Intent-Conditioned Computation: Rethinking the Computational Paradigm of AI Systems From Stored Programs to Autonomous Model-Oriented Systems

Intent-Conditioned Computation: Rethinking the Computational Paradigm of AI Systems From Stored Programs to Autonomous Model-Oriented Systems | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 3 April 2026 V1 Latest version Share on Intent-Conditioned Computation: Rethinking the Computational Paradigm of AI Systems From Stored Programs to Autonomous Model-Oriented Systems Author : Huiwen Han 0009-0000-5852-5916 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177524397.72082163/v1 136 views 43 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract For more than half a century, computing has been understood through the stored-program abstraction: programs encode explicit control flow, and machines execute them deterministically. This model has shaped hardware architecture, programming languages, and software engineering practice. Contemporary AI systems-particularly foundation models and agentic architectures-operate in ways that increasingly strain this abstraction. Behavior is no longer determined solely by fixed code paths; it is conditioned by high-level intent specifications interpreted by large-scale learned models at runtime. This article argues that we are witnessing a shift in computational emphasis, and introduces Intent-Conditioned Computation (IIC) as a complementary abstraction for understanding this shift. In IIC, intent serves as the primary interface, models function as general-purpose policy engines, and execution unfolds as probabilistic, context-sensitive processes. Crucially, IIC does not replace classical computing: modern AI systems stratify both paradigms into complementary layers, with deterministic infrastructure handling reproducibility-critical tasks while intentconditioned models handle flexible, context-sensitive reasoning. We ground this argument in a concrete open-source case study-the ArchHarness enterprise architecture tool-that demonstrates within a single workflow how stored-program and intent-conditioned computation coexist, divide labor, and interact. We discuss implications for system design, evaluation, and governance, and identify five open research directions for the AI community. Supplementary Material File (main-aai-iic-aim-06.pdf) Download 236.46 KB Information & Authors Information Version history V1 Version 1 03 April 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords agentic ai systems ai system architecture computational paradigm foundation models human-ai interaction intent-conditioned computation probabilistic execution stored-program abstraction Authors Affiliations Huiwen Han 0009-0000-5852-5916 [email protected] Lenovo China View all articles by this author Metrics & Citations Metrics Article Usage 136 views 43 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Huiwen Han. Intent-Conditioned Computation: Rethinking the Computational Paradigm of AI Systems From Stored Programs to Autonomous Model-Oriented Systems. Authorea . 03 April 2026. DOI: https://doi.org/10.22541/au.177524397.72082163/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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