DSA vs Dev ? What to choose ?

What to choose between Dev and DSA if you are in 1st-2nd-3rd-4th Year of your college, or contemplating on switching to a different Role.

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Introduction

Let’s tackle the age-old question of how to decide between a career in development (Dev) and data structures and algorithms (DSA). Moreover, we will discuss a framework that can help you make decisions when you find yourself struggling between two technologies.

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1. Personal Experience

During my college years, like many others, I had to choose between pursuing development or focusing on data structures and algorithms. Recognizing the importance of DSA for securing a job, I dedicated my first two semesters to mastering it. However, my motivations took a turn when I discovered the concept of earning money through internships. The prospect of making $5500 over the summer motivated me to shift my focus to development.

The lesson here is that motivation is strongly tied to monetary outcomes.

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2. Aligning Incentives and Motivations

When I received confirmation of getting into the Google Summer of Code (GSoC), my incentives for development diminished. I knew that I would be making $5500, and my motivation shifted towards competitive programming and preparing for ICPC regionals. While it may sound discouraging to employers, the reality is that when incentives are aligned with monetary rewards, individuals tend to work harder.

It is crucial to recognize when your incentives end in a particular field and move on to the next area where motivations are high.

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3. Learning Curve

In one of my previous job experiences at a big finance company, I found that my incentives were not well aligned. I had a clear understanding of my bonus and salary, and I worked on a specific codebase that was mainly relevant to that company. This situation created a dilemma because investing time in learning the company-specific language would not translate well into future job opportunities. Consequently, my motivation to learn was significantly lower.

This experience taught me the importance of immediate monetary outcomes and their impact on long-term learning.

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4. Earn to Learn!

During my freelancing phase, I ventured into full-stack development without a strong background in it. The key to my learning success was the opportunity to learn on the job. Clients would request projects involving technologies I wasn't yet proficient in, but I took on the projects at a lower price point and used the opportunity to learn and grow.

This approach, where immediate monetary outcomes drive learning, proved to be highly effective.

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5. Long-Term Goals, Motivation, and Market Trends

A friend of mine was determined to enter the Web3 space, enticed by the potential for substantial financial gains. However, after a few weeks of exploration, he realized the immediate need for financial stability. Considering the uncertain market conditions and the potential delay in financial benefits, he decided to shift his focus back to full-stack development. By securing a 100K offer in that field, he regained his motivation and left open the possibility of returning to Web3 in the future.

The lesson here is that long-term goals require careful consideration of immediate financial benefits and sustained motivation.

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My Decision

Web3 vs. AI: Recently, I faced a decision between Web3 and AI. Check out the video to know why I chose Web3 over AI.

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