quality_assurance · education · workflow

Duolingo boosts developer speed up to 25% with GitHub Copilot and Codespaces

Duolingo's developers needed to be as efficient as possible, but fragmented tooling across repositories—including third-party tools like Gerrit and PullApprove—created inconsistent workflows and prevented developers from moving easily between projects.

How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Developer initiates coding task
A developer begins writing code or writes natural language comments describing what they want the code to do.
Tools used
GitHub EnterpriseGitHub CopilotCodespacesGitHub's APIsGerritPullApprove
Outcome

GitHub Copilot increased developer speed by at least 25% for those new to a codebase and 10% for familiar ones; a custom Slack integration cut code review turnaround from three hours to one; and Codespaces reduced the largest repo setup time from hours or days to one minute.

What failed first

Relying on third-party tools like Gerrit and PullApprove for code review left Duolingo's primary repositories with widely varying cultures and pull request processes, creating inefficiency and preventing developers from moving easily between repos.

Results
Time savedfrom three hours to one
Volumeat least 25%
Running since2011
Source

https://github.com/customer-stories/duolingo

How we source this →

Grounding & classification
Source type: vendor customer story
31 fields verified against source quotes.
agent assistcode generationcode diff prfailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describededucationcycle time reductionemployee productivitytime savedvendor customer storyback office opsquality assuranceai draft human approval