Xamun's methodology is published in a leading peer-reviewed information technology journal — independently reviewed, citation-ready, and grounded in real-world delivery data.
Why enterprise AI stalls before it reaches the P&L — the limits of retrieval, what graph memory fixes, and why the interface decides whether any of it pays. Thirteen cited sources across MIT, McKinsey, Gartner, Stanford and NBER.
Read the paper →The xDD (experience-Driven Development) methodology underpins the Xamun Software Factory. The paper sets out a specification-first, AI-augmented approach to software delivery: business specifications are formalised before code is written, AI handles the high-volume boilerplate, and expert engineers govern quality through structured review gates. The result is a delivery model that is faster than conventional outsourcing, more accountable than vibe-coded AI tools, and reproducible enough to publish.
This is not a marketing framework. It is research-grade documentation of a working methodology — independently peer-reviewed and publicly citable.
Reviewed by anonymous academic referees and editors before publication. Not a self-published whitepaper.
DOI-indexed. Discoverable in Google Scholar, OpenAlex, Crossref, Semantic Scholar, and academic databases.
Grounded in 25+ years of enterprise software delivery (Xamun, formerly BlastAsia) — a research methodology validated in production.
For academic, analyst, or journalistic citation:
Maity, A. (2025). The xDD (experience-Driven Development) methodology. Journal of Information Technology Case and Application Research. Taylor & Francis. https://doi.org/10.1080/15228053.2025.2525017
Maity, A. "The xDD Methodology." Journal of Information Technology Case and Application Research, Taylor & Francis, July 2025. DOI: 10.1080/15228053.2025.2525017.
Open frameworks and articles that complement the published research.
The market shift from buying tools to receiving outcomes. Xamun's positioning paper on how AI Transformation is delivered as a service through a closed loop.
Read the framework →Why corporate strategy consistently fails at the execution layer, and how continuous AI intelligence creates a feedback loop that keeps strategy alive.
Read on LinkedIn →Differentiate AI hype from reality. A practical guide for CxOs evaluating AI transformation investments.
View on Amazon →A practitioner's guide to digital transformation for $20M–$200M companies — the audience Xamun was built for.
View on Amazon →
BCG-popularised: transformation is 10% algorithm, 20% technology, 70% people and process. Most AI strategy inverts the ratio.
Most corporate strategies don't fail at the boardroom. They die in the long, quiet stretch between approval and execution.
Twelve diagnostic questions for CIOs and CEOs evaluating AI Transformation vendors. Separates structural fit from sales theatre.
If you're writing about AI Transformation, Outcome-as-a-Service, or AI software delivery methodologies, we're happy to provide briefings, primary data, and customer references.