# Range Let Planners Write the Agents Themselves

_Range let financial planners, not engineers, write 24 AI skills with a five-step method that keeps human review before any client sees advice._

**Published:** 2026-10-15
**Source:** https://www.startuphub.ai/ai-news/artificial-intelligence/2026/range-let-planners-write-the-agents-themselves

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Matthew Ragone said [Range](https://www.youtube.com/watch?v=gpmze-6ueGU) let its financial planners write the agents they use every day, and none of them write code, speaking to [AI Engineer](https://www.youtube.com/watch?v=gpmze-6ueGU).

Ragone is a certified financial planner who leads AI adoption for the planning team at Range, an all-in-one wealth management firm.

The team started with AI as a chatbot for polishing client messages, then shifted to agents that draft work while planners are elsewhere. Ragone said the guardrail is absolute: "The agent doesn't send anything. A planner reviews every single recommendation before a client sees it."

Two things had to be true for that to work, Ragone said. The agent had to work where the work lives, not in a separate chat window, and it had to know how Range does the work, not just generic planning.

He laid out five steps his team uses to turn that into a repeatable skill: pick, teach, pack, test, and ship. Pick a frequent, judgeable workflow like cash flow or insurance reviews. Teach it with several real cases and narrate judgment out loud. Pack it as a skill that asks questions before it starts and respects limits like never emailing a client. Test it five to 10 times on real cases, then ship it with an owner and a separate reviewer who keeps it current as processes and tax rules change.

Six months in, Ragone said Range has 24 skills and 17 of them are in planning, and the practice spread to sales, product and marketing without a mandate. That spread mirrors wider adoption patterns, where organizations deploy AI agents across a range of types and tasks and implement them with frameworks such as LangChain and Llama Stack or bring-your-own Python, according to [NVIDIA](https://www.startuphub.ai/ai-news/ai-stocks-daily/2026/ai-stocks-2026-08-24). The bottleneck now is not whether a model can draft an analysis, Ragone argued, but who writes down the firm’s method, who tests it and who owns it when 15 other people depend on it.

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Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory.

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