AI isn't eliminating software engineering but fundamentally changing it. Demand for traditional programming is declining, while demand for "AI native" engineers—who manage entire systems from prompt to deployment using agentic tools—has grown 143%. The role is shifting from writing code to orchestrating AI systems at a higher abstraction level.

Contrary to fears of job displacement, Todd McKinnon believes AI will increase the demand for software engineers. While AI will handle more initial code generation, humans will be needed to manage the complexity of maintaining, scaling, and architecting the 10x more software that will be built with these new agentic systems.

As AI handles low-level coding, Barbara Liskov suggests the crucial human skill will be working at a higher level of abstraction. The future engineer's role will involve design, modularity, and verification to ensure the systems AI builds are correct, safe, and meet specifications, rather than focusing on implementation minutiae.

AI lowers the economic bar for building software, increasing the total market for development. Companies will need more high-leverage engineers to compete, creating a schism between those who adopt AI tools and those who fall behind and become obsolete.

The role of a software engineer is evolving from a detail-oriented coder into a conceptual manager who directs a "team of AI agents." This shift prioritizes judgment and problem selection over granular coding expertise, rendering deep technical skills acquired just a few years ago, such as systems programming, potentially obsolete.

The idea that AI makes engineering obsolete is wrong. Just as cloud computing created "leaky abstractions" that still required knowledge of networking, AI tools require engineers to understand underlying models and systems to be effective. The best AI-assisted engineers will be those with strong fundamental knowledge.

AI coding tools democratize development, making simple 'coding' obsolete. However, this expands the amount of software created, which in turn increases the need for sophisticated 'engineering' to manage new layers of complexity and operations. The field gets bigger, not smaller.

Experience alone no longer determines engineering productivity. An engineer's value is now a function of their experience plus their fluency with AI tools. Experienced coders who haven't adapted are now less valuable than AI-native recent graduates, who are in high demand.

AI is automating the task of writing code, leading to a decline in "programming" jobs. Simultaneously, demand for "software engineering" roles, which involve higher-level system design and managing AI tools, is growing. This signals a fundamental reskilling shift from pure coding to architectural oversight.