Who did the work: people, AI tools or agents?
Understand how effort and cost split between developers, AI assistants and autonomous agents, workflow by workflow. Then decide where the next AI dollar goes.
| Workflow | Human hours | Agent runs | AI cost |
|---|---|---|---|
| Code review | 420 h | 1,180 | $6.4K |
| Test generation | 96 h | 2,350 | $4.1K |
| Migrations | 310 h | 640 | $5.2K |
Agents changed who does the work. Your reports did not.
Headcount math is broken
Planning still assumes humans write all the code. Capacity models drift every quarter.
Agent work is invisible
Agent PRs land under service accounts or a developer’s name, so their contribution and cost disappear.
Expansion is guesswork
You cannot tell which workflows deserve more automation without comparing human and agent cost per outcome.
A clear split of effort, cost and outcome.
Live in your stack, not another spreadsheet.
Connect your stack
Link Git (GitHub, GitLab, Bitbucket, Azure DevOps), Jira, CI/CD and your AI coding tools with read-only access.
Waydev maps the work
Every PR, review, ticket and AI session is tied to a team, an initiative and the tool or agent that produced it.
Act on Signals
Waydev Agent flags what changed, suggests Goals, and answers follow up questions in plain language.
Waydev reads engineering metadata through read-only APIs. Source code content is never ingested. Visit the Trust Center
Questions engineering leaders ask
How does Waydev tell human and agent work apart?
Is this used to rate individual developers?
What is CAFE(S)?
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