# Cost & Productivity

Control LLM spend with model policy and autonomy defaults, and measure Droid's productivity impact with the measurement surfaces you already have.

Droid gives you two measurement surfaces: [OTEL metrics exported](/enterprise/telemetry) to your own observability stack, and the hosted [Analytics API](/api-reference/analytics). This page is guidance for using them to control spend and to measure what the spend produces.

## Cost management strategies

LLM cost control is a combination of **model policy**, **usage patterns**, and **observability**.

### Constrain the model catalog

Use org-level policies to limit which models are available.

- Prefer smaller models for everyday tasks; reserve large models for complicated refactors or design work.
- Disable experimental or high-cost models by default.
- Enforce model choices per environment, such as cheaper models in CI.

See [Models](/models) for the current model catalog.

### Tune autonomy and context usage

Higher autonomy and larger context windows consume more tokens.

- Set reasonable defaults for autonomy level and reasoning effort.
- Use hooks to cap context size or block unnecessary large prompts.
- Encourage teams to iterate with tighter scopes, such as specific directories instead of entire monorepos.

### Monitor activity and cost

Combine both measurement surfaces:

- Feed [exported activity metrics](/enterprise/telemetry/data-reference), including tool invocations, code activity, and git activity, into your observability stack to build per-team and per-tool dashboards.
- Use the [Analytics API](/api-reference/analytics) for token consumption and cost estimates, which are not exported as customer OTEL metrics.
- Alert on unusual spikes and compare trends before and after policy changes.

## Measuring productivity impact

Cost only matters in the context of outcomes. You can correlate Droid usage with **software delivery and quality metrics** you already track.

Common approaches:

- Build dashboards from exported activity metrics (files and lines modified, commits, pull requests, tool invocations) per team and repository.
- Pull aggregated adoption and productivity signals from the [Analytics API](/api-reference/analytics) for leadership reporting.
- Measure how often Droid is involved in changes that reduce incidents, resolve alerts, or improve test coverage.
- Use [Agent Effectiveness](/agent-effectiveness/overview) to connect agent spend to cycle-time changes on the issues, projects, and pull requests it touched.

These analyses run entirely in your existing observability and analytics stack; Factory's role is to provide clean, structured signals from Droid.

<RelatedLinks>
  <RelatedLink href="/agent-effectiveness/overview" title="Agent Effectiveness">
    Measure how much faster your organization ships with Factory.
  </RelatedLink>
  <RelatedLink href="/api-reference/analytics" title="Analytics API">
    Query credits consumption, tool usage, and per-user productivity metrics.
  </RelatedLink>
  <RelatedLink href="/enterprise/telemetry" title="Telemetry & Analytics">
    Export OTEL metrics to your own observability stack.
  </RelatedLink>
  <RelatedLink href="/enterprise/telemetry/data-reference" title="Telemetry Data Reference">
    Every metric and attribute available for your dashboards.
  </RelatedLink>
</RelatedLinks>