When I graduated almost a year ago, I was completely lost. My mindset was purely academic, I had no internships or real-world engineering experience, and my job search was directionless. I knew Data Structures and Algorithms, but I didn't have the skills that it seemed like employers cared about, and even more importantly I didn't know how to build a career (that's not something they teach you in school). I was applying for roles without even truly understanding what they did.

Into the Wild

Graduating felt like being thrown from a pipeline into a wide open sandbox. Without a playbook for how to navigate this environment, I often felt lost. I started by sending out cold applications to roles on LinkedIn, on top of occasionally reaching out to people at companies to see if I could get an informational interview or a referral. I realized that I had very little experience that employers actually cared about, and didn't have the skills they wanted, so I started working on projects as a way to build my skills, and stand out. I struggled with staying focused, flip-flopping between projects and often leaving them half-baked. I also spent time every day doing LeetCode problems, but it felt like a waste of time because I wasn't getting interviews, and I was also hearing discussion questioning the value of LeetCode, so I stopped doing it.

Despite my struggles to find and stick to a direction, I came out of this time with far greater engineering experience than I had going into it. It was also at this time that I realized that through my projects I was sort of unintentionally learning core full-stack and AI concepts, even thought that wasn't really my target job to begin with. Building a generative AI agent based on a research paper taught me a lot about how AI agents are designed and can be implemented, and building my other projects such as my QuickBooks Data Fetcher taught me how to build an actual web application that integrates AI.

I also realized that spamming cold applications alone was not proving to be a successful strategy, and that in the current market I would likely have to be more strategic and focused if I want to increase my chances.

A New Approach

After a long period of applying to jobs and getting very limited results, I decided to pivot. If I couldn't get experience, I would create it. I adopted an entrepreneurial mindset with the goal of building a real product that people would use. AI was allowing people to do more with less, making it harder to get an entry level job, but making it easier to do things yourself.

At first I had no idea what I was doing. I ended up building an entire project based on just a vague idea and almost zero user research. I eventually realized it wasn't worth pursuing anymore and abandoned it. For my second project, I over-corrected. I spent weeks on research, got stuck in "analysis paralysis", and ended up building and launching something with a weak foundation, and no marketing or growth strategy. I abandoned this as well.

These failures were an important part of my education. I learned through my own personal experience, how to validate an idea, define a customer, and build a hypothesis.

I applied these lessons to my third project, LinkUp BU, a social app for college students. I built it as a full-stack application using Flutter and a Firebase backend. This time, I had a clear problem, a defined user, and a specific solution. This is also where I fully indulged in the powers of AI, learning a lot about working alongside it.

I used AI as a co-pilot for the entire process, handling everything from brainstorming and coding complex backend features like designing user authentication, building a real time chat, and handling notifications. to drafting marketing materials. What could have taken a year, I built in months. This taught me how to be an "AI-native" engineer and thinker. I learned how to balance speed with quality, and more importantly, how to use AI to accelerate my learning, not just bypass it. For example, I like using it to generate boiler-plate code, or to brainstorm, but for deeper architectural issues I will use it to either design a plan and make sure I understand it, or to guide me through building it myself, teaching me as I go. I learned to consider many factors when using AI, including different ways to use it for a job, how well can it get the job done, and what are the benefits and downsides of using it for this job. Using AI is not as simple as telling it "do [X]", and sitting back and waiting. It requires you to think about how you want it to do [X], and what are the implications of it doing [X] instead of using another method. Sometimes it may be best to break down [X] into smaller tasks, or even do just do it yourself, and learning these things takes time.

Throughout my entrepreneurship phase, I also learned more about myself. I learned that I thrive in dynamic environments where I can get variety in what I do. I enjoyed engaging in multiple areas (engineering, user research, market strategy), instead of just focusing on one. This is when I started to think a product focused role would be a good fit for me.

Reflection

Being thrown from a school environment to the real world also taught me broader skills. I became much better at navigating unstructured environments, and handling ambiguity. I learned to handle situations where things don't go the way I expected or hoped for. I think I overall became a better person.

Today, I'm still on the hunt for my first full-time role, but I'm a completely different person.

When I graduated, I barely had any idea of what I wanted to do, and had very limited knowledge about what roles there even were, or what they did. Now, I know that I want to pursue full-stack/product engineer roles with a special interest in integrating AI. I now know that I love building things to solve people's problems, and that I want to pursue entrepreneurship long-term. Now, having a better understanding of how the industry works, I know that my background is likely to have the strongest alignment with early stage startups, and thus I'm adjusting my job search strategy to focus on that. I now have real user-facing projects I can point to as real experience and talk about. I now have real technical engineering skills, including experience with java/typescript, react, python, SQL databases, AI, and software architecture, that I did not have a year ago.

My journey has been unconventional, but it's given me a practical "apprenticeship" in building, launching, and learning.

You can see the projects I've built at https://github.com/enteigss. I'm currently looking for a Full-Stack/Product Engineer roles, and open to connecting on LinkedIn!