The science behind SHIFT
SHIFT is grounded in peer-reviewed research on how AI changes the way engineers think, learn, and build. Papers from the founding organizations are collected here as they are published.
CMM-AISE: A Cognitive Maturity Model for AI-Assisted Software Engineering
Argues that AI-assisted engineering creates a tension between cognitive scaffolding, which strengthens reasoning, and cognitive substitution, which bypasses it — and proposes a maturity model spanning capability dimensions, maturity levels, and stage-dependent risk across the SDLC.
Read the paperRe-Imagining Software Visualization for Spec-Driven Development
Specifications are now first-class artifacts, yet they are still handled as flat text — the same comprehension problem that motivated code visualization two decades ago. Proposes a five-level framework for visualizing SDD projects, from the structure of a single spec through to traceability into generated code and its coevolution over time.
Read the paperSpec-Graph Meta-framework for AI-Assisted Software Development: An Industry Case
Treats specifications as a typed, queryable graph consumed at runtime by software agents rather than as inline prompt text — organised around legibility, addressability and longevity. Instantiated across a 50+ person software organisation with thirteen specification types and four cooperating agents, with 19 practitioners surveyed.
Read the paperWant to research with us?
Co-author a paper, take on a thesis, open your engineering teams to a study, or fund one. The questions behind these papers are bigger than the people currently working on them.