Persona Library
Community-sourced UX research

Who actually uses these products,
and what made them stay.

Deep persona profiles for the tools that run modern work. Community-validated. Exportable. Open for contribution.

5
datadogAPP-019
4 comments

The Datadog SRE

A site reliability engineer or platform engineer at a company with a production system that people depend on. Datadog is their window into that system. They've built dashboards that tell the story of what's happening in production. They've written monitors that page them when something goes wrong. They've been paged at 2am by monitors they wrote themselves and have opinions about that experience. They are better at Datadog than most people at their company and still feel like they're using 30% of what it can do.

Aha

Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about alert fatigue from monitors that fire on normal variance — the cry-wolf problem in two weeks.”

datadogAPP-126
3 comments

The Datadog SRE

A site reliability engineer or DevOps engineer responsible for the uptime and performance of production systems. They chose Datadog because it combines metrics, traces, logs, and alerts in one place — but now they're paying for all of it and the bill is terrifying. They've built dashboards that are beautiful, alerts that are precise, and runbooks that nobody reads. They are the person who gets paged at 3 AM and needs to determine in 90 seconds whether this is a real incident or a flapping alert.

Aha

The shift was quiet.”

sentryAPP-136
4 comments

The Sentry Error Wrangler

A developer — usually mid-level to senior — who has become the de facto owner of error tracking on their team. They set up Sentry, configured the alerts, and now they're the person who triages the error feed every morning. They know the difference between a real bug and a noisy exception. They've learned to read stack traces the way a doctor reads X-rays — quickly, looking for the thing that's actually wrong. They carry the mental burden of knowing exactly how many errors are happening in production at any given moment.

Aha

Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about grouping algorithms that split one bug into multiple issues or merge different bugs into one in two weeks.”

sentryAPP-094
6 comments

The Sentry Error Monitor

A backend, frontend, or full-stack developer at a product company for whom Sentry is the first place they look when something goes wrong in production. They didn't set Sentry up — it was already there when they joined — but they've learned to read its output. They've been paged because of a Sentry alert. They've traced a production incident back to a specific line using Sentry's stack traces. They've also spent 40 minutes investigating a Sentry error that turned out to be a bot making malformed requests. They've learned to filter.

Aha

It happened mid-workflow — it's Wednesday afternoon.”

pendoAPP-057
4 comments

The Pendo Product Manager

A product manager at a B2B SaaS company who owns feature adoption and in-app user education. They have engineering bandwidth for product, not for tooltips. Pendo lets them publish in-app guides without a ticket. They've also realized that Pendo's analytics tell them something different from their product analytics tool — not better, different. Pendo tells them where users are, not just what they do.

Aha

A major new feature shipped three weeks ago.”

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