Each guide covers the specific English vocabulary, phrasing patterns, and communication norms for your IT role — not generic business English, but the precise language of backend development, DevOps, frontend engineering, QA, and data science.
A backend developer and a QA engineer have completely different English needs. These guides reflect that. Each one covers the vocabulary and communication patterns that actually appear in that role's daily work.
Every phrase and vocabulary item is illustrated with an example you might actually write or say at work — a PR comment, an incident update, a model evaluation report, a bug description.
Each section links to specific exercises where you can practise the vocabulary in context. Reading about the language is the first step — the exercises are where it becomes automatic.
Each role requires switching between registers: technical documentation, daily Slack messages, formal design documents, interview responses. These guides cover all of them.
REST API documentation, code review communication, system design discussions, database language, and technical interview English. Covers everything from writing OpenAPI descriptions to LGTM vocabulary and CAP theorem discussions.
Incident response bridges, blameless postmortem writing, SLO/error budget discussions, CI/CD pipeline communication, Kubernetes operations vocabulary, and on-call runbook language.
CSS/JS naming conventions, component API documentation, accessibility (WCAG/ARIA) language, Core Web Vitals discussions, design handoff vocabulary, and browser compatibility communication.
Bug report writing, severity and priority language, test plan documentation, Given-When-Then acceptance criteria, TDD/BDD vocabulary, defect lifecycle communication, and automation testing language.
Experiment result communication, model evaluation vocabulary, data storytelling, stakeholder reporting, ML paper reading, feature engineering language, and ML production monitoring vocabulary.
CVE advisory writing, CVSS scoring language, penetration test reports, threat modeling (STRIDE), OWASP Top 10 communication, SOC operations vocabulary, and security incident response chain of command.
ETL/ELT pipeline communication, data modeling discussions, stakeholder reporting, SQL review vocabulary, data quality language, sprint planning for data teams, and interview vocabulary for dbt, Spark, Kafka, and data lakehouse roles.
Model review meetings, experiment discussion vocabulary, paper reading, production ML vocabulary (serving, monitoring, drift), research vs engineering communication, LLM/AI vocabulary, and interview preparation.
Start with the introduction and work through each section. Don't skip sections — even if a topic feels familiar, the vocabulary and phrasing conventions may be new.
Each section ends with a "Practice these skills" box linking to relevant exercises. Follow these links and do the exercises — this is where passive reading becomes active fluency.
Each guide includes 20 key phrases with example sentences. Read these carefully — focus on the example sentences, not just the phrase names. The examples show the phrase in its natural context.
The learning path at the end of each guide gives you a sequenced list of exercises to work through. This is the most efficient route to building fluency in your role's English.
Browse all learning paths organised by role, or explore the full exercise library to find topics relevant to your current work.