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Think like a Senior engineer
New
Rating: 5.0 out of 5(9 ratings)
13 students

Think like a Senior engineer

Why simple features are not simple
Last updated 6/2026
English

What you'll learn

  • Learn how to analyze software requirements beyond the obvious
  • Think beyond code and understand the real problem to solve
  • Ask the right questions before building a feature
  • Develop the mindset of a senior software engineer
  • Design reliable real-world features with confidence

Course content

1 section7 lectures1h 37m total length
  • Introduction5:35
  • OTP Verification Isn't Just Sending a Code18:30
  • Designing Coupon Logic for Real Products15:18
  • Creating a Username is Easy, Right?16:30
  • Hidden Complexity of 'Like'14:27
  • Why Users Hate Your Search23:00
  • Before you go3:42

Requirements

  • Basic web development experience on any programming language or framework

Description

Most developers learn programming languages, frameworks, design patterns, and how to write code. However, one of the most important skills in software engineering is rarely taught: how to think through a feature before building it.

In real-world software development, seemingly simple features such as coupon systems, OTP verification, search functionality,  username management, or social interactions can contain hidden business rules, edge cases, security concerns, scalability challenges, and user experience considerations. The difference between a junior implementation and a production-ready solution often comes down to understanding these hidden complexities before writing a single line of code.

In this course, you'll learn how experienced software engineers approach feature development and technical decision-making. Through practical examples and real-world scenarios, you'll discover how to analyze requirements, ask better questions, identify edge cases, evaluate tradeoffs, and make informed implementation decisions. Rather than focusing on a specific programming language or framework, this course focuses on the engineering mindset that applies across technologies, industries, and products.

You'll explore how seemingly straightforward requirements can lead to very different implementations depending on business goals, product constraints, user expectations, and future scalability needs. Along the way, you'll learn how to think beyond the happy path, anticipate potential problems, and design solutions that are reliable, maintainable, and aligned with real-world requirements.

This course is especially valuable in the age of AI-assisted development. Modern AI tools can generate code faster than ever before, but they cannot fully understand your product requirements, business objectives, operational constraints, or long-term architectural considerations. The ability to think critically, analyze requirements, and make sound engineering decisions is becoming more valuable—not less.

Whether you're a junior developer looking to accelerate your growth, a mid-level engineer preparing for senior responsibilities, or a freelancer building products for clients, this course will help you develop the mindset needed to approach software development with greater confidence and clarity.

By the end of this course, you'll have a stronger understanding of how experienced engineers think, enabling you to design better software, avoid common implementation mistakes, and make more informed decisions throughout the software development lifecycle.

Who this course is for:

  • Junior software developers who want to improve their requirement analysis and learn how experienced engineers think through real-world feature implementation.
  • Mid-level developers preparing for senior engineering roles and looking to strengthen their decision-making, system thinking, and problem-solving skills.
  • Freelancers and startup engineers who often need to make product and architecture decisions without dedicated product or engineering teams.
  • Developers using AI coding tools who want to understand the business rules, edge cases, and implementation tradeoffs that AI-generated code can miss.
  • Computer science students who want practical insight into how real software features are analyzed, designed, and implemented in production systems.