Developer productivity

How METR measures Long Tasks and Experienced Open Source Dev Productivity - Joel Becker, METR

How METR measures Long Tasks and Experienced Open Source Dev Productivity - Joel Becker, METR

AI models show remarkable progress on benchmarks, yet a field study with experienced developers revealed no productivity gains. This summary explores the disconnect between lab results and real-world impact, examining the causal relationship between compute and AI capabilities, the nuances of the developer productivity study, and future directions for measuring what AI can truly do.

Coding with AI // Chip Huyen

Coding with AI // Chip Huyen

Chip Huyen provides a deep dive into the evolving landscape of AI-powered coding. The talk covers the different interfaces for AI coding tools, introduces new metrics like "interruption rate" to measure productivity, and outlines a framework for the levels of coding automation. Huyen argues that the engineer's role is shifting from writing code to architecting systems and reviewing AI-generated output, emphasizing the rise of spec-driven development and the critical importance of system thinking.

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Alexander Embiricos, product lead for OpenAI's Codex, discusses the vision of AI as a proactive software engineering teammate, the product decisions that led to its explosive 20x growth, and why the real bottleneck to AGI-level productivity is shifting from model capability to human review speed.

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

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.

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Why humans are AI's biggest bottleneck (and what's coming in 2026) | Alexander Embiricos (OpenAI)

Alexander Embiricos, product lead for OpenAI's Codex, shares the vision of AI as a software engineering teammate, not just a tool. He explains how a strategic shift to a local, interactive experience unlocked 20x growth, details how the Sora Android app was built in 28 days, and argues that the real bottleneck to AGI-level productivity is now human review speed, not model capability.

2026: The Year The IDE Died — Steve Yegge & Gene Kim, Authors, Vibe Coding

2026: The Year The IDE Died — Steve Yegge & Gene Kim, Authors, Vibe Coding

Steve Yegge and Gene Kim discuss the current limitations of AI coding assistants, predicting a shift from simple code completion "power tools" to sophisticated, agent-based "CNC machines" that will automate the entire software development lifecycle. They explore the cultural resistance from senior engineers, the transformative impact on team structures, and the emergence of "Vibe Coding" as a new paradigm that will reshape technology organizations.