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Error tracking Q1 goals (#14132)
* add objectives * add driver * adapt with comments
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### Q4 2025 Objectives
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### Q1 2026 Objectives
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#### Go all in on AI (Driver: <TeamMember name="David Newell" />)
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* Implement issue autofixing
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* In-app flow where an issue can be assigned to Max
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* Build terminal based experience within the CLI
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* Add issue selection to MCP (e.g. by file, most impactful)
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* Stretch: Add test writing agent to prevent regressions
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* Add exception capture auto instrumentation to the wizard
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* Integrations to capture exceptions for popular LLM / agent tools (e.g. Langchain)
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#### **Alerting** - Spikes & Digest (Driver: <TeamMember name="Aleksander Błaszkiewicz" />)
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* Define how we calculate a spike and what are the controls
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* Add 'Issue Spiked' trigger in alerting
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* Add ability to snooze issues from alerting
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* Create weekly digest (warnings, resolved, recommendations, priorities...)
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* Stretch: correlate with event traffic to understand the context of a “spike”
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#### Ship mobile error tracking (Driver: <TeamMember name="Manoel Aranda Neto" />)
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* Complete 'straightforward' section of the [megaissue](https://github.com/PostHog/posthog/issues/38845)
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* Support suppression rules
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* Add suppression of minified exceptions before cymbal processing
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* Build dashboard template including crash free sessions / users metric
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#### **Engagement** - Search & Speed (Driver: <TeamMember name="Aleksander Błaszkiewicz" />)
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* Move issues to CH to avoid dual DB query
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* Stretch: Improve loading speed on search results
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#### Research deep dive on customers (Driver: <TeamMember name="Cory Slater" />)
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* Interview existing, potential, and recently churned customers to understand:
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* What makes people switch from competitors and what pulls them back?
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* What value would convince customers to remove billing limits?
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* How do AI-first companies handle errors differently?
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* What context would let customers skip steps in their workflow?
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* What drives month to month swings in spend vs contraction?
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* Every engineer to attend at least 2 customer interviews
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#### **Grouping** - Fingerprint & Sourcemaps (Driver: <TeamMember name="Hugues Pouillot" />)
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* Iterate on fingerprint algorithm and compare with existing approach using rand index
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* Stretch: Add bundler plugins to make sourcemap uploads easier
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* Stretch: Explore embedding based grouping
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#### Increase trust in product (Driver: <TeamMember name="Hugues Pouillot" />)
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* Improve issue grouping
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* Introduce a measure of grouping accuracy to base changes off
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* Add fingerprint versioning to avoid duplicate issues when iterating
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* Fix obvious mis-groupings based on minor stack trace variances
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* Ship embeddings to support merge suggestions
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* Decide with Team ClickHouse on approach to avoid dual DB querying
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* Reduce the number of stacktrace-less issues
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* Give better context when a recording is not found / source maps missing
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* Rethink UI / UX of issue page
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#### **Collection** - Cymbal refactoring & Mobile support (Driver: <TeamMember name="Hugues Pouillot" />)
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* Expose frame resolution and issue processing as endpoints
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* Coordinate with Ingestion team to move cymbal processing into plugin server
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* Make CLI compatible with stable chunk ids to:
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* be compatible with debug id specification and reuse current tooling.
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* avoid rebuilding application
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* speed up ingestion by reducing symbol set downloads
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* reduce symbol set uploads
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* Add debug symbol upload command to CLI
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* Support debug symbols with cymbal
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#### Improving context on issues (Driver: <TeamMember name="Aleksander Błaszkiewicz" />)
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* Add breakdowns to issues (by release / person_id)
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* Show first affected release & relevant commit
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* Stretch: Auto assign to commit author
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* Level up Node SDK (add contexts & tagging, $session_id propagation)
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* Capture code variables in Python
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* Stretch: Integrate logs into session timeline
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#### Stretch: Billing, spikes and alerts (Driver: <TeamMember name="Oliver Browne" />)
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(Note: this goal largely depends on the capacity Olly has outside of mobile error tracking, which takes precedence)
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* **Email** alerts for total exceptions ingested volume spikes
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* Add billing limits to onboarding
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* Fixed issue sampling (manually configured, drop X% of exceptions for this issue)
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* Stretch: Adaptive sampling (spread exception capture over billing period)
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* Threshold based alerting per-issue, based on product analytics insight alerts
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* Support "X occurrences per Y duration"
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* Add to alerting step during onboarding
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* Stretch: Support "X affected users per Y duration"
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* Issue time-based snoozing (drop all exceptions for X hours/days, re-open the issue if seen after that period)
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#### **Monitoring** - Acquisition & KPIs (Driver: <TeamMember name="Cory Slater" />)
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* Define KPIs for tracking collection, grouping, alerting, engagement
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* Deep dive into acquisition metrics
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* Case study around successful migration

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