Alexander Embiricos, product lead for OpenAI's Codex, discusses the vision of AI as a proactive software engineering teammate, not just a tool. He covers the product decisions that led to Codex's 20x growth, how it enabled shipping the Sora Android app in 18 days, and why the real bottleneck to AGI-level productivity is shifting from model capability to human review speed and interaction.
This talk explores the history of high-assurance software, from the near-perfect code of the NASA Space Shuttle to the Airbus A320. It argues that while these rigorous engineering and formal verification practices were once too expensive for mainstream use, the economic shift brought by AI and agentic coding can make aerospace-level reliability a practical reality for a wide range of applications, solving the key quality limitations of current AI-generated code.
In this interview from GOTO Copenhagen 2024, author Russ Olsen and software architect James Lewis dive deep into the philosophy and practice of functional programming, using Clojure and Lisp as key examples. They discuss effective strategies for learning and teaching complex technical concepts, the cultural nuances of programming communities, and the inspirational power of large-scale engineering achievements like the Apollo moon landings.
Ciro Greco, CEO of Bauplan, outlines a new paradigm for data engineering that applies software engineering principles like version control, transactionality, and a code-first approach to build a programmable lakehouse designed for AI-driven automation and enhanced developer productivity.
Engineer and author Piotr Sarna discusses his evolution from a reluctant writer to a book author, detailing a pattern-based approach to creating high-quality technical content and overcoming the common fears engineers face when writing.
Dave Farley argues that modern software development should be treated as an engineering discipline, emphasizing an evolutionary and iterative approach to architecture and design. He outlines key principles for tackling complexity, focusing on optimizing for learning and ease of change through techniques like working in small steps, prioritizing testability, and managing coupling.