Performance threshold definition
Define acceptable performance bounds for each model in production: quality floor, error rate ceiling, latency limit, and confidence score minimum. These become the trigger conditions for escalation review.
Intelligence Layer Strategy
Knowing when to stay with commodity models, when to optimize prompts, and when to invest in fine-tuned or hybrid systems is a product decision — not a technical one. This process builds the rules that govern that decision over time.
Method
Escalation rules define when the current model configuration is no longer sufficient and what the response should be. Without them, teams either over-invest in customization prematurely or under-invest until production failures force reactive decisions.
Define acceptable performance bounds for each model in production: quality floor, error rate ceiling, latency limit, and confidence score minimum. These become the trigger conditions for escalation review.
Categorize the types of failures the model can produce: factual errors, hallucinations, format violations, domain misapplication, and confidence miscalibration. Each type maps to a different escalation response.
Define the escalation sequence: prompt optimization, retrieval augmentation, few-shot enrichment, fine-tuning, hybrid routing, or full model replacement. Each level has a defined trigger and entry criteria.
Establish approval requirements and cost ceilings for each escalation level. Fine-tuning and custom model builds require different governance than prompt changes — rules prevent scope creep.
Define when escalation decisions are reviewed: scheduled cycles, drift alerts, and external trigger events like foundation model updates or regulatory changes that may reset the cost-benefit calculation.
Outputs
Documented quality and risk thresholds per model and workflow, used as escalation triggers.
Visual map of the model escalation sequence with trigger criteria and approval requirements per level.
Mapping of failure categories to the appropriate escalation response and resolution owner.
Schedule and criteria for periodic escalation rule reviews and updates.
Engagement Cadence
Output: a documented escalation framework that governs model upgrade decisions consistently — preventing both premature investment and reactive failure responses.