Every claim on this blog is traced to a named study, survey or report: no invented statistics, no recycled marketing numbers. If we can't source it, we don't publish it.
A study-by-study look at what happens when AI-generated code meets real users, drawing on Veracode, Stanford and CodeRabbit research.
SECURITYVeracode, GitGuardian and SecurityWeek data on how often AI-generated code introduces vulnerabilities, and why the numbers keep climbing.
MAINTAINABILITYGitClear's 211-million-line analysis on code churn and copy-pasted code, and what it means for a codebase's shelf life.
TRUSTStack Overflow's 2025 survey shows trust falling as adoption rises. Snyk's research shows the opposite belief in practice. Both are true at once.
PRICINGWhat actually drives the price of a code audit or hardening engagement, and why lines of code is only half the formula.
GUIDEThree terms that get used interchangeably and shouldn't be. What each one actually delivers, and which one you need.
CHECKLISTA practical, non-theoretical checklist for the gap between "it works on my machine" and "it survived launch day."
SECURITYWhat the research says about Copilot-class tools specifically, and the concrete checks that catch what they miss.
GUIDESignals that separate a prototype that's fine to leave alone from one that's a genuine liability.
HISTORYHow a February 2025 post by Andrej Karpathy became Collins Dictionary's word of the year and reshaped how software gets built.