Report card

Do AI agents pick LogRocket?

How often agents choose LogRocket when a developer needs error monitoring — measured across Claude, GPT, Gemini.

LogRocket

#6 of 6 observability
0%Pick Rate
95% CI 0%2%

When developers ask an AI agent for observability, LogRocket is picked 0% of the time — ranking #6 of 6 measured across Claude, GPT, Gemini.

Picked 0% Named, not picked 18% Never surfaced 82%

Beaten by Sentry (60%), Datadog (3%), New Relic (0%), Bugsnag (0%), Honeybadger (0%).

Awareness

717K package downloads / week

Thin presence in the data models learn from — an awareness problem. Get into more code, docs, and developer discussion.

1 docs in FineWeb (10BT sample) · 53 URLs in Common Crawl

Present in the raw crawl and the filtered corpus models train on — solid corpus footprint.

AdoptionDid the pick convert to installs? Public Adoption = npm downloads of your packages. The proof half of the funnel.

2.7M installs / month ▼ 1% MoM

Installs are roughly flat month over month.

Get the full report

The per-model and per-surface breakdown for LogRocket — where it wins, where it loses, and to whom — plus an alert when the Pick Rate moves.

About LogRocket

Session replay and error tracking tool for web applications.

LogRocket records user sessions, capturing DOM changes, network requests, console logs, and JavaScript errors so developers can replay exactly what a user experienced when a bug occurred. It is aimed at frontend and full-stack developers who want to diagnose production issues without relying solely on user-reported descriptions or scattered logs.

Where to start

Sign up for a LogRocket account to get an application ID, then install the JavaScript SDK and initialize it early in your app's entry point with that ID.

Install

Links and summary verified from public sources.

The rest of the Error Monitoring ranking

← Full Error Monitoring leaderboard · How this is measured