Renaming AI Persona -> AI Agent

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Exec summary: the term AI Persona is becoming a liability - we would like to align with the industry and rename to AI Agent

The term “AI Persona” was adopted by me in Discourse back in November 2023.

In AI terms, it feels like decades ago.

Over the past year and a half, a new trend has emerged in the AI space.

The words “agentic” and “AI Agents” are now used ubiquitously to describe AIs that act on our behalf (more technically, LLM Loop + Tools).

Discourse has supported AI agents since 2023; the key concept of calling an LLM → calling tools → calling an LLM and so on was baked into Discourse AI back then.

This year, we have made strides to centralize all of our AI LLM uses to funnel through personas. Our goal is to have one flexible primitive for working with any LLM and integrating into Discourse and third parties via tools.

By centralizing the logic, we also allow better flexibility for admins, since they can customize any persona.

Back on track.

The term “persona” has now become unique (in a bad way) and confusing in the ecosystem. Explaining to new Discourse admins that it supports agents is something that conveys the story in one sentence. Telling them we have “personas” creates a whole new conversation — which reaches the final point of “oh, you mean Discourse supports AI agents?”

Given that the industry has now decided on the term that is meant to be used, I think it would be healthy for Discourse to rename the primitive. It is a big change, and a lot of code and documentation will need to be amended to make it happen.

I am curious to know what various users of Discourse AI think about the rename and would like to take feedback.

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An AI persona has very bad sound. And at same time when common atmosphere is turning more negative against AI use, because of various reasons, calling AI as a person will turn against Discourse at some point.

Outside this bubble I’ve used term a model, even that is different thing. But an agent is good. And more commonly used than a persona, I reckon.

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The first question that comes to mind is whether there’s truly just one entity that needs naming. In my daily work with these systems, I use several distinct and related terms:

  • tool
  • client
  • server
  • host
  • ChatBot
  • MCP
  • connection
  • system prompt
  • user prompt

While I frequently encounter the words agent or agentic in documentation, I tend to avoid them in practice. Many users have conflicting interpretations of what these terms mean, which often creates more confusion than clarity.

See: The definition of agent is interpreted differently by different people - Community - OpenAI Developer Community

Given the complexity often encountered with learning code architectures, I’ve found it helpful to ask LLMs like Claude to create wireframe diagrams in SVG format, often linking to relevant GitHub repositories. This approach could be particularly valuable for the multiple components mentioned in your original post.

Your mention of LLM Loop + Tools brings to mind Host with MCP Client + MCP Servers, illustrated here:

A diagram illustrating a computer with an MCP client, three servers (A, B, and C), and two local data sources (A and B) with Server C connected to a remote service over the internet via web APIs and MCP protocols. (Captioned by AI)
A diagram illustrating a computer with an MCP client, three servers (A, B, and C), and two local data sources (A and B) with Server C connected to a remote service over the internet via web APIs and MCP protocols. (Captioned by AI)860×577 19.4 KB

Please correct or expand on LLM Loop + Tools as needed if my analogy is flawed, as this seems central to identifying which specific entities need renaming.

The pace and breadth of Discourse’s AI integration work has been remarkable. The entire team should be proud of these accomplishments. :clap:

Took a closer look at

As odd as this may sound, using configuration in place of persona works better for me. :man_shrugging:

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