AI for developmentInfoQ
AI for development
Drawing from the enduring adaptability of HTML and HTTP, Seph Gentle proposes embedding self-contained schemas directly into file headers, ensuring data remains readable without external definitions. His experimental format prioritises…
AI makes the first 80% of development feel fast, but hides architectural complexity until it's too late. To prevent system instability, engineering leaders must shift from raw throughput to systemic comprehension. By unifying spec-anchored…
Kubernetes has quietly become the default platform for AI and machine learning. Whether you run notebook servers for data scientists, schedule distributed training jobs, tune hyperparameters, or orchestrate multi-step ML pipelines, those…
DoorDash details the architecture behind Ask DoorDash, its AI-powered conversational shopping assistant, combining LLMs, specialized AI agents, MCP-based tooling, and an intelligence layer with persistent consumer memory and live backend…