Most enterprises have bought an AI coding agent and are stuck. The ones generating real productivity gains didn’t win by picking a better model. They built a platform around the agent. This post walks through the five control-plane responsibilities that separate the 11% of AI-native orgs from the 95% reporting zero ROI, grounded in public deployments from Block, Shopify, Atlassian, Airbnb, and others.
An interactive technical breakdown of Claude Code’s architecture — from the query loop and five compaction mechanisms to the permission pipeline and feature flags. Based on source code analysis of ~1,884 TypeScript files.
Production AI agents face infrastructure problems that framework-level code cannot solve: state loss on crashes, LLM API flakiness, debugging non-deterministic behavior, and coordinating human approvals across hours-long runs. This post walks through Temporal’s durable execution model and why companies like OpenAI chose it for their agent infrastructure.
An interactive visual exploration of OpenClaw — the open-source AI agent that broke GitHub. Explore its three-layer architecture, two key primitives, memory system, and composable system prompt.
A deep dive into the architecture, design patterns, and engineering decisions behind production-grade agentic code assist solutions. By dissecting OpenHands, we uncover how to build AI agents that safely execute code, manage complex state, and operate reliably in production.