{
  "id": 9454245,
  "title": "Harness Engineering: the 5 layers of the agent - memory, context, skills, agents and tools",
  "url": "https://urgent.news/2026/09/24/harness-engineering-as-5-camadas-do-agent-memory-context-skills",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-24T00:37:34.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/tiagovilasboas/harness-engineering-as-5-camadas-do-agent-memory-context-skills-agents-e-tools-2oog"
  },
  "original_language": "pt",
  "account": "The article discusses the concept of a \"harness\" in artificial intelligence, which refers to the infrastructure that supports an AI model, enabling it to operate effectively. A harness is not just a chat interface, but a complete environment that allows the model to read files, execute commands, and decide the next step. The article highlights the differences between a harness and a simple chat interface, using examples such as Cursor, Kiro, and Claude Code. It also outlines a five-layer framework for building a harness, consisting of memory, context, skills, agents, and tools, and explains the importance of each layer in enabling the AI model to operate efficiently.",
  "summary": "Imagina um piloto de Fórmula 1 sentado num banco de praça. Ele sabe pilotar. Mas sem o carro, sem o volante, sem a experiência, sem o box ele não corre. O modelo de IA é o piloto. O harness é o carro inteiro. Cursor, Kiro, Claude Code, Windsurf, Cline. Essas não são \"IDEs com chat\". São harnesses — ambientes completos onde o modelo opera em loop, lê arquivos, executa comandos, e decide o próximo…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}