Three production failures, a shared root cause, and a framing that most agentic engineering discussions skip entirely. A support agent that handles an escalated customer correctly — except the escalation happened two hours ago and the CRM hasn't synced yet, so the agent is acting on the pre-escalation record.

Code review bottlenecks are not a new problem, but the Linux kernel's memory management subsystem offers an unusually rigorous window into how bad they get at scale. A decade-long study of kernel patch reviews finds that submission rates have structurally outpaced the capacity of the small group of

Google DeepMind's AntiGravity — their VS Code fork built for agentic coding — ships a three-primitive system for programmable agent behavior that most teams are currently cobbling together from scattered documentation and system prompts. The `.agent/` folder exposes Rules (what the agent must always follow, or can decide to apply

Vibe coding unlocked the ability for anyone to build a working web app from natural language. It quietly created a harder second-order problem: if an agent builds the app autonomously, how do you automatically verify it works correctly? Static visual checks fail because vibe-coded apps vary too widely in structure.

Mobile development has always been a harder target for coding agents than web or general-purpose library work — and now there's benchmark data to prove it. MobileDev-Bench is the first production-grade evaluation covering all three major mobile stacks: Android Native (Java/Kotlin), React Native (TypeScript), and Flutter (Dart). Its

A new paper from arXiv gives engineering teams a rare thing: a production-validated blueprint for self-improving software that has actually shipped. The Kitchen Loop is a four-primitive framework tested across two live systems over 285 iterations, producing more than 1,094 merged pull requests with zero regressions detected by the