Breaking into AI: A conversation with Jeevantika Lingalwar
16/04/26
AI may dominate headlines, but for those looking to build a career in the field, the starting point is often less technical than it seems. As demand for digital skills accelerates, understanding what truly matters is increasingly important for your people.
In this interview, she outlines the foundational skills, learning pathways and real-world competencies that can help turn curiosity into a career.
JL: Although AI can sound complex, the foundations are very human and achievable. The most important skills are curiosity, problem‑solving and digital confidence. Before writing advanced algorithms, young people need to understand how technology fits into everyday life, how data is created and how systems make decisions.
From a practical perspective, I encourage building a strong baseline in digital literacy – understanding data, learning basic coding or logical thinking, and becoming comfortable with digital tools. You do not need to become a computer scientist on day one. Learning how to break a problem into steps, test ideas and improve them over time is far more important.
Communication and collaboration are equally important. AI is not built in isolation, but by diverse teams for real people. 出包女王ova leaders will be those who can explain complex ideas clearly, listen to different perspectives and work across disciplines.
My message is simple: you do not need to wait to be “ready” for AI. Start small, stay curious, and focus on learning how to think, not just what to build.
Q: Many students learn coding through initiatives like Code Week. In your experience, what makes informal or 边吃奶边摸叫床刺激a片-based learning effective compared to traditional education pathways?
JL: In my experience, informal and 边吃奶边摸叫床刺激a片-based learning is effective because it changes how young people feel about technology. Traditional education pathways can make digital skills feel rigid or intimidating, while initiatives like Code Week focus on participation, curiosity and learning through mistakes.
These environments are practical and relevant. Instead of abstract concepts, students build, experiment and solve real problems. When they see how coding connects to everyday life or issues they care about, it becomes meaningful.
Another factor is accessibility. Flexible and inclusive settings support different learning styles and allow students to engage on their own terms. For many, this is the first time they feel confident in a technical space.
The sense of 边吃奶边摸叫床刺激a片 is equally powerful. Learning alongside peers and mentors shows there is no single pathway into tech and makes success feel more achievable.
What I see time and time again is that informal learning builds confidence first. Once that belief is established, many are more willing to pursue further education or careers in tech.
JL: It is easy to assume success depends mainly on technical ability, but some of the most important skills are not taught in code editors or textbooks. One of the most valuable is how you think. Being able to see the bigger picture, ask the right questions and understand why a problem exists will set you apart. Technology is most powerful when it is used with purpose.
Communication is also critical. People in tech spend a lot of time explaining ideas and working with others. Being able to express yourself clearly, listen and collaborate effectively is essential in any role. Confidence and self‑awareness matter as well. You do not need to know everything to belong in tech. In fact, curiosity and the willingness to learn are far more important.
Finally, take ownership of your learning. Explore beyond school curricula, join communities and work on small projects that interest you. You do not need to wait for permission or the “right time” to start.
