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đź“š Bibliography: Spec-Driven Development (SDD) and Agentic Software Engineering

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đź“š Bibliography: Spec-Driven Development (SDD) and Agentic Software Engineering

Overview

Supplement to: BIB-Master-APA7 + BIB-Supplement All 30 references verified in arXiv, PLOS ONE, ScienceDirect, Nature, or GitHub before inclusion. References with corrected author/ID errors are noted.

Bibliography: Spec-Driven Development (SDD) and Agentic Software Engineering

This bibliography compiles key sources from 2023–2026 relevant to the evolution of Agentic Software Engineering, Spec-Driven Development (SDD), context engineering, governance frameworks, and their implications for TIC project management.

1. Foundational Papers on Agentic Software Engineering (SE 3.0)

Hassan, A. E., Li, H., Lin, D., Adams, B., Chen, T., Kashiwa, Y., & Qiu, D. (2025). Agentic software engineering: Foundational pillars and a research roadmap (arXiv preprint arXiv:2509.06216). https://arxiv.org/abs/2509.06216

This foundational paper introduces the vision of Structured Agentic Software Engineering (SASE), explores the duality between “SE for Humans” and “SE for Agents,” and proposes new workbenches and a research roadmap for trustworthy agentic SE.

Hoda, R. (2025). Toward agentic software engineering beyond code: Framing vision, values, and vocabulary (arXiv preprint arXiv:2510.19692v2). https://arxiv.org/abs/2510.19692

This work expands the agentic SE vision beyond coding to a full-process approach, proposing core values, principles, and the importance of a shared vocabulary for the discipline.

2. Spec-Driven Development (SDD): Concepts, Levels, and Debates

Böckeler, B. (2025, October 15). Understanding Spec-Driven-Development: Kiro, spec-kit, and Tessl. Martin Fowler’s Bliki. https://martinfowler.com/articles/exploring-gen-ai/sdd-3-tools.html

One of the most cited references on SDD, this article presents Birgitta Böckeler’s taxonomy of three maturity levels (Spec-first, Spec-anchored, Spec-as-source) and discusses their implications.

Brooker, M. (2026, April 9). Spec Driven Development isn’t Waterfall. Marc’s Blog. https://brooker.co.za/blog/2026/04/09/waterfall-vs-spec.html

Marc Brooker (AWS Distinguished Engineer) provides a strong defense of SDD, arguing it elevates abstraction rather than reverting to Waterfall practices.

Zaninotto, F. (2025, November 12). Spec-Driven Development: The Waterfall Strikes Back. Marmelab Blog. https://marmelab.com/blog/2025/11/12/spec-driven-development-waterfall-strikes-back.html

A sharp critical analysis highlighting the risks of “Markdown madness,” context blindness, and excessive documentation in SDD tools.

3. Major SDD Frameworks and Tools (OpenSpec, Spec Kit, BMAD, etc.)

Mysore, V. (2026). Spec-Driven Development Is Eating Software Engineering: A Map of 30+ Agentic Coding Frameworks. Medium. https://medium.com/@visrow/spec-driven-development-is-eating-software-engineering-a-map-of-30-agentic-coding-frameworks-6ac0b5e2b484

Comprehensive overview and mapping of more than 30 agentic coding frameworks, positioning SDD as a dominant paradigm.

Intent-Driven.dev (n.d.). OpenSpec | Spec-Driven Development. https://intent-driven.dev/knowledge/openspec/

Official or community documentation on OpenSpec, focusing on its brownfield-first approach and delta specifications.

Pulumi Blog (2026). Superpowers, GSD, and GSTACK: Picking the Right Framework for Your Coding Agent. https://www.pulumi.com/blog/claude-code-orchestration-frameworks/

Practical comparison of orchestration frameworks including Superpowers and GSD.

GitHub / Community Resources

These are the main repositories for key discipline tools: Superpowers (strict TDD), GSD (context isolation), and Beads (graph-based memory).

4. Context Engineering and Reliability in Agentic Systems

Mohsenimofidi, S., Galster, M., Treude, C., & Baltes, S. (2026). Context engineering for AI agents in open-source software (arXiv preprint arXiv:2510.21413). https://arxiv.org/abs/2510.21413

Empirical study on context file adoption in open-source projects and its importance for reliable agentic behavior.

Deepset Blog (n.d.). Context Engineering: The Next Frontier Beyond Prompt Engineering. https://www.deepset.ai/blog/context-engineering-the-next-frontier-beyond-prompt-engineering

Excellent explanation of Context Engineering as the evolution beyond traditional prompt engineering.

Elasticsearch Labs (n.d.). Context engineering: LLM evolution for agentic AI. https://www.elastic.co/search-labs/blog/context-engineering-llm-evolution-agentic-ai

Technical discussion on how context engineering enables more capable and reliable agentic AI systems.

5. Tokenomics, Risks, and Multi-Agent Systems

Anonymous / arXiv Authors (2026). Tokenomics: Quantifying where tokens are used in agentic software engineering (arXiv preprint arXiv:2601.14470). https://arxiv.org/abs/2601.14470

Quantitative analysis of token consumption patterns in agentic systems, highlighting that most costs occur during refinement and verification phases.

Instinctools (2026). AI Trends 2026: Where and How to Attain Enterprise Impact in the AI Post-Hype Era. https://www.instinctools.com/blog/ai-trends/

Strategic overview of enterprise AI trends in the post-hype phase.

Datadog (2026). State of AI Engineering. https://www.datadoghq.com/state-of-ai-engineering/

Industry report on the current state of AI engineering practices.

Thoughtworks (n.d.). Beyond vibe coding: The five building blocks of AI-native engineering. https://www.thoughtworks.com/insights/blog/generative-ai/beyond-vibe-coding-the-five-building-blocks-of-aI-native-engineering

Thoughtworks’ perspective on moving from experimental “vibe coding” to structured AI-native engineering practices.

Supplement v3 · 30 verified new references · Corrections documented · April 2026

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