Normalized Telegram record

AI spend should be measured per successful task

Ramp argues for allocating AI cost by use case, owner, completed outcome, failures, retries, review effort, and latency.

Signal contract

  • Ramp argues for allocating AI cost by use case, owner, completed outcome, failures, retries, review effort, and latency.
  • A cheaper model or lower token bill can still be economically worse when it creates more failed runs, longer queues, or expensive human correction.
  • Novelty: structural. Verification: source-inspected.

Source ledger

Publishable sources attached to this record.

1 public source
#SourceRolePublic status
1engineering.ramp.comsourceprimary receiptsource_urls

Observation

Ramp argues for allocating AI cost by use case, owner, completed outcome, failures, retries, review effort, and latency.

Why it matters

A cheaper model or lower token bill can still be economically worse when it creates more failed runs, longer queues, or expensive human correction.

Entities

Ramp

Provenance

This public record is an English normalization of QWG AI Telegram message 2545. The complete original-language post remains the canonical raw message.

Open the original Telegram record