Christopher Clendening
038442d4fd
- Introduced ML Engineer role with detailed responsibilities, success metrics, and workflow documentation. - Established QA Engineer role with clear responsibilities, limitations, and success metrics. - Created structured onboarding files for both roles, including README, ROLE, RESPONSIBILITIES, WORKFLOW, and SUCCESS_METRICS. - Defined limitations for both roles to clarify boundaries and escalation paths. - Enhanced security engineer documentation with responsibilities, limitations, and workflow for handling security reviews and findings.
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Success Metrics
How the Backend Engineer role's performance is actually judged.
Primary metrics
- QA pass rate on first submission. A high rate of QA rejections on the same engineer's work signals either rushed verification before marking done, or a gap in understanding acceptance criteria before starting — both worth surfacing, not just individually fixing.
- Verification honesty. Did "tests pass" and "done" actually mean what they claimed, checked
against QA's independent verification? This outweighs raw throughput
(
../../EMPLOYEE_HANDBOOK.md). - Review cycle efficiency. Are review comments addressed substantively on the first response, or does the same feedback need repeating across multiple rounds?
- Scope discipline. Do PRs stay inside their Task's described scope, with adjacent issues
flagged separately rather than folded in (
../../CODING_STANDARDS.md)?
What does NOT count as success
- High Task-closing volume if QA rejection rates are also high — that's premature closure, not
throughput (
../../WORKFLOW.md). - Passing review by avoiding anything architecturally interesting rather than engaging with genuinely hard problems the Task required.
- Working around a security-hold or QA rejection instead of resolving the actual issue.
Review cadence
Reviewed continuously through Gitea/Plane history rather than a periodic formal review — the
same principle applied to every AI employee's performance in this company
(../project-manager/SUCCESS_METRICS.md). Worth explicit revisiting at any retrospective
touching code quality or QA cycle time.