PostHog vs June
Side-by-side trajectory, velocity, and editorial themes.
PostHog is wiring itself into the MCP ecosystem while shoring up mobile-SDK feature parity.
PostHog continues its weekly grind, but the May releases cluster around two themes: an MCP toolchain (alerts to Slack and webhooks, SDK Doctor, mode selection via header) and LLM analytics BYOK providers (Together AI, Azure OpenAI). At the same time the mobile teams are filling in iOS and Android session-replay controls, rage-click detection, and survey delays that previously only the web SDK had.
The shape of PostHog's surface keeps widening rather than deepening: more LLM-vendor coverage in the analytics product, more MCP-tooling so AI agents can read and act on PostHog data, more parity across SDKs. Less obvious is which surface becomes the headliner; right now Conversations, Logs, Experiments, and Client Libraries are all shipping into a single weekly digest with comparable weight.
Expect MCP integration to keep expanding from peripheral utilities into the core insights and alerting paths, with PostHog positioning itself as the analytics endpoint AI agents read from when reasoning about product usage. Mobile SDK parity work should compress in the next month or two as the gap with the web SDK closes.
June's last visible push was a tight May 2025 B2B sprint — Custom Objects, SQL traits, PostHog integration.
June is product analytics for B2B SaaS, and the only visible release activity in the input is a concentrated four-week sprint in May 2025: SQL computed traits, PostHog as a data source, increased computed-trait limits, and the GA of Custom Objects after a two-month rollout. Each release is paired with small fixes (Slack alerts, HubSpot reverse sync) suggesting a stable maintenance cadence around the headline launches.
The May 2025 batch is internally consistent: every release widens what June can model (Custom Objects), how flexibly customers can compute on it (SQL traits), or how easily it slots into existing data plumbing (PostHog source). All three target the B2B-SaaS persona that wants more than user/account analytics. After this burst the changelog goes quiet in the input — it's not clear from the entries alone whether the product moved to a slower cadence, switched publishing channels, or paused.
The entries don't support a confident prediction about what comes next. If publishing resumes from the same direction, the obvious extensions are deeper integrations with reverse-ETL or warehouse-native sources and richer pre-built health-score templates on top of SQL computed traits.
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