Example: error-tracking research
You run a small API in production, and you hear about failures from users before you see them in logs. Before writing any code, you want an engineering answer: does a dedicated error-tracking service earn its keep, and which one fits a small project? Start a new session, switch to Ask, and paste:Watch the loop start
Expand the thought/work section. Bright clarifies objectives, then typically:- Assigns an Explorer to inspect your repo and stack (framework, error handling today)
- Assigns a Researcher to compare error-tracking services on setup effort and free tiers
- Runs those tracks in parallel
What the research recommends
For this example, Bright lands on a simple call:- A dedicated service beats logs alone for production failures: grouped errors with stack traces and source context, release tagging, and alerts when a new error class appears
- Sentry fits a small project: free tier + paid tiers (see sentry.io/pricing) and a maintained Node.js SDK
- Skip self-hosting for now. It is operationally heavier than the problem justifies at this size
Bright also flags tradeoffs — for example, what you give up by not self-hosting, and when plain structured logging is still the right answer.
Suggested wiring path
1
Create the Sentry project
Create your org and project in the Sentry dashboard, and note the DSN.
2
Add env vars
Store
SENTRY_DSN server-side only.3
Install the SDK
Add the Sentry Node SDK and wire the error handler middleware.
4
Verify with a test error
Trigger one handled test error and confirm it shows up with a stack trace.