Model Churn Exposure

Frontier assistants change month to month, so any agency workflow hard-wired to one model version carries a hidden rework tax: prompts, evals, and client-facing claims that must be retested every release cycle. The framework asks a simple question before you standardise: how much of this deliverable survives a model swap? Workflows that survive are the ones worth productising into retainers; workflows that break are experiments, not delivery lines. OpenAI's October 2, 2026 guide splits the GPT-6 family into three tiers for prototyping, feature development, and multi-step orchestration, which means a single client workflow can now span multiple models with different cost and quality profiles. Anthropic's Claude 5.5 release drew independent scepticism about announcement hype, and a September 2026 technical analysis found top benchmark scores do not reliably predict production performance. Agencies that map churn exposure per deliverable can quote model-agnostic retainers instead of absorbing every release as unpaid rework.