Original Summary

when we built our original product (customer agent for that sits on a website and inside of applications), we realized that building proactive and "always on" AI functionality was hard to get right. you have to: construct an agent runtime or use an OSS one manage infra, retries, cost and human in the loop run for each customer with the right permissions and allowances understand how much value you're delivering and how to charge for it the last point is important because before AI, it made sense to just charge a fixed amount for access to features. the human was still doing the work. as we ship our MCPs, APIs, CLIs, etc., it is becoming clear that some customers will use their own agents on top of our primitives. it is also becoming clear that customers want outcomes. once they get agent drive outcomes, the tolerance for DIY drops. we launched a product ( agentic services ) that lets customers deliver the same sort of AI outcomes they are getting in our product, to their own customers. it runs on top of their own product MCP/endpoints. they define a catalog of services, the cost, the pricing and can collect payments directly through us. one thing we didn't expect is that we're delivering more value to our customers than they can reasonably get on their own through our API/MCP + their Claude or ChatGPT. and their agents can access our agentic services anyway via our service catalog. are you guys running into anything similar?   submitted by   /u/aimdoc-ai [link]   [comments]

  • 情报分类：开源项目与落地
  • 分类依据：内容涉及项目实践、创业、副业或变现
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/19 02:26:54