The Age of Multi-Agent AI: A Paradigm Shift in Programming

This article examines the emerging role of multi-agent artificial intelligence in software development and discusses how agent-based systems may transform programming workflows. It presents a conceptual management model covering task allocation, agent interaction and integration, quality assurance, cascading errors, and human oversight. The article also considers criteria for evaluating system performance, repeatability, controllability, and scaling. The proposed model is conceptual and has not yet been empirically validated.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23768756
Primary Topic
Software Engineering Techniques and Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

The Age of Multi-Agent AI: A Paradigm Shift in Programming

Yana Mishina, Maxim Matveev
Zenodo (CERN European Organization for Nuclear Research)
Software Engineering Techniques and Practices
article

The Age of Multi-Agent AI: A Paradigm Shift in Programming

Yana Mishina, Maxim Matveev
article en

Abstract

This article examines the emerging role of multi-agent artificial intelligence in software development and discusses how agent-based systems may transform programming workflows. It presents a conceptual management model covering task allocation, agent interaction and integration, quality assurance, cascading errors, and human oversight. The article also considers criteria for evaluating system performance, repeatability, controllability, and scaling. The proposed model is conceptual and has not yet been empirically validated.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 7%
Software Engineering Techniques and Practices
DOIOpen Access PDFOpenAlex
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The Age of Multi-Agent AI: A Paradigm Shift in Programming — Yana Mishina, Maxim Matveev · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS