LN: Assalaarachchi et al. (2026) — Toward Agentic Software Project Management: A Vision and Roadmap
Bibliographic Reference
Citation: Assalaarachchi, N., Hoda, R., Hassan, A. E., & Grundy, J. (2026). Toward agentic software project management: A vision and roadmap. arXiv:2601.16392. ICSE 2026 AGENT Workshop. https://arxiv.org/abs/2601.16392
Pass 1 — Bird’s Eye View (5 Cs)
| C | Assessment |
|---|---|
| Category | Vision paper + roadmap |
| Context | First paper to explicitly propose “Agentic Project Manager” as a research direction |
| Correctness | Position paper; empirically-grounded vision based on current AI capabilities. |
| Contributions | (1) Concept of “Agentic Project Manager” (APM) in software project management; (2) Taxonomy of autonomy levels (from assistant to junior PM agent); (3) Ethical implications of human role shift to “coach”; (4) Research roadmap for SPM 3.0 |
| Clarity | Excellent. Clear framework and diagrams. |
Relevance: ⭐⭐⭐⭐⭐
This is the most directly aligned paper with PUMA’s long-term vision (Stage 5: Smart PMO). Pioneer paper in “agentic SPM” micro-niche.
Pass 2 — Key Points
The paper proposes Software Project Management 3.0: autonomous AI agents take over routine PM tasks while humans transition to strategic coaching roles. Three autonomy levels:
- Assistant: AI suggests, human decides (PUMA Stages 1–3)
- Co-pilot: AI leads, human validates (PUMA Stage 4)
- Junior PM Agent: AI executes autonomously, human coaches (PUMA Stage 5 vision)
Ethical framing: The human-as-coach model directly supports PUMA’s HITL principle and addresses concerns about job displacement.
Pass 3 — Virtual Reconstruction
Q1 (How can I use this?): Cite as the foundational vision paper for PUMA’s Stage 5 Smart PMO. The 3-level autonomy taxonomy provides the conceptual framework for PUMA’s incremental design (Strategies C → D → long-term).
Q2 (Does it do what it claims?): Vision paper, no empirical results. Consistent with current AI capabilities literature.
Q3 (What if?): What if the “junior PM agent” level requires a different evaluation methodology than the benchmark approach PUMA uses? A future study could evaluate APMs on full project simulations rather than individual task metrics.
PUMA Integration
- Section 1.1: Cite to justify PUMA’s vision beyond MVP → PR-PUMA-Ch1-Introduction
- Smart PMO: Primary reference for Stage 5 → Smart-PMO-Vision
- BMAD: APM’s multi-agent structure maps to BMAD → BMAD-PRD-PUMA
- Hypotheses: Stage 5 targets from H1/H2 extrapolation → EX-Hypotheses-H1-H2
Related Permanent Notes
- PN-MultiAgent-ArchitecturePatterns — specialisation that enables Agentic PM
- PN-PUMA-within-AgenticScience-Trajectory — PUMA’s theoretical position
- PN-IssueTriage-StoryPoints — the specific PM tasks in scope
- PER-Assalaarachchi-Nuwan — key thinker note
- PN-SDD-Framework — BMAD multi-agent methodology