More Than Coding: Building a Professional Identity in a Digital World
I used to believe that good work would speak for itself. As long as I developed strong technical skills, completed my projects carefully, and continued improving, I thought those efforts would naturally lead to future opportunities. The PIE Theory from The Networking Institute challenged that assumption and became the idea that stood out to me most this week. It helped me realize that career development depends not only on what I can do, but also on how others understand my abilities and whether my work is visible to the right people. This was especially meaningful to me as a computer science student because technical ability is important, but simply having those skills does not guarantee that professors, recruiters, or future employers will know what I have accomplished. I now see professional image and exposure as ways of making real work visible rather than simply promoting myself.
This idea also changed how I think about my online professional identity. This week, I added more information to my LinkedIn profile about my education, interests, skills, and experience, but I also realized that my profile is something I should continue improving over time. Cotriss’s article about social media screening showed me that employers can use online information to learn more about job candidates, while Asghar’s article emphasized how platforms such as LinkedIn can help people build professional networks and increase their visibility. I plan to keep my LinkedIn information accurate and updated, add future projects and experiences, and be thoughtful about what I make public online. I also want to continue improving my GitHub profile because it gives me another way to show what I can actually create. At the same time, Hoover, Rupp, and McCauley’s research on cybervetting reminded me that social media screening also raises questions about privacy, fairness, and bias. This made me think that employers should focus on information that is actually related to a person’s ability to perform a job.
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When I searched for how social media and online platforms are used professionally in computer science, I found that GitHub can play an important role in a technical job search. GitHub’s official guidance explains that a profile can help hiring managers understand a person’s technical skills and experience, especially when users highlight strong projects and provide clear documentation. I also found that LinkedIn can help professionals build their networks, connect with recruiters, and discover new career opportunities. This is relevant to me because I already use GitHub to create repositories, upload projects, and look at other people’s code to learn how they approach programming problems. In the future, I want to organize my strongest projects more carefully and make them easier for other people to understand. LinkedIn and GitHub can serve different purposes, but together they can show both my professional background and evidence of my technical work. I now see professional networking as more than simply adding connections online. Sharing useful work, learning from others, and participating in technical communities can create connections that may later lead to internships, research opportunities, or jobs.
Digital leadership has become more meaningful to me because of both my computer science background and my current agricultural research experience. My current lab conducts field monitoring of agricultural insect pests and is also exploring how newer technologies, including AI-assisted and automated monitoring, could improve this type of work. This experience has helped me see that using technology in agriculture is not simply about applying an algorithm. A system also needs accurate data, reliable identification, and the ability to perform under changing field conditions. When I searched online for examples of digital technology in agriculture, I found that the USDA’s National Institute of Food and Agriculture (NIFA) supports research using machine learning, autonomous systems, remote sensing, and other intelligent technologies for agricultural monitoring and decision making. I also found NIFA-funded projects that use image-based AI to identify agricultural pests and support pest management. These examples are closely connected to the kind of work I am interested in pursuing in the future. I hope to explore areas such as AI agents, computer vision, and intelligent detection systems and apply them to agriculture or biotechnology. To me, digital leadership in this area means being able to connect technical knowledge with real-world problems, evaluate whether a technology actually works, and help improve it when limitations appear.
The IEEE Computer Society also describes communication, collaboration, problem-solving, and decision-making as important skills for people moving toward leadership roles in software engineering. I think these skills are especially important when technology is used across different fields because a digital leader needs to communicate with people who may have very different areas of expertise. If I continue toward AI and agricultural or biotechnology applications, I will need not only programming and technical skills but also the ability to understand research problems, work with domain experts, explain technical ideas clearly, and make responsible decisions about how technology is used. Moving forward, I want to continue developing my AI and programming skills while also improving how I present my work through LinkedIn, GitHub, and professional connections. I hope that combining these skills will allow me to contribute to practical technologies and eventually take a leadership role in solving real-world problems.
