links

Author: lukegalbraithrussell

docs/english/concepts/message-sending.md

@@ -120,4 +120,4 @@ const feedbackBlock = {
 };
 ```
 
-Read more about streaming messages in the [_Using AI in Apps_](/tools/bolt-js/concepts/ai-apps) guide.
+Read more about streaming messages in the [_Adding agent features_](/tools/bolt-js/adding-agent-features) guide.

docs/english/building-an-app.md docs/english/creating-an-app.mddocs/english/building-an-app.md renamed to docs/english/creating-an-app.md

@@ -2,7 +2,7 @@
 sidebar_label: Building an App
 ---
 
-# Building an app with Bolt for JavaScript
+# Creating an app with Bolt for JavaScript
 
 This guide will walk you through creating and using a Slack app built with Bolt for JavaScript.
 

docs/english/tutorials/ai-assistant.md

@@ -155,7 +155,7 @@ export const openai = new OpenAI({
 });
 ```
 
-In the `listeners/assistant/index.js` file, we initialize the Bolt Assistant class. The Assistant class is a [Bolt feature](/tools/bolt-js/concepts/ai-apps) that simplifies handling incoming events related to the app assistant.
+In the `listeners/assistant/index.js` file, we initialize the Bolt Assistant class. The Assistant class is a [Bolt feature](/tools/bolt-js/concepts/using-the-assistant-class) that simplifies handling incoming events related to the app assistant.
 
 ```js
 import { Assistant } from '@slack/bolt';
@@ -490,7 +490,7 @@ This sample app uses Socket Mode to receive events. This is great for developing
 
 ### Learn more {#learn}
 
-➡️ Read more about Bolt support for apps using platform AI features in the documentation [here](/tools/bolt-js/concepts/ai-apps).
+➡️ Read more about Bolt support for apps using platform AI features in the documentation [here](/tools/bolt-js/concepts/adding-agent-features).
 
 ➡️ Level up your AI game after reading through the [usage guide](/ai/developing-ai-apps) and [Best practices for AI feature-enabled apps](/ai/ai-apps-best-practices).
 

docs/english/tutorials/code-assistant.md

@@ -376,7 +376,7 @@ This is the meat of our app! Here's a breakdown of what we've added:
 
 * `DEFAULT_SYSTEM_CONTENT` is a set of instructions for the model. Think of it as setting the scene in the play that is the interaction between your users and the AI model; it is the context for the role that the model will be playing.
 * `convertMarkdownToSlack` is a function that converts traditional markdown to the markdown that Slack uses (which is different). Alternatively, you could send the model's response through the [markdown block](/reference/block-kit/blocks/markdown-block) to achieve the same result.
-* `assistant` is an instance of the [`Assistant` class](/tools/bolt-js/concepts/ai-apps#the-assistant-class-instance); this sets up the suggested prompts that the user sees in the split-view container upon opening your app.
+* `assistant` is an instance of the [`Assistant` class](/tools/bolt-js/concepts/using-the-assistant-class); this sets up the suggested prompts that the user sees in the split-view container upon opening your app.
 * `userMessage` is the handler that takes care of the fiddly bits around getting the thread history, preparing the structure of the messages for processing in a way that the model is expecting, interacting with the model, and responding to the user.
 * `app.function` sets up the custom function that can be used to achieve the same result of `userMessage` but as a custom step in a workflow built in Workflow Builder 🎉 This is the implementation logic of the custom workflow step we saw created by the manifest in the app settings. We use the [`conversations.history`](/reference/methods/conversations.history) method to find the message where the emoji reaction was placed, then send that to the model as the question.