{"@":{"v":"gdom/1.2","profile":"https://dng.ai/gibberdom/gdom-1.2.json","proj":"text","index":"https://dng.ai/_gdom/manifest.json","site":"https://dng.ai/_gdom/site.gdom","self":"https://dng.ai/_gdom/platform/agents/index.text.gdom"},"text":"# Agents that reason, act, and collaborate.\n\nThe AI Agent node is a true reasoning runtime. Multi-agent teams share memory, debate, and ship — model-agnostic, tool-equipped, and MCP-ready.\n\n## What agents take off your plate.\n\n### Reasoning runtime\n\nAgents plan, call tools, and adapt — not single-shot prompts.\n\n### Multi-agent teams\n\nSpecialized roles share memory and hand off work.\n\n### MCP-ready\n\nConnect any MCP server to give agents new tools in minutes.\n\n### Model-agnostic\n\nPick the best model per task; swap without re-platforming.\n\n### Tool use\n\nWeb, CMS, CRM, warehouse — agents act on real systems.\n\n### Memory\n\nGrounded in your knowledge base, brand voice, and past work.\n\n## A reasoning runtime, not a prompt box.\n\nGive the agent a goal and it plans the steps, calls tools, observes the results, and adapts until it's done — bounded by the tool-call limit and instructions you set.\n\n## Tools, datasources, and MCP — wired in.\n\nEquip an agent with exactly the abilities a task needs. It calls them on its own as it reasons.\n\n## Pick the right brain for each agent.\n\nChoose a reasoning-capable model per node — GPT-4, Claude Sonnet/Opus, or Gemini Pro — and tune temperature, top-K, top-P, and max tokens. Swap models without re-platforming.\n\n## How an agent comes together.\n\n### Define the goal\n\nDrop an AI Agent node into Studio, write the system prompt, and set the tool-call limit — no code required.\n\n### Attach capabilities\n\nEquip the agent with tools, MCP servers, and RAG datasources so it can act on real systems.\n\n### Run and observe\n\nFire the workflow — watch the agent plan, call tools, and adapt step by step in the execution log.\n\n### Review and refine\n\nInspect every reasoning step and tool call, tune the prompt or tools, and iterate until it ships reliably.\n\n## What teams ask before they commit.\n\nIn Draft & Goal, an AI agent is a reasoning runtime, not a single-shot prompt. You give it a goal and it plans the steps, calls tools, observes the results, and adapts until the task is done — bounded by the tool-call limit and the instructions you set.\n\nDraft & Goal is model-agnostic. You pick a reasoning-capable model for each agent node — GPT-4, Claude Sonnet or Opus, or Gemini Pro — and tune temperature, top-K, top-P, and max tokens. Because the choice is made per node, teams can swap models without re-platforming their workflows.\n\nA multi-agent team is a group of specialized agents that share memory and hand off work to each other — for example a researcher, a writer, and a reviewer collaborating on one deliverable. Draft & Goal coordinates these roles so each agent handles the part of the process it is built for.\n\nYou equip each agent with exactly the capabilities its task needs: web search, a web scraper, API connectors, RAG datasources, MCP servers, and structured JSON output. The agent calls them on its own as it reasons, acting on real systems such as your CMS, CRM, or data warehouse.\n\nNo. You drop an AI Agent node into Studio, write the system prompt, and set the tool-call limit — no code required. You can then attach tools, MCP servers, and RAG datasources, run the workflow, and inspect every reasoning step and tool call in the execution log.\n\nShow us the workflow.We'll show you the 10x.\n\nBring the marketing workflow that eats your week. We'll build it live, with your data and your models, in 30 minutes.\n\n## Outbound links\n\n- [Book a demo →](https://dng.ai/book-demo/)\n\n- [Tour the platform](https://dng.ai/platform/)\n\n- [Draft & Goal](https://dng.ai/)\n\n- [Read the docs](https://docs.dng.ai/)\n\nSite navigation: https://dng.ai/_gdom/site.gdom\n\nFull page index: https://dng.ai/_gdom/manifest.json","links":[{"rel":"internal","href":"https://dng.ai/book-demo/","path":"/book-demo","label":"Book a demo →","gdom":"/_gdom/book-demo/index.text.gdom"},{"rel":"internal","href":"https://dng.ai/platform/","path":"/platform","label":"Tour the platform","gdom":"/_gdom/platform/index.text.gdom"},{"rel":"internal","href":"https://dng.ai/","path":"/","label":"Draft & Goal","gdom":"/_gdom/index.text.gdom"},{"rel":"external","href":"https://docs.dng.ai/","label":"Read the docs"}]}