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feat: add documentation for new Inbox product
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contents/docs/inbox/changelog.mdx

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---
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title: Inbox Changelog
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sidebar: Docs
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showTitle: true
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---
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## 2024-05-20: Inbox Beta Launch
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We are excited to launch the first beta of **Inbox**!
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### Features
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- **Signal Sources:** Connect PostHog Error Tracking, Support, and GitHub Issues.
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- **AI Prioritization:** Automated P0-P3 ranking based on product impact.
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- **Self-Driving Research:** Agents use MCP to find root causes in your codebase.
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- **Automated PRs:** One-click implementation for actionable bugs.
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---
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For older updates on PostHog Code, check the [PostHog Code Changelog](/docs/code/changelog).
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---
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title: Research and Implementation
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sidebar: Docs
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showTitle: true
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---
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The "self-driving" magic of Inbox happens through two core background tasks: **Research** and **Implementation**. These are performed by autonomous AI agents.
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## Research Tasks
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When a signal (like a Sentry error or a GitHub issue) arrives, an agent is dispatched to investigate.
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### Codebase Context (MCP)
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The agent uses a **Model Context Protocol (MCP) server** to interact with your codebase. This allows it to:
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- Search for specific symbols, classes, or functions.
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- Read file contents.
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- List directory structures.
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### Root Cause Analysis
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By combining the production signal (e.g., a stack trace from Error Tracking) with codebase access, the agent identifies the root cause.
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- **Example:** An agent sees a `DoesNotExist` error in production data and finds the exact line in `billing_manager.py` where a database query is missing a null check.
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## Implementation Tasks
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Once the research is complete and a fix is identified, the agent moves to implementation.
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### Sandboxed Execution
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The agent clones your repository into a secure, sandboxed environment. It then:
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1. Creates a new git branch (e.g., `ai-fix/billing-null-check`).
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2. Applies the code changes.
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3. Runs any local tests (if configured).
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### Pull Request Generation
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The agent pushes the branch to your remote (e.g., GitHub) and opens a Pull Request.
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- **Description:** The PR includes an AI-generated summary of the problem, the proposed change, and the research reasoning.
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- **Labels:** PRs are automatically labeled with `LLM context` or `PostHog Agent` to notify reviewers.
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## Auditing the Agent
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Every action the agent takes is logged. You can view the **Agent Log** directly in the Inbox to see:
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- Which files the agent read.
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- Which search queries it ran.
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- How it arrived at the final implementation logic.
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This transparency ensures that you can trust the "self-driving" process even as it automates the tedious parts of your job.
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---
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title: Connecting Signal Sources
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sidebar: Docs
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showTitle: true
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---
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Inbox identifies potential work by monitoring **Signal Sources**. These sources provide the raw data that AI agents use to research and triage issues.
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## Internal PostHog Sources
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These sources are available by default if you are already using PostHog.
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### Error Tracking
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Monitors your production exceptions. Inbox triggers reports when:
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- A new unique error is first seen.
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- An error is reopened after being marked resolved.
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- There is a significant spike in error volume for an existing issue.
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### Support Conversations
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Analyzes user support tickets from PostHog's built-in [support features](/docs/support). It identifies actionable bug reports or feature requests hidden within user chats.
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### Session Replay
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(Beta) Uses AI to analyze [session recordings](/docs/session-replay) for anomalous user behavior, UX friction points, or rage clicks that don't necessarily trigger an error log.
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## External Integrations
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You can connect external tools to Inbox to consolidate your engineering work into one place.
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### GitHub Issues
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Inbox monitors your repositories for new issues. When a GitHub issue is opened, Inbox automatically kicks off a **Research Task** to see if it can propose a fix.
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### Linear & Zendesk
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By connecting Linear (for project management) or Zendesk (for customer support), Inbox can:
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1. Read the ticket/issue context.
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2. Search your codebase for relevant logic.
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3. Propose a fix that references the original ticket ID.
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## Configuration
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To manage your sources:
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1. Navigate to **Inbox** in the main PostHog navigation.
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2. Click the **Settings** icon (or the "Signal Sources" tab).
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3. Toggle the sources you wish to enable and follow the authentication prompts for external services.
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> **Note:** For agents to successfully research issues from these sources, you must have a connected repository with a configured [MCP server](/docs/ai-engineering/mcp).

contents/docs/inbox/start-here.mdx

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---
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title: Getting started with Inbox
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sidebar: Docs
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showTitle: true
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---
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import { QuestLog, QuestLogItem } from 'components/Docs/QuestLog'
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import OSButton from 'components/OSButton'
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PostHog **Inbox** is your command center for self-driving development. It uses signals from your production data—like error spikes, user complaints, and session anomalies—to automatically research issues, write code fixes, and open pull requests.
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Instead of reactive firefighting, Inbox moves your workflow to a "proactive merging" model where AI agents do the heavy lifting of investigation and implementation.
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<QuestLog firstSpeechBubble="Let's set up your self-driving command center!" lastSpeechBubble="Your Inbox is ready. Time to start merging!">
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<QuestLogItem
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title="Connect your Signal Sources"
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subtitle="Required"
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icon="IconPlug"
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>
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Inbox identifies work by monitoring "Signals." To get started, you need to connect the sources where your product data and user feedback live.
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- **Internal:** Enable [Error Tracking](/docs/error-tracking), [Support Conversations](/docs/support), and [Session Replay](/docs/session-replay).
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- **External:** Connect your [GitHub Issues, Linear, or Zendesk](/docs/inbox/signal-sources) accounts.
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<OSButton variant="primary" asLink to="/docs/inbox/signal-sources">
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Configure sources
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</OSButton>
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</QuestLogItem>
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<QuestLogItem
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title="Triage actionable reports"
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subtitle="Required"
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icon="IconTerminal"
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>
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Once sources are connected, Inbox clusters signals into **Reports**. Each report is automatically ranked by:
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- **Priority (P0-P3):** Determined by the impact on user flow and code importance.
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- **Actionability:** Marked as "Actionable" if an agent has found a clear path to a fix.
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Review your first report to see the root cause analysis and the proposed resolution logic.
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<OSButton variant="primary" asLink to="/docs/inbox/triage-and-priority">
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Learn about prioritization
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</OSButton>
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</QuestLogItem>
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<QuestLogItem
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title="Audit Agent Research"
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subtitle="Recommended"
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icon="IconMagnifyingGlass"
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>
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For actionable reports, an AI agent automatically performs a **Research Task**. It uses the [Model Context Protocol (MCP)](/docs/ai-engineering/mcp) to search your codebase and identify the exact lines of code causing the issue.
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You can audit the agent's logs to see exactly how it navigated your repo and reached its conclusions.
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<OSButton variant="primary" asLink to="/docs/inbox/research-and-implementation">
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See how agents research
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</OSButton>
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</QuestLogItem>
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<QuestLogItem
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title="Merge your first PR"
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subtitle="The Goal"
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icon="IconRocket"
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>
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When research is complete, the agent executes an **Implementation Task**: cloning your repo, creating a branch, and opening a GitHub PR.
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Each PR includes an AI-generated description of the problem and the change. Your job is simply to review the code in GitHub and click **Merge**.
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<OSButton variant="primary" asLink to="/docs/inbox/research-and-implementation#implementation-tasks">
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Review the PR workflow
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</OSButton>
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</QuestLogItem>
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</QuestLog>
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## Next steps
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- Explore [how prioritization works](/docs/inbox/triage-and-priority) to focus on what matters.
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- Deep dive into [Agent Research](/docs/inbox/research-and-implementation) to understand the "self-driving" engine.
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- If you run into issues, check the [troubleshooting guide](/docs/inbox/troubleshooting).
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---
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title: Triage and Prioritization
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sidebar: Docs
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showTitle: true
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---
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The Inbox isn't just a list of errors; it's an intelligent triage system. It uses AI to cluster millions of raw signals into actionable **Reports** and ranks them so you know what to work on first.
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## Understanding Reports
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A **Report** is a high-level summary of an issue. Each report contains:
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- **The "What":** A clear description of the bug or problem.
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- **Priority:** Ranked from P0 (Critical) to P3 (Low).
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- **Actionability:** A status indicating if the AI agent has found a clear path to a code-based fix.
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## How Priority is Determined
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Inbox uses a "Product-Aware" prioritization engine. Instead of just looking at error frequency, it analyzes:
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1. **Code Importance:** Does the issue occur in a "hot path" like your checkout, signup, or billing logic?
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2. **User Impact:** How many unique users are affected? Are they on a high-value billing plan?
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3. **Severity:** Is the product completely broken for these users, or is it a minor UX glitch?
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## The Triage Workflow
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1. **P0 & P1 (Immediate Action):** These should be your first priority. If they are marked as **Actionable**, an agent has likely already opened a pull request.
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2. **Actionable Reports:** Focus on these even if the priority is lower. These represent "slam dunk" fixes where the agent has already done the research and implementation work for you.
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3. **Needs Research:** If a report isn't yet actionable, you can manually trigger a **Research Task** to have an agent investigate the codebase.
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## Assigning Owners
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Inbox automatically suggests reviewers and owners for each report based on:
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- **GitHub Blame:** Who recently touched the affected lines of code.
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- **Historical Ownership:** Who has resolved similar issues in this part of the codebase before.
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---
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title: Troubleshooting
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sidebar: Docs
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showTitle: true
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---
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## Common Issues
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### Sources are connected but no signals appear
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- **Check Permissions:** Ensure your PostHog API key has `read` permissions for the products you've enabled (e.g., Error Tracking).
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- **Verify Activity:** Signals only appear for *new* activity. If your product currently has no errors or support tickets, the Inbox will remain empty.
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### Agent fails to find the root cause
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- **MCP Server Status:** Ensure your [MCP server](/docs/ai-engineering/mcp) is correctly configured and reachable by PostHog.
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- **Codebase Indexing:** Large repositories may take time to index. If the agent can't find a file you know exists, try re-triggering the Research Task.
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### GitHub PRs aren't being created
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- **GitHub App Installation:** Ensure the PostHog GitHub App is installed on the specific repositories you want to automate.
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- **Branch Permissions:** The agent needs permission to push branches to your repository. Check your GitHub branch protection rules.
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### Prioritization feels incorrect
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- **Hot Path Configuration:** You can manually tag certain files or directories as "Hot Paths" in your Inbox settings to increase the priority of issues occurring in those files.
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## Getting Help
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If you're still stuck:
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- Check our [community forum](/questions).
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- Reach out to us via the **Support** widget in your PostHog instance.
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---
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title: Inbox Changelog
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sidebar: Docs
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showTitle: true
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---
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## 2024-05-20: Inbox Beta Launch
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We are excited to launch the first beta of **Inbox**!
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### Features
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- **Signal Sources:** Connect PostHog Error Tracking, Support, and GitHub Issues.
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- **AI Prioritization:** Automated P0-P3 ranking based on product impact.
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- **Self-Driving Research:** Agents use MCP to find root causes in your codebase.
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- **Automated PRs:** One-click implementation for actionable bugs.
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---
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For older updates on PostHog Code, check the [PostHog Code Changelog](/docs/code/changelog).
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---
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title: Research and Implementation
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sidebar: Docs
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showTitle: true
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---
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The "self-driving" magic of Inbox happens through two core background tasks: **Research** and **Implementation**. These are performed by autonomous AI agents.
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## Research Tasks
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When a signal (like a Sentry error or a GitHub issue) arrives, an agent is dispatched to investigate.
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### Codebase Context (MCP)
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The agent uses a **Model Context Protocol (MCP) server** to interact with your codebase. This allows it to:
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- Search for specific symbols, classes, or functions.
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- Read file contents.
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- List directory structures.
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### Root Cause Analysis
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By combining the production signal (e.g., a stack trace from Error Tracking) with codebase access, the agent identifies the root cause.
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- **Example:** An agent sees a `DoesNotExist` error in production data and finds the exact line in `billing_manager.py` where a database query is missing a null check.
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## Implementation Tasks
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Once the research is complete and a fix is identified, the agent moves to implementation.
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### Sandboxed Execution
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The agent clones your repository into a secure, sandboxed environment. It then:
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1. Creates a new git branch (e.g., `ai-fix/billing-null-check`).
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2. Applies the code changes.
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3. Runs any local tests (if configured).
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### Pull Request Generation
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The agent pushes the branch to your remote (e.g., GitHub) and opens a Pull Request.
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- **Description:** The PR includes an AI-generated summary of the problem, the proposed change, and the research reasoning.
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- **Labels:** PRs are automatically labeled with `LLM context` or `PostHog Agent` to notify reviewers.
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## Auditing the Agent
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Every action the agent takes is logged. You can view the **Agent Log** directly in the Inbox to see:
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- Which files the agent read.
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- Which search queries it ran.
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- How it arrived at the final implementation logic.
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This transparency ensures that you can trust the "self-driving" process even as it automates the tedious parts of your job.
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---
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title: Connecting Signal Sources
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sidebar: Docs
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showTitle: true
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---
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Inbox identifies potential work by monitoring **Signal Sources**. These sources provide the raw data that AI agents use to research and triage issues.
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## Internal PostHog Sources
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These sources are available by default if you are already using PostHog.
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### Error Tracking
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Monitors your production exceptions. Inbox triggers reports when:
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- A new unique error is first seen.
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- An error is reopened after being marked resolved.
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- There is a significant spike in error volume for an existing issue.
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### Support Conversations
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Analyzes user support tickets from PostHog's built-in [support features](/docs/support). It identifies actionable bug reports or feature requests hidden within user chats.
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### Session Replay
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(Beta) Uses AI to analyze [session recordings](/docs/session-replay) for anomalous user behavior, UX friction points, or rage clicks that don't necessarily trigger an error log.
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## External Integrations
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You can connect external tools to Inbox to consolidate your engineering work into one place.
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### GitHub Issues
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Inbox monitors your repositories for new issues. When a GitHub issue is opened, Inbox automatically kicks off a **Research Task** to see if it can propose a fix.
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### Linear & Zendesk
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By connecting Linear (for project management) or Zendesk (for customer support), Inbox can:
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1. Read the ticket/issue context.
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2. Search your codebase for relevant logic.
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3. Propose a fix that references the original ticket ID.
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## Configuration
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To manage your sources:
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1. Navigate to **Inbox** in the main PostHog navigation.
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2. Click the **Settings** icon (or the "Signal Sources" tab).
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3. Toggle the sources you wish to enable and follow the authentication prompts for external services.
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> **Note:** For agents to successfully research issues from these sources, you must have a connected repository with a configured [MCP server](/docs/ai-engineering/mcp).

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