World's Fair 2026
\"Software engineering is not about writing code\" — Benoit Schillings, Google DeepMind VP of Research
Overview
This talk argues that the core challenge in software engineering is shifting from writing code to managing complexity, designing systems, and ensuring correctness. While AI models now excel at generating code syntax, the future of software development lies in leveraging AI for higher-level tasks like architectural design, complex problem decomposition, and inductive reasoning. The economics of code production are changing, making code generation nearly free and emphasizing the need for new processes and evaluation methods.
Who should watch
- AI Engineers exploring the evolution of coding agents and their impact on development workflows.
- Product Managers and Builders interested in the future of software development and the role of AI in product creation.
- Developers facing challenges with large, complex codebases and seeking new approaches to software engineering.
- Researchers investigating the frontiers of AI capabilities in code generation, reasoning, and problem-solving.
Key takeaways
- The era of optimizing machine performance through manual coding is over; the limiting factor has become human cognitive capacity for modular design.
- AI models now achieve superhuman syntax generation, making the act of writing code itself no longer the primary bottleneck.
- Future software engineering will focus on managing extreme complexity, architectural design, security, and ensuring code correctness from the start.
- The economics of code are changing, with generation becoming nearly free, leading to an explosion in code production and a need for new paradigms.
- Evaluation methods must evolve beyond simple code execution to encompass open-ended problems that drive novel algorithmic discovery.
- AI's ability to process vast amounts of data and perform self-play is key to advancing capabilities in complex code generation and problem-solving.
- Human roles will shift towards architecture, inductive thinking, and understanding the broader implications of AI-generated code.
- The rapid experimentation enabled by AI in code is poised to accelerate breakthroughs in domains like chemistry and biology.
Notable quotes
*Software engineering is not about writing code. Software engineering is the first time you join a company and you realize that there are 35 million lines of PHP in the codebase and that you need to make some changes.*
*The minutia of code writing I mean you can fight you can argue you can find counter example but that time is is gone.*
*We're now in a world where writing code is free or nearly free.*
Unofficial community note. Prefer the recording for nuance.