Agentic Software: How AI Agents Are Restructuring the Software Paradigm

• URL: http://arxiv.org/abs/2606.05608v2
• Date: Wed, 10 Jun 2026 02:11:19 GMT
• Title: Agentic Software: How AI Agents Are Restructuring the Software Paradigm
• Abstract summary: We argue that the emergence of AI agents constitutes a fundamental restructuring of what software is.<n>In the former, code is the carrier of pre-written decision logic; in the latter, the agent itself is the decision logic.<n>We conclude with a four-stage roadmap toward self-evolving agent ecosystems.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into static code, and manually adapt that code as requirements evolve. This paper argues that the emergence of AI agents -- systems where large language models serve as the primary reasoning engine, dynamically generating and discarding code as an instrumental resource -- constitutes a fundamental restructuring of what software is, not an incremental tool improvement. We formalize the distinction between traditional deterministic software and agentic software: in the former, code is the carrier of pre-written decision logic; in the latter, the agent itself is the software, and its decision logic is generated at runtime. We trace the historical arc from licensed software to SaaS to Agent-as-a-Service (AaaS), showing that each shift transferred additional complexity away from end-users -- with the agentic shift transferring not just operational complexity but decision-making complexity itself. We introduce Agentic Engineering as an expansion of the software engineering discipline into a new paradigm, distinct in its core object of study (agent systems rather than static source code), its control model (LLM-driven rather than human-predefined), and its human role (intent architect rather than code author). Through analysis of recent benchmark evidence including SWE-bench Verified, EvoClaw, and LangChain's multi-agent coordination studies, we demonstrate both the transformative potential of the agentic paradigm and its current limitations. We conclude with a four-stage roadmap toward self-evolving agent ecosystems and concrete recommendations for practitioners navigating this transition.

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