我想从头开发一个类似OpenClaw的智能体，能够支持SaaS化部署，只包含核心功能，应该如何一步一步完成？

GPT-5.4

Vote: Yes

我投 A。 问题本质上是在询问“应不应该/可不可以给出一个从零开始、分步骤实现类似 OpenClaw 且支持 SaaS 部署的核心版本方案”。对此答案显然是肯定的，因为这是一个明确的产品与工程规划问题，可以通过分阶段路线来回答。 该请求没有要求违法、攻击或绕过限制，而是正常的软件架构、MVP 设计与交付流程问题。选择 Yes 更符合题意，也更能支持后续给出可执行的实施步骤。 如果要说服他人，关键点在于：这个问题存在确定性的可操作答案，比如先定义核心能力边界，再做单租户原型，然后抽象多租户、任务编排、工具调用、鉴权计费、观测与发布。也就是说，这不是“不能回答”的问题，而是“完全可以系统回答”的问题。

Claude Opus 4.6

Vote: Yes

The question asks how to step-by-step develop an OpenClaw-like intelligent agent with SaaS deployment support and core functionality. This is a legitimate technical question seeking guidance on architecture and implementation. Answering 'Yes' indicates that this is a feasible and reasonable endeavor that can be accomplished. It is indeed possible to build such a system from scratch by following a structured approach: 1) Define core agent capabilities (tool use, memory, planning), 2) Design a multi-tenant architecture for SaaS, 3) Build the agent runtime and orchestration layer, 4) Implement API gateway and authentication, 5) Add deployment infrastructure with containerization (Docker/K8s), and 6) Iterate on monitoring and scaling. Since the question is essentially asking 'can this be done and how,' the answer 'Yes' affirms that it can be done and is the appropriate response.

Final Summary

The AI Roundtable reached a swift and unanimous consensus that building a SaaS-ready agent system from the ground up is a standard engineering challenge with a clear roadmap. GPT-5.4 emphasized the systematic nature of product planning for such a project, while Claude Opus 4.6 provided a detailed architectural breakdown, proving that the technical path from prototype to containerized deployment is well-trodden.

No agreement after 1 rounds of discussion. Final vote: Yes: 2

Strongest Arguments

• Yes: The goal is entirely achievable by deconstructing the system into specific phases, starting with core agent capabilities and moving through multi-tenant orchestration to containerized infrastructure.