docs: remove subagents from experimental (#4907)

2025-09-30 19:32:48 -07:00
parent f2bf927011
commit 937c75bc51
31 changed files with 42 additions and 55 deletions
@@ -36,7 +36,7 @@ I decided to create a digital resource that teaches foundational concepts like A

 ## Meet the Subagents

-[Subagents](/docs/experimental/subagents) are individual AI instances that take on specific tasks. Each one runs in its own session, which helps preserve the main context window and keeps your primary Goose conversation uncluttered and focused on high-level orchestration. I think of subagents as temporary teammates. Goose assigns each subagent a job and deallocates it when the work is complete.
+[Subagents](/docs/guides/subagents) are individual AI instances that take on specific tasks. Each one runs in its own session, which helps preserve the main context window and keeps your primary Goose conversation uncluttered and focused on high-level orchestration. I think of subagents as temporary teammates. Goose assigns each subagent a job and deallocates it when the work is complete.

 For this project, I turned my subagents into an on-demand dev squad, and I assigned them the following roles:

@@ -58,7 +58,7 @@ export GOOSE_ALPHA_FEATURES=true

 ## Instructing My Team

-There are a few ways to create subagents in Goose. You can use natural language prompts, define them through [recipes](/docs/guides/recipes/), or even spin up [external subagents](/docs/experimental/subagents/#external-subagents) like Codex or Claude Code.
+There are a few ways to create subagents in Goose. You can use natural language prompts, define them through [recipes](/docs/guides/recipes/), or even spin up [external subagents](/docs/guides/subagents/#external-subagents) like Codex or Claude Code.

 I took the natural language prompt approach because it felt convenient to directly configure a subagent through one prompt. Here’s the prompt I used:
  
@@ -173,7 +173,7 @@ What will you build with subagents?

 [Download Goose](/)

-[Learn about subagents](/docs/experimental/subagents)
+[Learn about subagents](/docs/guides/subagents)

 <head>
  <meta property="og:title" content="Orchestrating 6 Subagents to Build a Collaborative API Playground for Kids" />
@@ -406,7 +406,7 @@ Angie's Diner shows exceptional performance with premium order values and strong
 </details>


-What a fun experiment! This gave me a better understanding of how agent-to-agent and [subagent](/docs/experimental/subagents) workflows may work behind the scenes. Makes you wonder, what else could happen when AIs start talking to each other without us?
+What a fun experiment! This gave me a better understanding of how agent-to-agent and [subagent](/docs/guides/subagents) workflows may work behind the scenes. Makes you wonder, what else could happen when AIs start talking to each other without us?

 ---

@@ -21,7 +21,7 @@ Every week, the PulseMCP team faced the same time-consuming workflow: sourcing r

 ## The Solution: Why Sequential Beats Monolithic

-Instead of building one massive "do-everything" agent (which inevitably fails on complex tasks), PulseMCP broke their workflow into six distinct phases. Each phase gets handled by focused [recipes](/docs/guides/recipes/session-recipes), [subrecipes](/docs/guides/recipes/subrecipes) and [subagents](/docs/experimental/subagents) with clear inputs, outputs, and a single job.
+Instead of building one massive "do-everything" agent (which inevitably fails on complex tasks), PulseMCP broke their workflow into six distinct phases. Each phase gets handled by focused [recipes](/docs/guides/recipes/session-recipes), [subrecipes](/docs/guides/recipes/subrecipes) and [subagents](/docs/guides/subagents) with clear inputs, outputs, and a single job.

 This approach has three main benefits: debugging becomes easier when agents have single responsibilities, results become more predictable with clear handoffs between stages, and humans stay in control of the editorial process while automating the tedious work.

@@ -36,7 +36,7 @@ Think lone developer grinding through the ticket.

 ## The Subagent Setup: Orchestrator With a Crew

-With [subagents](/docs/experimental/subagents), you still have one "main" agent, but instead of doing everything, it plays tech lead and delegates pieces of the work to other specialized agents.
+With [subagents](/docs/guides/subagents), you still have one "main" agent, but instead of doing everything, it plays tech lead and delegates pieces of the work to other specialized agents.

 The main agent says:

@@ -81,7 +81,7 @@ The [Memory extension](https://block.github.io/goose/docs/mcp/memory-mcp) stores

 **5. Subagents**

-[Subagents](https://block.github.io/goose/docs/experimental/subagents) handle specific tasks in their own isolated sessions. This prevents your main conversation from getting cluttered with implementation details and tool outputs. You delegate work to subagents and only see the final results, keeping your primary context window clean and focused.
+[Subagents](https://block.github.io/goose/docs/guides/subagents) handle specific tasks in their own isolated sessions. This prevents your main conversation from getting cluttered with implementation details and tool outputs. You delegate work to subagents and only see the final results, keeping your primary context window clean and focused.

 **6. Short sessions**

@@ -7,7 +7,7 @@ authors:

 ![Subagents vs Subrecipes](subrecipes-vs-subagents.png)

-When you're working on complex projects with goose, you'll often need to break work into multiple tasks and run them with AI agents. Goose gives you two powerful ways to do this: [subagents](/docs/experimental/subagents/) and [subrecipes](/docs/tutorials/subrecipes-in-parallel/). Both can run multiple AI instances in parallel, but they work  differently. Picking which one to use can be confusing, so we're going to guide you to a decision.
+When you're working on complex projects with goose, you'll often need to break work into multiple tasks and run them with AI agents. Goose gives you two powerful ways to do this: [subagents](/docs/guides/subagents/) and [subrecipes](/docs/tutorials/subrecipes-in-parallel/). Both can run multiple AI instances in parallel, but they work  differently. Picking which one to use can be confusing, so we're going to guide you to a decision.

 I've been using both approaches, and the choice between them depends on what you're trying to accomplish. Let me break down when to use each method and show you real examples.