Technical English: Getting Understood, Not Just Heard
Practical advice for non-native English speakers in tech on writing clearer tickets, standups, and code comments that actually get read.
Most technical misunderstandings at work have nothing to do with grammar. A ticket gets misread, a Slack message gets ignored, a standup update leaves everyone confused about what actually happened. If you've spent time on security or dev teams with people from a dozen different countries, you already know the real skill isn't fluency — it's precision under time pressure.
Why grammar isn't the bottleneck
Native speakers write confusing tickets constantly. The problem is usually structure, not vocabulary. A message like "the API is being weird again, might be related to that thing from yesterday" fails regardless of accent or grammar score. Compare that to: "POST /users/create returns 500 since 14:02 UTC. Started after yesterday's deploy (commit a3f9c1). Logs attached." That second version works because it front-loads the fact, gives a timestamp, and names the suspected cause. Anyone reading it, in any time zone, knows what to do next.
This matters more in distributed and security teams than almost anywhere else. An incident response channel at 3am doesn't have room for hedging language or long warm-up sentences. If English isn't your first language, you have an advantage here: you're already forced to think about what you're actually trying to say before you say it. Native speakers often skip that step and ramble.
The three sentence shapes that cover 90% of work writing
Most technical communication fits into three patterns:
- State + evidence — "The login endpoint fails intermittently. Error rate is 3% over the last hour, all 502s, all from us-east-1."
- Ask + constraint — "Can you review the firewall rule change before 4pm? It's blocking the deploy."
- Decision + reason — "We're rolling back to v2.3.1. The new rate limiter is dropping legitimate traffic."
Memorize these shapes and you can write almost anything a standup, ticket, or postmortem needs without reaching for fancy vocabulary. Fancy vocabulary is usually where non-native speakers lose time and confidence — hunting for the
Written with AI assistance, reviewed and published by Michal Pilch (CISSP), Korra Studio.
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