of Engineering and Technology Research, Volume 1, Issue 3, pages 153-162, published by EP Journals Group on 28 November 2025.
Is this article free to read?
Yes. It is open access under a Creative Commons Attribution 4.0 (CC BY 4.0) licence, so anyone can read, share and reuse it with attribution.
What is the DOI of this article?
10.65150/EP-gjetr/V1E3/2025-07 (https://doi.org/10.65150/EP-gjetr/V1E3/2025-07).
How do I cite this article?
APA: Dr. Sanjay Nakharu Prasad Kumar (2025). Building Scalable and Reliable Agentic AI Systems: A Technical Blueprint for Autonomous Intelligence. Global Journal of Engineering and Technology Research, 1(3), 153-162. https://doi.org/10.65150/EP-gjetr/V1E3/2025-07
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