Forecast: By 2028, AI coding will be more expensive than human developers

Heise Online's English edition reports on the same Gartner forecast as CIO.com, adding detail from analyst Tushar Tyagi on transparency gaps, missing cost-optimization features, and the role of uncontrolled agent autonomy. The piece is widely cited in EU enterprise IT circles as

Tyagi identifies three structural drivers: (1) the shift to consumption-based pricing across all major vendors, (2) providers' lack of integrated cost optimization, and (3) uncontrolled autonomy in agent-driven workflows that produces expensive retry loops. Heise's piece is more skeptical than CIO.com's, noting that vendors have an obvious incentive to keep billing opaque and that the 2028 endpoint may actually be conservative if agent loops keep getting longer. Pairs well with the Simon Willison writeup on the OpenClaw public red-team — the same $500 token burn Willison flags as the cost of one experiment is a tiny example of the spending trajectory Heise is reporting on.