# A smarter approach to AI cost controls: allocating spend by efficiency | Devin

The features grade developer usage, provide pre-execution prompt feedback, and automatically raise usage caps for high-performing engineers.

- Efficiency Score rates engineers from 0 to 100 based on estimated productive engineering hours per Agent Compute Unit and total volume across recent sessions.
- Devin Coach uses an LLM classifier to flag issues such as vague instructions or unnecessary high-tier model choices before a prompt runs.
- Efficiency-based approvals automatically raise usage limits up to an admin-set ceiling for engineers graded Healthy or Satisfactory.
- Requests exceeding the ceiling or submitted by engineers graded Needs Improvement are routed to administrators with usage and efficiency metrics attached.
- Admins can configure prompt intervention modes to inline suggestions, required confirmations, or disabled.

## Why it matters

Enterprise engineering teams can replace static usage caps with automated, performance-based budget allocation while guiding engineers toward lower-cost prompting habits.

## Sources

- [Devin: A smarter approach to AI cost controls: allocating spend by efficiency | Devin](https://devin.ai/blog/efficiency-based-cost-controls)

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Summarized by dstilled on 2026-10-19. https://dstilled.ai/story/7ce43435-edb7-4c88-a6b6-cb2b0ca2d246