Software engineering

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.

Research to Reality with Google DeepMind — Benoit Schillings, Google DeepMind, VP of Technology

Research to Reality with Google DeepMind — Benoit Schillings, Google DeepMind, VP of Technology

Benoit Schillings, VP of Technology at Google DeepMind, explores the evolution of AI's role in software development, highlighting the transition from human-limited coding to an AI frontier where syntax generation is solved. He delves into the power of self-play for model training, the shifting economics of software engineering, and the imperative for active guardrails. Schillings also discusses the need for inductive architecture, advanced model planning, multimodal reasoning (as seen in Gemini), and the potential for AI to drive scientific breakthroughs in fields like chemistry and biology by uncovering patterns imperceptible to human bias.

Simon Willison in conversation with Cat Wu & Thariq Shihipar, Anthropic

Simon Willison in conversation with Cat Wu & Thariq Shihipar, Anthropic

A Q&A with Anthropic's Cat Wu and Thariq Shihipar on how Claude Code and agentic AI are fundamentally changing software development, from workflow shifts and engineering norms to safety, model trust, and team collaboration. The discussion covers the rapid evolution of coding agents, the rise of proactive agents like Claude Tag, new approaches to code review and system prompt optimization, and Anthropic's robust safety measures including Auto Mode.