Agentic Development Metrics
How we track agentic workflows and team adoption.
Agentic Development Metrics
We track how agentic workflows perform and how the team adopts them. Metrics inform where we invest in agents, where we add guardrails, and how we train people.
Agentic Development Metrics
We track how agentic workflows perform and how the team adopts them. Metrics inform where we invest in agents, add guardrails, and train people.
Usage
How often agents and AI-assisted flows are used: e.g. PRs touched by AI, tasks completed via agents. We avoid vanity metrics; we focus on signals that correlate with delivery and quality.
Example of events we might log (conceptually) so we can aggregate usage:
// Conceptual: event we emit when an AI-assisted action is used
type AgenticEvent = {
kind: 'pr_edit' | 'codegen' | 'review_assist' | 'doc_draft';
tool: 'cursor' | 'copilot' | 'internal_agent';
repo: string;
timestamp: string; // ISO
// No PII; we aggregate by kind, tool, repo, week
};We then aggregate by kind, tool, and time window to see trends (e.g. “review_assist usage went up”) without tracking individuals.
Quality
We care about acceptance rate, revert rate, and time-to-resolution for agent-assisted outputs. We compare against human-only baselines where it makes sense.
| Metric | What it means |
|---|---|
| Acceptance rate | Share of AI-suggested edits that are accepted (as-is or with minor tweaks) in review. |
| Revert rate | Share of merged PRs that are reverted; we watch if AI-assisted PRs revert more often. |
| Time to merge | From first commit to merge; we check that AI doesn’t slow us down with back-and-forth. |
If acceptance rate drops or revert rate rises, we tighten prompts or add more checks (e.g. tests, lint).
Velocity
Impact on cycle time and throughput. We care that AI helps us ship faster without sacrificing quality or sustainability.
We don’t optimize for “more PRs” alone. We look at:
- Cycle time for similar-sized tasks (e.g. “add a docs page”) before and after adoption.
- Whether we’re able to do more in the same sprint without increasing bugs or rework.
Why metrics matter
Metrics help us decide where to invest in agents, where to add guardrails, and how to train the team. We focus on outcomes that align with delivery and quality.