Localization tooling has a deceptively hard job: it has to feel fast for translators doing thousands of small edits, while staying correct across many locales and edge cases. This is the story of [feature/area] I worked on.
The problem
[Describe the problem — e.g. translators were slowed down by X / a workflow was missing Y / a system didn’t scale to Z]. Concretely, [the pain point], which affected [who — e.g. a specific locale team / all reviewers / the community at large].
The signal that this mattered: [how the problem surfaced — bug reports / community feedback / a metric].
The approach
I tackled it by [high-level approach]. The work touched:
- [Component 1] — [what changed].
- [Component 2] — [what changed].
- [Component 3] — [what changed].
The trickiest part was [the hard part — e.g. handling translation memory consistency / a performance constraint / backwards compatibility]. I resolved it by [solution].
Trade-offs
| Option | Pro | Con | Chose? |
|---|---|---|---|
| [Option A] | [pro] | [con] | [yes/no] |
| [Option B] | [pro] | [con] | [yes/no] |
I went with [chosen option] because [reasoning].
Shipping it
The change rolled out [how — e.g. behind a flag / to a single locale first / all at once] in [ship date]. Because Pontoon is open source, the work landed publicly: [link to PR / issue].
Impact
- [Metric 1 — e.g. reduced X by N%].
- [Metric 2 — e.g. unblocked workflow for N locales].
- [Qualitative — e.g. positive feedback from the community].
What I’d do differently
In hindsight, [reflection — e.g. I’d have invested in tests earlier / scoped the rollout tighter]. [Optional next step or follow-up work that came out of it.]