Spec-Driven Development for Agentic Software Engineering: Harnessing Human-Agent Teamwork
On the map: LLM agents and tool use → Software engineering coding agents
Abstract (arXiv)
Context: Software engineering is moving from AI-assisted practices like vibe coding, in which assistants accelerate individual developers, towards Agentic Software Engineering (ASE), in which autonomous agents are delegated goal-level tasks. However, industry reports a productivity paradox: as individual productivity increases, team throughput, review capacity, and stability degrade because team-scale software engineering discipline is neglected. Objective: This paper aims to establish the conceptual and methodological foundations of Spec-Driven Development (SDD) as an enabling discipline for ASE at team scale and characterize the harness, i.e., the technical and methodological mechanisms through which teams govern agent behavior. Method: We conducted a conceptual analysis drawing predominantly on gray literature, including ASE vision and roadmap papers, practitioner reports, talks, and tooling, because peer-reviewed evidence and a shared academic-industrial vocabulary are not yet established. Results: Using a comparative characterization of the paradigm progression as conceptual framing, the article presents (i) a socio-technical model of SDD in which specifications act as the contract substrate between humans and agents; (ii) an operational characterization of the harness, distinguishing the technical harness around the agent from the methodological harness around the team, with worked examples; and (iii) a typology of five human--agent interaction patterns through which the human role is redefined. Conclusion: We conclude that SDD reconstitutes, in specification-centric form, the contracts that vibe coding dissolves: accountability, verifiability, and transferability. Given the immaturity of the evidence base, this work is presented as a first step toward academic-industrial consensus rather than a validated theory, and outlines a research agenda for future empirical validation.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 8 of its 41 references that are in the map. First posted on arXiv 31 Aug 2026.
Builds on
8 of 41 references.
Closest ancestors · 3
Same direction, newest first
- 2025Toward Agentic Software Engineering Beyond Code: Framing Vision, Values, and Vocabulary22 Oct
- 2024Agents in Software Engineering: Survey, Landscape, and Vision13 Sep
- 2024Large Language Model-Based Agents for Software Engineering: A Survey4 Sep
Other references · 5
- 2017Guidelines for including grey literature and conducting multivocal literature reviews in software engineeringcited by 41
- 2024Towards AI-Native Software Engineering (SE 3.0): A Vision and a Challenge Roadmapcited by 30
- 2024Empowering Agile-Based Generative Software Development through Human-AI Teamworkcited by 12
- 2020Reliability in Software Engineering Qualitative Research through Inter-Coder Agreement: A guide using Krippendorff's α & Atlas.ticited by 1
- 2021DevOps Team Structures: Characterization and Implicationscited by 1
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- 2026Human-AI Collaboration and the Transformation of Software Engineering Work
- 2026How Do Practitioners Build SE Agents? Insights from a Mixed-Methods Study
- 2026Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development
- 2026Rethinking Software Engineering for Agentic AI Systems
- 2025Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025
- 2025The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering