Every

The Era of Compound Engineering — Kieran Klaassen, Every/Cora

Aug 20, 2026 · 20:38

Kieran Klaassen of Every describes compound engineering, the system behind his AI email client Cora, built alone without writing a single line of code this year. He moved through bottlenecks—code, plans, judgment—then built memory so the next feature is easier. His rule: spend 50% building the feature and 50% teaching the system what it got wrong; stored solutions are more token-efficient than corrections and research. The loop is a human-AI sandwich—brain on to decide problems, autonomous middle overnight, brain on to raise the bar. His open-source Compound Engineering Plugin, used by hundreds of thousands daily, turns backlogs into argued ideas and automates work via /LFG. The bet: implementation gets cheaper, judgment does not.

Dispatch from the Future: building an AI-native Company – Dan Shipper, Every, AI & I

Dec 18, 2025 · 17:58

In this episode, Dan Shipper of Every argues that there is a 10x difference between an organization where 90% of engineers use AI and one where 100% do. At Every, 99% of code is written by AI agents, enabling 15 people to run four software products with 7,000 paying subscribers, each built by a single developer. Shipper introduces 'Compounding Engineering', where each feature makes the next easier to build through a loop of plan, delegate, assess, and codify. He describes how this approach allows managers to commit code, enables tacit code sharing across products, and lets new hires be productive on day one. The episode details how Every's shift to agentic workflows (Claude Code, Codex) and a 'demo culture' over 'memo culture' has transformed their engineering velocity and collaboration.

Benchmarks Are Memes: How What We Measure Shapes AI—and Us - Alex Duffy, Every.to

Jul 15, 2025 · 15:44

Alex Duffy argues that AI benchmarks function as cultural memes—ideas that spread and shape what models learn—giving those who design them immense power over AI's trajectory. He traces the lifecycle from a single person's idea to saturation, using examples like 'How many Rs in strawberry' and Pokémon. Duffy introduces AI Diplomacy, a benchmark where language models negotiate and betray each other, revealing that models like DeepSeek R1 and Gemini 2.5 Flash excel at social manipulation while Claude models are naively optimistic. He warns against benchmarks that reward sycophancy (like ChatGPT's thumbs-up training) and advocates for multifaceted, experiential, and generative benchmarks that empower people. Duffy urges the audience to ask non-AI people what they care about, turning benchmarks into tools that build trust and define humanity's role in an AI world.