Evgeny Bryndin*

Research Department, Research Center «Natural Informatics», Novosibirsk, Russia

*Corresponding Author: Evgeny Bryndin, Research Department, Research Center «Natural Informatics», Novosibirsk, Russia.

Received: August 01, 2025; Published: September 06, 2025

Abstract

A trend of vibe coding has emerged in the world of technology – code generation by neural networks from natural language. For example, Cursor via ChatGPT 4.1 can generate various software modules based on descriptions of their functions in natural language. Creating large software systems from generated modules requires integration. Neurocomplexation of software modules is the process of integrating or combining various software modules to create complex systems based on neural models or artificial neural networks. This approach is proposed to be used in the field of artificial intelligence and machine learning to build complex systems where individual modules interact and jointly perform tasks. Promising areas of application are, firstly, the creation of cognitive systems and intelligent ensembles of agents and assistants. Secondly, modeling of thinking and brain function for research in neuroscience, and thirdly, the development of complex solutions in the field of automation and robotics. The key features of the neural network integration process are, firstly, the integration of modules with different functions (recognition, data processing, training). Secondly, the use of neural network algorithms for adaptation and self-training. Thirdly, ensuring the flexibility and scalability of the system.

Keywords: Neural Network Technology; AI Generation; System Program Code; Modular Neural Integration.

References

1. Alexander Kirichenko. “Neural Network Programming. Neurocomputing Toolkit”. Created in the Intelligent Publishing System Ridero (2020).
2. Evgeny Bryndin. “Self-learning AI in Educational Research and Other Fields”. Research on Intelligent Manufacturing and Assembly 3.1 (2025): 129-137.
3. Andy Smith. “Mastering Prompts: The Art of Interacting with AI”. Samizdat (2024): 63.
4. H Peter Alesso. “Vibe Coding by Example”. Independently published (2025): 329.
5. Greg Lim. “Vibe Coding for Beginners with Python and ChatGPT”. Independently published (2025).
6. David Gillette. “Vibe Coding in Python: The Python Programmers Guide to AI-Powered Programming (Generative AI Mastery)”. Independently published (2025): 171.
7. Addy Osmani. “Vibe Coding The Future of Programming: Leveraging Your Experience in the Age of AI-Assisted Coding (First Early Release)”. O'Reilly Media, Inc. (2025): 250.
8. Evgeny Bryndin. “Creation of Multi-purpose Intelligent Multimodal Self-Organizing Safe Robotic Ensembles Agents with AGI and cognitive control”. COJ Robotics and Artificial Intelligence (COJRA) 5 (2024): 1-10.
9. Evgeny Bryndin. “Creation of Multimodal Digital Twins with Reflexive AGI Multilogic and Multisensory”. Research on Intelligent Manufacturing and Assembly 1 (2024): 85-93.
10. Evgeny Bryndin. “Formation of Motivated Adaptive Artificial Intelligence for Digital Generation of Information and Technological Actions”. Research on Intelligent Manufacturing and Assembly 1. (2025): 192-199.
11. Evgeny Bryndin. Network Training by Generative AI Assistant of Personal Adaptive Ethical Semantic and Active Ontology”. International Journal of Intelligent Information Systems2 (2025): 20-25.
12. Addy Osmani. “Beyond Vibe Coding”. Publisher(s): O'Reilly Media, Inc. (2025).

Citation

Citation: Evgeny Bryndin. “Technological Stages of Neural Network AI Generation of System Program Code Based on Modular Neuro Integration".Acta Scientific Computer Sciences 7.7 (2025): 03-09.

Copyright

Copyright: © 2025 Evgeny Bryndin. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.