PostHog · cleo-pleurodon · Jul 21, 2026 · Jul 22, 2026 · Jul 22, 2026 · Jul 22, 2026
diff --git a/contents/blog/self-driving-product.mdx b/contents/blog/self-driving-product.mdx
@@ -16,6 +16,10 @@ tags:
   - PostHog news
 ---
 
+<div className="dark:bg-dark bg-accent border border-input p-4 rounded">
+    <p className="!mt-0 !mb-0"><strong>Update:</strong> PostHog Code is now <a href="/desktop">PostHog Desktop</a> – it does a lot more than just write code these days. This post still uses the old name, since that's what we called it at launch.</p>
+</div>
+
 Today, [PostHog Code](/desktop) enters beta. 
 
 It's a desktop app that runs coding agents on top of your product data. The obvious stuff ships itself. The tricky stuff shows up as a prioritized to-do list for you to steer.

diff --git a/contents/handbook/brand/tone.md b/contents/handbook/brand/tone.md
@@ -115,12 +115,12 @@ On that last one: PostHog makes _your_ product self-driving. Keep the customer's
       <td>"PostHog has more than two dozen varied products for your needs. They are:"</td>
     </tr>
     <tr>
-      <td>"Introducing PostHog Code, the product editor that:<br/>• Understands your product<br/>• Identifies usage patterns<br/>• Triages bugs and errors for you<br/>• Creates PRs to fix them<br/>• Continuously monitors and improves your product"</td>
-      <td>"PostHog Code is the product editor that understands your product, identifies usage patterns, triages bugs and errors for you, creates PRs to fix them, and continuously monitors and improves your product."</td>
+      <td>"Introducing PostHog Desktop, the product editor that:<br/>• Understands your product<br/>• Identifies usage patterns<br/>• Triages bugs and errors for you<br/>• Creates PRs to fix them<br/>• Continuously monitors and improves your product"</td>
+      <td>"PostHog Desktop is the product editor that understands your product, identifies usage patterns, triages bugs and errors for you, creates PRs to fix them, and continuously monitors and improves your product."</td>
     </tr>
     <tr>
-      <td>"Fable 5's in PostHog Code (again)"</td>
-      <td>"We're proud to announce that Fable 5 is now available in PostHog Code. Happy coding!"</td>
+      <td>"Fable 5's in PostHog Desktop (again)"</td>
+      <td>"We're proud to announce that Fable 5 is now available in PostHog Desktop. Happy coding!"</td>
     </tr>
     <tr>
       <td>(reply) "this is incredible"</td>

diff --git a/contents/handbook/company/do-more-weird.mdx b/contents/handbook/company/do-more-weird.mdx
@@ -27,7 +27,7 @@ Weird ideas are fragile, so the most important feedback you can give if you see
 - Creating James Hawkins action figures and [filming an ad](https://www.youtube.com/watch?v=xxBqKIBBxQw) for them
 - Creating a fake boardroom along with fake board meeting for another conference
 - Putting the HackerNews feed into [the Wizard](/wizard)
-- Making PostHog Code say "meep"
+- Making PostHog Desktop say "meep"
 - [DPA generator](/dpa) with fairy tale, Taylor Swift, and Gen Z slang versions
 - Having a [feet pics](/feet-pics) page (which ranked on Google for "feet pics" for a while)
 - [Hedgehog Mode](/sparks-joy/hedgehog-mode) and accompanying [documentary](https://www.youtube.com/watch?v=dGaSxBs3OsU)

diff --git a/contents/handbook/engineering/ai/ai-platform.md b/contents/handbook/engineering/ai/ai-platform.md
@@ -72,7 +72,7 @@ These are the AI features users interact with directly:
 - **[PostHog AI](/handbook/engineering/ai/products#posthog-ai)**: In-app conversational agent for interacting with PostHog
 - **[Deep research](/handbook/engineering/ai/products#deep-research)**: Automated investigative research for complex, open-ended problems
 - **[Session summaries](/handbook/engineering/ai/products#session-summaries)**: Batch analysis of session recordings to find patterns
-- **[PostHog Code](/handbook/engineering/ai/products#posthog-code)**: Agent development environment that gives each task its own isolated workspace
+- **[PostHog Desktop](/handbook/engineering/ai/products#posthog-desktop)**: Agent development environment that gives each task its own isolated workspace
 - **[Wizard](/handbook/engineering/ai/products#wizard)**: CLI tool for automated PostHog installation and setup
 - **[MCP Server](/handbook/engineering/ai/products#mcp)**: Protocol integration for third-party AI tools like Claude Code
 
@@ -88,8 +88,8 @@ The shared components that power all products:
 
 How everything connects together:
 - Products share the same agent features through the MCP server
-- Task generation systems (from Deep Research, Session Summaries, PostHog signals) feed PostHog Code
-- The Wizard and PostHog Code consume MCP tools to interact with PostHog
+- Task generation systems (from Deep Research, Session Summaries, PostHog signals) feed PostHog Desktop
+- The Wizard and PostHog Desktop consume MCP tools to interact with PostHog
 
 For a detailed technical overview, see [AI platform architecture](/handbook/engineering/ai/architecture).
 
@@ -119,13 +119,13 @@ Analyze hundreds of session recordings in minutes instead of hours. Session summ
 
 [Learn more →](/handbook/engineering/ai/products#session-summaries)
 
-### PostHog Code [Beta]
+### PostHog Desktop [Beta]
 An agent development environment that solves the messy workflow problem of engineering with coding agents. Each task gets its own isolated workspace where an agent works — you can guide the agent, review changes, and switch between workspaces, with everything related to a task in one place instead of across your terminal, editor, and GitHub.
 
 **Best for**: Product engineers who work on multiple tasks simultaneously and already use agents heavily
 **Status**: Beta | **Pricing**: Usage-based (AI credits, no markup) with free tier
 
-[Learn more →](/handbook/engineering/ai/products#posthog-code)
+[Learn more →](/handbook/engineering/ai/products#posthog-desktop)
 
 ### Wizard [General availability]
 Get PostHog set up in minutes instead of hours. The Wizard detects your tech stack, generates integration code, verifies the installation, and gets you collecting data with minimal manual work.
@@ -168,7 +168,7 @@ For a list of key concepts definitions, see the [Glossary](/handbook/engineering
 The AI platform is actively evolving. Major initiatives include:
 
 - **Third-party context integration**: Connect PostHog AI to Slack, Zendesk, and other tools for richer context
-- **PostHog Code expansion**: Moving from alpha dogfooding to broader availability
+- **PostHog Desktop expansion**: Moving from alpha dogfooding to broader availability
 - **Deep research refinement**: Improving research strategies and denoising algorithms
 - **Mode expansion**: Adding more specialized agent modes as product teams identify needs
 

diff --git a/contents/handbook/engineering/ai/architecture.md b/contents/handbook/engineering/ai/architecture.md
@@ -16,7 +16,7 @@ graph TB
         PostHogAIUI[PostHog AI<br/>In-app Agent]
         DeepResearch[Deep Research]
         SessionSum[Session Summaries]
-        PostHogCode[PostHog Code<br/>Desktop App]
+        PostHogCode[PostHog Desktop]
         Wizard[Wizard<br/>CLI Tool]
         ClaudeCode[Claude Code /<br/>Other AI Tools]
     end
@@ -54,9 +54,9 @@ graph TB
 
 1. **The agent uses dynamic modes**: The single-loop agent architecture uses dynamically loadable modes that expose PostHog capabilities.
 
-2. **MCP provides universal access**: The MCP server makes agent features accessible to any MCP-compatible client. PostHog AI, PostHog Code, Session Summaries, Wizard, and third-party tools like Claude Code all consume the same MCP server.
+2. **MCP provides universal access**: The MCP server makes agent features accessible to any MCP-compatible client. PostHog AI, PostHog Desktop, Session Summaries, Wizard, and third-party tools like Claude Code all consume the same MCP server.
 
-3. **Task generation feeds PostHog Code**: Signals from PostHog data, PostHog AI conversations, and Deep Research investigations are processed into structured tasks that PostHog Code can execute.
+3. **Task generation feeds PostHog Desktop**: Signals from PostHog data, PostHog AI conversations, and Deep Research investigations are processed into structured tasks that PostHog Desktop can execute.
 
 4. **Shared features**: Every surface consumes the same agent features through the MCP, ensuring consistency across the platform.
 
@@ -172,11 +172,11 @@ The problem we needed to solve: PostHog AI and the MCP server were developed by
 
 The solution is an abstraction layer. Agent modes expose both high-level LLM tools (like "create a funnel with these parameters") and low-level API endpoint tools (like "call POST /api/projects/{id}/insights"). Both PostHog AI and the MCP have access to the same features, just through different interfaces.
 
-## How PostHog Code and Wizard fit in
+## How PostHog Desktop and Wizard fit in
 
-Both PostHog Code and the Wizard currently consume the MCP. This integration gives them access to all the agent modes we're building. If Claude Code (which PostHog Code uses for code generation) ever becomes a bottleneck, we could swap in PostHog's own single-loop agent since they share the same mental model. We'd need to copy over Claude Code's terminal and file system tools (bash, grep, etc.) and add them as core tools.
+Both PostHog Desktop and the Wizard currently consume the MCP. This integration gives them access to all the agent modes we're building. If Claude Code (which PostHog Desktop uses for code generation) ever becomes a bottleneck, we could swap in PostHog's own single-loop agent since they share the same mental model. We'd need to copy over Claude Code's terminal and file system tools (bash, grep, etc.) and add them as core tools.
 
-We could also tag modes for specific interfaces. For example, a `CodingMode(tags=["posthog-code"])` would only be exposed to the PostHog Code agent, not to PostHog AI, because it's specific to code generation workflows.
+We could also tag modes for specific interfaces. For example, a `CodingMode(tags=["posthog-code"])` would only be exposed to the PostHog Desktop agent, not to PostHog AI, because it's specific to code generation workflows.
 
 ## Glossary
 

diff --git a/contents/handbook/engineering/ai/implementation.md b/contents/handbook/engineering/ai/implementation.md
@@ -8,7 +8,7 @@ This page provides implementation guidance for building AI features at PostHog.
 
 ## How PostHog AI works across surfaces
 
-PostHog AI isn't a single product – it's a platform that works wherever customers work. Through a combination of MCP tools and skills, PostHog AI is available across any agent of the customer's choice: PostHog AI in the web, PostHog Code, Claude Code, Cursor, Codex, and others.
+PostHog AI isn't a single product – it's a platform that works wherever customers work. Through a combination of MCP tools and skills, PostHog AI is available across any agent of the customer's choice: PostHog AI in the web, PostHog Desktop, Claude Code, Cursor, Codex, and others.
 
 All of these surfaces share the same underlying capabilities. The MCP server exposes PostHog's API as atomic tools, and skills teach agents how to compose those tools into workflows. When a product team adds a new MCP tool or writes a new skill, every surface benefits automatically.
 
@@ -22,9 +22,9 @@ PostHog AI in the web is a sandboxed coding agent built on the Agents SDK (Claud
 - **User-created custom skills and capabilities** – customers can create their own skills to teach the agent domain-specific workflows.
 - **Generative UI for complex needs** – for the most complex UI requirements, the agent can generate custom visualizations and interfaces on the fly.
 
-### PostHog Code
+### PostHog Desktop
 
-PostHog Code is a desktop agent that turns PostHog signals into shipped code. It watches PostHog for problems (errors, frustration patterns, user feedback) and automatically creates tasks, generates fixes, and opens pull requests with human oversight at key decision points.
+PostHog Desktop is a desktop agent that turns PostHog signals into shipped code. It watches PostHog for problems (errors, frustration patterns, user feedback) and automatically creates tasks, generates fixes, and opens pull requests with human oversight at key decision points.
 
 ### Third-party agents
 
@@ -98,13 +98,13 @@ So that users can learn how to use PostHog without worrying about being charged,
 
 ### How users should think about our products
 
-**PostHog AI** is the main PostHog product for AI interactions. You can use it in the web for the richest experience, through PostHog Code for code-generation workflows, or through any third-party agent via MCP. The web UX is best for sharing, navigation, and linking between AI results and PostHog artifacts. PostHog AI is also trained on PostHog-specific patterns and your actual usage data, so it provides higher quality, more contextual results than a general-purpose AI.
+**PostHog AI** is the main PostHog product for AI interactions. You can use it in the web for the richest experience, through PostHog Desktop for code-generation workflows, or through any third-party agent via MCP. The web UX is best for sharing, navigation, and linking between AI results and PostHog artifacts. PostHog AI is also trained on PostHog-specific patterns and your actual usage data, so it provides higher quality, more contextual results than a general-purpose AI.
 
 **Deep research** is a feature available within PostHog AI, but also accessible through its own dedicated UI if you want to jump straight into research. Use it for open-ended investigative work where you're trying to understand a complex problem.
 
 **Session summaries** is callable from PostHog AI and Deep research, and also has its own UI. Use it when you need to analyze many session recordings and extract patterns or issues.
 
-**PostHog Code** is a desktop product for single-engineer use. It's separate from PostHog AI because the workflow is different – you're not asking questions, you're letting an AI agent watch PostHog for problems and automatically fix them in your codebase. Think of it as an AI assistant that lives in your development environment.
+**PostHog Desktop** is a desktop product for single-engineer use. It's separate from PostHog AI because the workflow is different – you're not asking questions, you're letting an AI agent watch PostHog for problems and automatically fix them in your codebase. Think of it as an AI assistant that lives in your development environment.
 
 **MCP** is for users who prefer to work in third-party tools like Claude Code, Cursor, or Codex. You get access to PostHog's data and can combine it with other MCP servers (like Hubspot or Zendesk). The trade-off is you don't get PostHog AI's polished UX or PostHog-specific optimizations.
 
@@ -114,19 +114,19 @@ So that users can learn how to use PostHog without worrying about being charged,
 2. **Write YAML configs and skills.** Use the monorepo Claude Code skills to scaffold tool definitions and write skills (TODO: dedicated skill for this).
 3. **Build skills and dump them locally.** Run `hogli build:skills` to render all skills, then unzip them into `.agents/skills/` so Claude Code can pick them up during local testing: `unzip -o products/posthog_ai/dist/skills.zip -d .agents/skills/`.
 4. **Test with headless agents, not UIs.** Forget about UIs – that's for humans. Test your tools and skills by talking to Claude Code or another headless agent. If the agent can accomplish the job, the capability works.
-5. **Test with PostHog Code.** Sign in to a local environment in PostHog Code and verify the end-to-end workflow.
+5. **Test with PostHog Desktop.** Sign in to a local environment in PostHog Desktop and verify the end-to-end workflow.
 6. **Alternatively, add the local MCP server to Claude Code.** Run `claude mcp add --transport http posthog-local http://localhost:8787/mcp` to point Claude Code at your local MCP server.
 
 
 ## Future directions
 
 ### Third-party context integration
 
-We want to connect PostHog AI to third-party tools for additional context. Imagine PostHog AI analyzing data across PostHog, Slack messages, and Zendesk tickets to understand not just what users are doing, but what they're saying and reporting. This data could also generate signals for PostHog Code – if users are complaining about a bug in Slack and PostHog sees errors in the same area, that's a strong signal to investigate and potentially fix automatically.
+We want to connect PostHog AI to third-party tools for additional context. Imagine PostHog AI analyzing data across PostHog, Slack messages, and Zendesk tickets to understand not just what users are doing, but what they're saying and reporting. This data could also generate signals for PostHog Desktop – if users are complaining about a bug in Slack and PostHog sees errors in the same area, that's a strong signal to investigate and potentially fix automatically.
 
 ### Continuous instrumentation
 
-The Wizard's future evolution involves continuous instrumentation – watching your codebase and suggesting event tracking for new features, filling gaps in existing tracking, and standardizing event patterns. This could integrate with PostHog Code to automatically handle PostHog instrumentation when generating code.
+The Wizard's future evolution involves continuous instrumentation – watching your codebase and suggesting event tracking for new features, filling gaps in existing tracking, and standardizing event patterns. This could integrate with PostHog Desktop to automatically handle PostHog instrumentation when generating code.
 
 ### Research improvements