Software engineering

OpenAI’s Plan to Make ChatGPT the Everything App — Akshay Nathan, OpenAI

OpenAI’s Plan to Make ChatGPT the Everything App — Akshay Nathan, OpenAI

Akshay Nathan, head of Core Product Engineering at OpenAI, discusses the journey and rationale behind ChatGPT Work. He explains how Codex's unexpected adoption by non-developers led to a unified agent harness, blurring the lines between developer and knowledge worker tools. The conversation delves into model capabilities, the role of artifacts and interactive 'Sites' in replacing traditional documents, and how AI fosters a new era of 'T-shaped' generalists. Nathan emphasizes the shift in productivity bottlenecks to 'ideas and taste' and the importance of 'quality at-bats' over mere 'motion' in an AI-powered development landscape.

DeepSWE: A Contamination-Resistant Coding Benchmark — James Shi, Datacurve

DeepSWE: A Contamination-Resistant Coding Benchmark — James Shi, Datacurve

DeepSWE is a novel benchmark for evaluating AI models on software engineering tasks. It features 113 original, long-horizon problems from real open-source repositories, designed to resist contamination and provide clearer differentiation between models. The benchmark highlights unique failure modes and strengths of models like Claude and GPT, emphasizes realistic prompt design, and uses program-based verifiers focusing on observable behavior.

Loop Engineering from First Principles — Kyle Mistele, HumanLayer

Loop Engineering from First Principles — Kyle Mistele, HumanLayer

Kyle Mistele, in this presentation, argues that fixing the problem of unreviewable 40,000-line pull requests generated by coding agents doesn't lie in better prompts but in better, control theory-inspired loops. He details how to build agentic control loops with distinct sensors, controllers, and actuators, ensuring incremental, verifiable code changes. Using a practical example of RPC API migration, he demonstrates how to implement these loops with tools like ASGrep, integrate them into CI/CD, enable human feedback, and manage workflow to prevent overwhelming reviewers, ultimately leading to more robust and readable agent-generated code.

WebAssembly on Kubernetes • Nicolas Frankel • YOW! 2025

WebAssembly on Kubernetes • Nicolas Frankel • YOW! 2025

Nicolas Fränkel explores the evolution of WebAssembly (Wasm) beyond its web origins, showcasing its potential to revolutionize application deployment on Kubernetes. The talk demonstrates how Wasm enables incredibly small container sizes (down to 2MB for an HTTP server) by integrating specific Wasm runtimes with Kubernetes' extensible architecture. However, Fränkel also provides a candid assessment of the ecosystem's rapid, often unstable, development, recommending Wasm on Kubernetes for agile startups seeking competitive advantage but cautioning traditional enterprises due to the inherent risks and maintenance challenges.

6 Ways to Enhance Developer Productivity with AI

6 Ways to Enhance Developer Productivity with AI

Discover how top-performing teams achieve 100-150% productivity gains with AI by strategically restructuring workflows, automating wisely, prioritizing design, fostering deep work, reducing cognitive load, investing in growth, and optimizing tools. This goes beyond mere AI adoption, focusing on human-centric practices and intelligent measurement to drive real impact and retention.

From Blind Spots to Merged PRs: Continuous Agentic Performance Optimization - May Walter, Hud

From Blind Spots to Merged PRs: Continuous Agentic Performance Optimization - May Walter, Hud

May Walter, CTO of Hud, details a real-world case study on integrating AI agents into the SDLC for continuous performance optimization. The talk covers Hud's runtime intelligence layer, which uses production context to identify and fix high-ROI performance issues like N+1 queries and missing database indexes. It highlights the technical approach, challenges, and the development of a human-friendly reporting system that delivers measurable P90 latency improvements, enabling proactive optimization in mature codebases.