Explore all chapters from "AI changes the tools, you still own the craft"
Learn about Hoang Nguyen, Director of Engineering at ShopBack and author of 'AI changes the tools, you still own the craft'. Discover his journey from software engineer to engineering leader.
From curiosity to realization: How AI tools evolved from experimental to essential, and why this book exists to help engineers, leaders, and teams navigate the transformation thoughtfully.
How AI evolved from hype to baseline job expectation. Practical guidance for engineers, teams, and leaders navigating the shift from excitement to real integration in software development workflows.
The historical evolution of AI from research labs to everyday accessibility. How ChatGPT transformed AI from a specialized tool for experts into something anyone can use, marking the true turning point in AI adoption.
Understanding why AI isn't a passing trend and why coding became the perfect entry point. How accessibility revolutionized AI adoption and why engineers can't afford to ignore this transformation.
Why writing code was never the hard part of engineering. How AI reveals that problem-solving, not coding speed, is the real value of software engineers—and how to thrive by focusing on the why, not just the how.
How to work with AI using the junior engineer mindset. Understanding what AI can and can't do, how to give clear guidance, review its work, and maintain decision-making authority while delegating effectively.
A complete breakdown of engineering work and AI's real capabilities. Where AI excels (code, testing, docs) versus where it falls short (judgment, problem understanding, long-term design). Includes a practical decision matrix for when to use AI versus human-led approaches.
How AI transforms the traditional development process from linear steps to an interconnected web. The new workflow: Think → Prompt → Code → Review → Ship faster. Moving from 'time-to-code' to 'time-to-insight' with shorter feedback cycles and continuous AI collaboration.
The realistic math behind AI speed improvements. Breaking down where AI actually helps (50% coding, 40% planning, 30% monitoring) to reveal ~30% total workflow improvement—not 10x. How teams must change their approach to see real gains.
How AI transforms team composition from scaling by headcount to scaling by intelligence. Moving from '2 seniors + 4 juniors' to '2 seniors + 2 juniors + AI'. Building smaller, smarter, more fluid teams while still investing in junior talent.
How AI transforms product-engineering collaboration from transactional handoffs to shared problem-solving. Breaking down silos, working in one repo, and shifting from execution bottlenecks to alignment bottlenecks. Speed comes from thinking together, not just coding faster.
The organizational foundation for AI success. Why weak context, not weak models, holds teams back. How to centralize knowledge, write for robots, add semantic structure, and treat information as a product. Setting up AI like you would onboard a new engineer.
How engineers can evolve and thrive as AI shifts the baseline. From code writer to problem solver, debugger, and AI guide. Master fundamentals, practice problem-first thinking, and treat AI as a build engine. The future belongs to engineers who think, not just type.
The concluding message: engineering fundamentals haven't changed. AI can't solve problems, understand trade-offs, or care about impact—that's still our job. Engineering becomes coaching: guide the machine, shape output, but your thinking and judgment turn software into something worth shipping.
The author's personal thank you and invitation for dialogue. This book is a conversation starter, not the final word. Share your perspective, stories, and feedback on how AI is changing your work as an engineer, leader, or builder.