In mid-2025, the debate over AI in programming mirrors historic resistance to earlier breakthroughs in computing. Critics say current AI coding tools often slow developers and create overconfidence, while supporters argue they will eventually transform software creation.

The Register compares this moment to the 1950s, when Grace Hopper faced opposition to high-level programming languages. Similar scepticism greeted technologies such as C, Java, and intermediate representation, which later became integral to modern computing.

Current AI tools face limits in resources, business models, and capability. Yet, as past trends show, these constraints may fade as hardware, training, and developer practices improve. Advocates believe AI will shift human effort toward design and problem definition rather than manual coding.

For now, adoption remains a mixed blessing, with performance issues and unrealistic expectations. But history suggests that removing barriers between ideas and results catalyses lasting change.