Fast Agents, Slow Decisions: How Teams Recreate Waterfall at AI Speed
A coding agent can turn a detailed plan into code, tests, configuration, and infrastructure before the next planning meeting. That can reduce the time and effort needed for implementation. It does not settle whether the team chose the right problem, has permission to use the data, understands the operational consequences, or can release the change safely. That gap can make a familiar delivery failure happen sooner. The risk is easy to miss because the first result looks convincing. The pull request is large. The test suite is green. The service starts. People can demo it. By then, a team may have invested enough in one approach that changing direction feels costly or politically difficult. ...
