[Meetup VOD] A 31-year veteran developer shares "How to live as a developer in the AI era"

Facing the AI era

31-year veteran developer Toby's
honest story

“If we no longer need to write code,
what should developers do in the future?”

No developer is immune to the message that AI will replace our jobs. From entry-level candidates preparing for their careers to seniors with decades of experience, everyone is asking the same question. I, too, cannot say for certain how a developer should navigate the AI era. I simply want to share my honest experiences from being in the midst of this transformation.

What is clear is that being a developer is no longer a fixed profession, but a role that is constantly being redefined alongside AI. So, what we need may be the power to embrace and adapt to change, rather than technology itself.

Adding thinking power on top of AI
Augmented Developer

In this course, we will explore together what skills developers should build and in what direction they should grow amidst these changes.

What we'll discuss

Chapter 1. 6 Levels of AI Coding Spectrum

AI coding has been with us for a long time. It has gradually permeated and changed the way we develop, even without us realizing it. In this chapter, we will follow the '6 Stages of the AI Coding Spectrum' to visualize the past, present, and the unfolding future of AI coding.

Chapter 2. Human-AI Collaboration

Development is no longer a stage for humans alone, nor for AI alone. Beyond the simple choice of human-led versus AI-led, various collaboration models exist that suit the situation and the nature of the task. In the second chapter, we explore how humans and AI can coordinate and work together, sometimes even switching roles.

Chapter 3. Architecture Design for Collaboration with AI

Currently, it remains effective for human developers to make and control high-level architecture and design decisions. This chapter covers architecture design methods to maximize collaboration with AI. Well-designed architecture and clean code serve as clear guidelines not only for humans but also for AI, and can even be a more essential standard for AI.

Chapter 4. The Renaissance of Test-Driven Development

TDD is a core workflow for using AI safely and productively and is the most preferred method even among leading AI companies like Anthropic and OpenAI. It is not just a simple development technique, but is establishing itself as a core principle for handling code reliably in the AI era. In this chapter, we will explore the power of that very TDD.

Chapter 5. Using AI as a Learning Catalyst

These days, the focus is solely on “how fast one can develop with AI.” However, pursuing only productivity can cause a developer’s growth to stagnate or even regress. We now need a perspective of utilizing AI while balancing the two pillars of productivity and learning.

Chapter 6. Toby's Recent AI Usage

AI is not simply a tool that writes code for you. In this chapter, we share various examples of how AI is actually utilized in the development and learning process. From analyzing existing code with AI and learning the knowledge derived from that process, to learning by conversing with AI based on reference documentation... we show the vivid ways in which real developers grow alongside AI.

Chapter 7. Survival Strategies in the AI Era: Exploratory AI Usage

We must not become mere "click-only developers." If you want to continue growing, you need a process of reading, reviewing, understanding, and sometimes critically evaluating and actively learning from AI-generated code. In this chapter, we present a new survival strategy called "Exploratory AI Usage". We will discuss how to use AI as a tool for deliberate practice instead of passively consuming it.