Published October 27, 2026 | Version v0,6
Preprint Open

Logic on the Fly (LOTF): From Intelligent Interfaces to Dynamically Synthesised Software

Description

The cost of producing executable code continues to fall. The cost of understanding, verifying,
integrating, securing and maintaining the resulting systems has not fallen proportionally. This
asymmetry raises a structural question: must software functionality continue to reside primarily
in persistent, application-specific logic?
Logic on the Fly (LOTF) is proposed as one possible architectural response. The paper
makes four primary contributions:
1. It articulates a conceptual trajectory from dynamic evaluation and object-oriented encapsulation to intent-responsive capability acquisition, while identifying security as an inseparable
architectural concern.
2. It distinguishes implementation maintenance from relevance maintenance—the continued
ability of a machine to meet changing temporal and contextual demands.
3. It characterises the common condition of interface-bounded intelligence, in which interpretive
power operates over a substantially closed set of operational capabilities.
4. It defines a LOTF architecture centred on the possible migration of maintenance effort from
application-specific code toward semantic contracts and runtime governance, augmented by
opinionation, test–repair loops and configuration caching.
These are research proposals, not established results. Sections ?? and ?? supply a concrete
technical scenario and a comparative everyday illustration; Section ?? makes the cost hypothesis
measurable.

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References

  • Sadia Sultana Chowa, Riasad Alvi, Subhey Sadi Rahman, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Md Rafiqul Islam, Mukhtar Hussain, and Sami Azam. From language to action: A review of large language models as autonomous agents and tool users. Artificial Intelligence Review, 59(71), 2026. doi: 10.1007/s10462-025-11471-9.
  • Sumit Gulwani, Oleksandr Polozov, and Rishabh Singh. Program synthesis. Foundations and Trends in Programming Languages, 4(1–2):1–119, 2017. doi: 10.1561/2500000010.
  • Umar Iqbal, Tadayoshi Kohno, and Franziska Roesner. LLM platform security: Applying a systematic evaluation framework to OpenAI's ChatGPT plugins. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, volume 7, pages 611–623, 2024. doi: 10.1609/aies.v7i1.31664. Also arXiv:2309.10254.
  • Alan C. Kay. The early history of Smalltalk. ACM SIGPLAN Notices, 28(3):69–95, 1993. doi: 10.1145/155360.155364.
  • Jeffrey O. Kephart and David M. Chess. The vision of autonomic computing. Computer, 36 (1):41–50, 2003. doi: 10.1109/MC.2003.1160055.
  • Xinzhe Li. A review of prominent paradigms for LLM-based agents: Tool use, planning (including RAG), and feedback learning. In Proceedings of the 31st International Conference on Computational Linguistics (COLING), pages 9760–9779, 2025. URL https://aclanthology.org/2025.coling-main.652/.
  • Peyman Oreizy, Michael M. Gorlick, Richard N. Taylor, Dennis Heimbigner, Gregory Johnson, Nenad Medvidovic, Alexander Quilici, David S. Rosenblum, and Alexander L. Wolf. An architecture-based approach to self-adaptive software. IEEE Intelligent Systems, 14(3):54–62, 1999. doi: 10.1109/5254.769885.
  • Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. ReAct: Synergizing reasoning and acting in language models. In International Conference on Learning Representations (ICLR), 2023. URL https://arxiv.org/abs/ 2210.03629.