AI, Critical Thinking, and Software Engineering

Participants: Sirwan and Foad

Foad shared his experiences with DeepSeek and Z.ai. He had noticed some right-to-left (RTL) text issues in DeepSeek, while Z.ai stood out for following a long text, keeping its context, and answering detailed questions.

The Future of Software Engineering

We discussed the familiar question, “I want to become a software engineer. Where should I start?” Learning a language, practising the fundamentals, and building projects are still useful starting points, but AI is changing how the work gets done.

AI can already generate, explain, debug, and modify code. We expect engineers to spend more time understanding the problem, setting clear requirements, choosing an approach, and checking whether the result is correct. Programming fundamentals will remain important for making technical decisions and catching mistakes in AI-generated work.

Skills to Keep Practising

We highlighted English and communication for learning, collaborating, and explaining requirements, alongside problem-solving and critical thinking. Useful practice includes breaking a difficult problem into smaller parts, understanding the underlying concepts, comparing trade-offs, and questioning AI answers instead of accepting them automatically.

We also talked about continuing to challenge our minds through mathematics, reading, and other demanding activities. AI can make intellectual work easier, but relying on it for every difficult step could reduce our opportunities to practise independent reasoning. As we put it, having a car doesn’t mean we should stop walking.

Main takeaway: As AI takes on more implementation, understanding what to build, communicating it clearly, and judging the result will matter more than memorising syntax alone. Use AI to extend your abilities while continuing to think for yourself.