English for Science & Tech Professionals
Your code works perfectly. Your data is accurate. So why did the stakeholders look confused?
This is the struggle for many of my students who work in IT, Engineering, and Data Science. You have deep technical knowledge, but translating that "machine logic" into human communication is difficult—especially in a second language.
The "Black Box" Problem
When engineers explain a problem, they often want to explain how they fixed it. They talk about the code, the bugs, and the process.
But managers and clients usually only care about the Input and the Output.
They view your work as a "Black Box." They don't want to know what happens inside the box; they just want to know that the problem is solved.
Strategy: The "Bottom Line Up Front"
Instead of starting with the technical details, start with the impact.
Don't say: "We had a server latency issue because the SQL query was unoptimized, so I re-indexed the database..."
Do say: "The website is running fast again. I optimized the database to prevent this from happening next week."
Technical Vocabulary vs. Jargon
There is a difference between necessary technical terms and confusing jargon. If you are speaking to other engineers, use technical terms. If you are speaking to Marketing or Sales, you must use analogies.
- Don't say "Bandwidth bottleneck."
- Say "It's like traffic on a highway."
Confidence in Q&A
The scariest part of a tech presentation is often the Q&A. You worry you won't understand the question. In my classes, we practice specific phrases to verify questions before you answer, giving you time to think and ensuring you don't answer the wrong thing.
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