This is one of the clearest explanations I've seen of why model upgrades should be treated more like distributed system migrations than simple config changes.
The point about "implicit contracts" is especially important. Most failures don't come from the model being worse they come from downstream systems quietly depending on formatting, tool behavior, response length, or other patterns nobody documented.
Shadow traffic, canaries, and evals are necessary, but behavioral diff reports for downstream teams are underrated. In AI systems, a parser, workflow engine, or support automation built months ago can become the real blast radius.
"Code rollouts fail closed. Model rollouts fail confidently." That's a line a lot of teams will recognize after their first production model migration.