30 May 2026Community AI

Teaching AI basics at Bendemeer RN

Teaching AI basics at the Bendemeer Resident's Network AI Explorers workshop — AI Explorers workshop at Bendemeer Resident's Network, part of Jalan Besar Constituency.

Today I volunteered as one of the instructors for an AI Explorers workshop at Bendemeer Resident's Network under Jalan Besar Constituency. It was a very different setting from presenting to engineers or technical stakeholders, because the goal was not to show how complex AI can be. The goal was to make AI feel useful, understandable, and safe enough for normal people to try.

The workshop covered AI basics, prompt engineering, effective AI use, and the safety and responsibility of using AI tools. I found myself coming back to one simple point again and again: AI is powerful, but it still needs direction. A vague question can still produce a confident answer, and that confidence is exactly why people need to learn how to guide and check it properly.

For prompting, I tried to make the advice practical instead of too academic:

Give the model enough context, especially who the answer is for and what situation it will be used in.
State the intent clearly, because a model can guess, but it may guess the wrong kind of help.
Set the tone and format when the output needs to be polite, concise, formal, or easy for a child to read.
Ask it to explain assumptions or list things to verify when the answer affects a real decision.

Volunteer instructors at the Bendemeer Resident's Network AI Explorers workshop

AI Explorers workshop poster at Bendemeer Resident's Network

Community learners attending the Bendemeer Resident's Network AI Explorers workshop

The responsibility part was just as important as the prompting part. We talked about not pasting sensitive personal information into tools casually, not trusting every generated answer, and being careful when AI is used for health, finance, legal, or other serious decisions. These are not exciting points, but they are the parts that make AI use sustainable.

I also realised that community teaching is a good test of whether I actually understand something. If I cannot explain hallucination, bias, or prompt context without hiding behind technical terms, then I probably do not understand the practical side well enough. The session reminded me that AI adoption is not only about better models. It is also about helping people build better habits around the tools they already have.

Personal note.