Glossary

The terms, defined

Plain, sourced definitions of the language of measuring software development in the AI era.

AI productivity paradox

The AI productivity paradox is the gap between how productive AI coding tools feel and what they measurably deliver. Developers report working faster and produce far more output, yet at the level of the whole organisation, delivery, quality and business outcomes often do not improve to match. More is produced, and less of it can be accounted for.

Independent software audit

An independent software audit is an outside assessment of what an organisation's software development produces and what state its code is in, carried out by a party with no stake in the answer. It reads output and value, quality and technical debt, security and architecture, and reports them to the budget owner in business terms.

Software development ROI

Software development ROI is the return on the money an organisation spends building software: the value produced divided by what it cost. Cost is usually known; value usually is not, which is why most attempts stall. Measuring it means establishing the value side independently, from the work itself, and tracking it over time.

Technical debt

Technical debt is the accumulated cost of shortcuts, ageing design and deferred maintenance in a codebase: work that must be done later to keep software workable. Left unmeasured it compounds, slowing every future release and raising the risk of failure, while staying invisible in status reports and delivery updates.

Technical due diligence

Technical due diligence is the assessment of a target company's software, engineering and technology before a transaction: what state the code is in, what the team produces, and what risks are carried in the codebase. For software intensive businesses it sits alongside financial and legal diligence, because the code is a large part of what is being bought.