We built our own cloud agents runtime. Here's what we learned
PostHog details its cloud agent runtime architecture, which uses Temporal workflows to manage sandboxed environments for agent tasks.
PostHog details its cloud agent runtime architecture, which uses Temporal workflows to manage sandboxed environments for agent tasks.
Replay Vision is an AI layer for session recordings that identifies user struggles and automatically drafts pull requests to fix UI inconsistencies.
PostHog has released distributed tracing in beta, allowing users to send traces via OpenTelemetry to visualize request paths across services.
PostHog's Replay Vision can now identify user struggles in session replays and automatically open pull requests to address the issues.
PostHog has introduced a provisioning API that allows developers to programmatically create and manage PostHog accounts for their own users.
PostHog has introduced scouts, which are autonomous agents that monitor product data for patterns and draft fixes. This feature is now available in open beta.
PostHog has released a pipeline that ingests product signals, uses research agents to identify actionable problems, and automatically opens GitHub pull requests.
The PostHog Slack app is now in beta, allowing users to trigger automated bug fixes and feature development directly from Slack threads.
PostHog has announced plans to train models on internal data to improve proactive features like session replay analysis and synthetic user testing.
PostHog Desktop, formerly PostHog Code, is now in beta. It is a desktop application that runs coding agents on top of product data to automate bug fixes, UX issues, and conversion tweaks.
PostHog has introduced automatic clustering for LLM traces and generations. This feature helps AI product teams analyze usage patterns and identify outlier behaviors in their AI applications.
PostHog has extended its Vercel integration to v0 via MCP. This allows v0 to generate code based on real product data, including experiment results and feature flag states.
PostHog has released an integration with Vercel that syncs feature flags and experiments into Vercel's native Flags system, automating credential management.
PostHog Logs is now generally available, providing a centralized destination for logs alongside errors, session replays, and product data.
PostHog now provides automated evaluation tools that use LLMs to score generative AI outputs based on criteria like relevance and helpfulness. It includes pre-built templates for common use cases.
Workflows allows users to automate actions like sending emails or Slack alerts directly from PostHog event data. It eliminates the need for external syncing tools or custom API integrations.
PostHog has introduced a logs feature in beta, allowing developers to view backend logs directly alongside session replays and error tracking without switching platforms.
PostHog released Session Summaries in beta, a tool that uses multi-modal LLMs to analyze user session recordings and highlight issues automatically.
PostHog AI is an integrated agent that can access product data, write SQL queries, manage feature flags, and perform multi-step analyses of product usage.
Workflows has moved to beta, allowing users to automate product-led actions like emails and Slack alerts based on live event data.
PostHog introduced Workflows in alpha, an automation builder that triggers actions based on live user behavior and event data.
PostHog has rewritten its feature flag evaluation service in Rust to improve speed and reliability by moving evaluation logic from database queries to in-memory processing.
| Release-notes page | Site | Feed |
|---|---|---|
| Changelog posthog.com | posthog.com | None |
| How to publish changelog posthog.com | posthog.com | None |
| Product updates posthog.com | posthog.com | None |
| Release notes posthog.com | posthog.com | None |