AI ROI
How to measure ROI from AI coding agents honestly
Choose a comparable baseline
Use a recent task of similar scope or run a controlled comparison. Do not compare an agent-assisted feature with an unrelated manual project.
Record what the baseline includes: discovery, implementation, review, release and correction.
Count accepted delivery
Track whether the requested outcome reached production and passed its natural-destination checks. Generated files and passing unit tests are intermediate outputs.
Separate first-pass acceptance from acceptance after repeated correction.
Include all material costs
Add provider usage, operator time, review effort, failed runs and incident recovery. Do not claim every elapsed hour as labor saved.
Record quality improvements separately when they cannot be converted responsibly into money.
Review the trend
One task can be unusually easy or difficult. Compare a consistent set of measures across several projects and look for fewer corrections, shorter cycle time and stable quality.
Use the result to improve the workflow, not to manufacture a headline.
COMMON QUESTIONS
What builders ask next
What is the best ROI metric for a coding agent?
Start with cost per accepted, verified outcome. Add cycle time and defect measures to explain the result.
Can I count estimated hours saved?
Use estimates only when the baseline and method are explicit. Prefer observed operator time and completed outcomes.
How can QERA improve ROI?
QERA reduces preventable rework by resolving costly project decisions before the implementation agent starts.