Why One Model Should Not Handle Every AI Task
Using one model for every AI task turns model choice into a hidden default. Production workflows need explicit model policies for task type, risk, latency, evidence, fallback, and evaluation.
Read more
Tag
Efficiency Layer
Token Economics: Why Prompt Bloat Kills AI Margins
Token waste is architecture debt. Oversized prompts, broad context, verbose outputs, retries, review, and eval runs compound into the cost per trusted completed unit.
Read more
Semantic Caching Is Harder Than It Looks
Semantic similarity measures intent, not validity. Safe AI caching needs source versions, schemas, model policy, evidence, permissions, review state, and wrong-hit tracking.
Read more