Project delivery and risk
Why big projects overrun and what to do about it: tail risk in cost and schedule, reference-class forecasting, and what actually ships versus what gets started.
Explainers
- Research Explainer · Flyvbjerg et al. (2026)
IT projects often hit budget, but their overruns defy conventional forecasting
Across 11,011 projects, IT had the fattest cost-overrun tail and the only Pareto alpha point estimate at or below 1. The danger is not an ordinary bad average, but a class of risk for which mean-based forecasts can fail outright.
- Research Explainer · Demirer, Musolff & Yang (2026)
AI coding agents triple the code developers write, but shipped software barely budges
A study of more than 100,000 GitHub developers finds that each generation of AI coding tool delivers bigger task-level gains, yet those gains shrink dramatically as they travel down the production chain toward actual releases and end users.
- Research Explainer · Liu (2026)
AI coding assistants fix more code smells than they create, but introduce nearly twice the security issues they resolve
Across 304,362 AI-authored commits from 6,275 GitHub repositories, AI tools are a net positive for surface-level code quality but a net negative for bugs and security vulnerabilities, with 24.2% of all introduced issues persisting indefinitely.