Are software engineers going to be commodities?
The coming of AI in software development
The fast-paced evolution of Artificial Intelligence (AI) tools in the software development arena has given rise to a contentious debate: are software engineers on the path to becoming mere commodities? AI-powered tools like GitHub Copilot, ChatGPT, and CodeWhisperer are becoming more and more composed; they are changing the way developers work. If we step back and look at it through the lens of a lot of engineers across FAANG (Facebook, Amazon, Apple, Netflix, Google) companies and beyond, many have a nagging feeling that these changes in the industry potentially altering the role of the traditional software engineer.
AI Tools: From Assistants to Code Creators
AI-assisted development tools have moved beyond autocomplete functions to writing production-level code. For example:
GitHub Copilot, powered by OpenAI’s Codex, generates substantial portions of code, making developers significantly more productive.
Tabnine and similar tools use AI to suggest contextually relevant code snippets, further reducing time spent on repetitive tasks.
Full-stack solutions like Builder.io’s AI are capable of designing and building frontends with minimal human intervention.
These advancements empower software engineers to focus more on architecture, business logic, and innovation while delegating repetitive tasks to AI. However, as these tools improve, the question arises: how much of a developer’s role can be automated?
The Data Behind the Shift
According to a 2023 McKinsey report, 45% of software development tasks can now be automated using existing technologies. Tasks like debugging, testing, and basic coding have become prime candidates for AI automation. Additionally, productivity studies reveal that teams using AI tools reduce development timelines by up to 30%.
Many FAANG employees echo similar sentiments in internal discussions. "AI is democratizing software development," said a senior engineer at Google. "It lowers the barrier to entry, which means the core skill set that differentiates top engineers is shrinking."
This trend is reflected in hiring patterns. Companies are beginning to prioritize problem-solving, product design, and systems thinking over mastery of specific programming languages or frameworks skills that AI can easily replicate.
The Commoditization Threat
A "commodity" in any industry is something widely available, interchangeable, and relatively low-cost. As AI tools standardize software engineering workflows, junior and mid-level engineers may find their roles diminished in value. Tasks like creating CRUD operations, writing boilerplate code, or building standard APIs once entry-level jobs are increasingly automated.
This is evident in the recent hiring slowdown in Big Tech. According to public data from LinkedIn and Glassdoor, demand for software engineers at FAANG has dropped by nearly 15% since 2022. While some of this is due to macroeconomic factors, the growing efficiency of AI tools cannot be ignored.
What Differentiates the Engineers of Tomorrow?
Despite these challenges, experts argue that software engineers are far from obsolete. Instead, the role is evolving. To remain competitive, engineers must adapt by focusing on areas where AI still falls short:
Problem-Solving & Creativity
AI excels at generating code but lacks the contextual understanding to solve complex, abstract problems. Engineers who can design creative solutions and deeply understand business requirements will remain invaluable.AI Tool Mastery
Familiarity with tools like Copilot or custom AI-driven frameworks will become a baseline skill. Engineers who can effectively integrate these tools into their workflows will have a significant edge.System Design & Architecture
High-level design decisions require a holistic view of systems and their interactions something AI cannot replicate. Engineers who excel in this domain will continue to lead teams and projects.Ethics & AI Governance
The growing role of AI raises ethical questions. Engineers equipped to navigate these issues, including biases in AI algorithms and data privacy, will become crucial in the age of AI-driven software.
The Bigger Picture
The commoditization of certain engineering tasks may not necessarily be negative. It could democratize access to technology, allowing smaller startups and non-technical teams to build software previously requiring specialized expertise. This could spur innovation across industries.
However, it also poses risks. As basic coding becomes easier, competition may drive down wages for entry-level roles, making it harder for new engineers to enter the field. To stay ahead, engineers must shift their focus to areas where human intuition and creativity remain irreplaceable.
AI tools are undeniably reshaping the landscape of software engineering. While some aspects of the role may become commoditized, the profession itself is not disappearing it is transforming. Engineers who embrace this change, continuously upskill, and focus on strategic, high-value work will thrive in the new era.
In the words of a senior Amazon engineer: "AI won’t replace software engineers. But engineers who use AI effectively will replace those who don’t."
The choice is clear: adapt or risk becoming obsolete in the fast-moving world of software engineering.