Hyperprobe

my question is does it affect my app data or not and second thing is when i use multiples apps at once dose it work smooth ?

Interesting approach, does customer sensitive data leave the application ever? How does this not affect certifications like soc2, gdpr, HIPAA etc

One Shot , drop 2 birds - Sentry & Datadog 😉

Interesting approach, but I'd want to understand the guardrails before letting an agent do this on its own. "Read-only" still means the agent is deciding on its own, at 2am, which running production service to attach a probe to and what to inspect. Is there any human approval step in that path, or an audit log of every probe that gets dropped, or is the trust boundary basically "we trust the agent's judgment on production systems" out of the box?

How do you handle sensitive product data when the probes capture variable state?

Huge congrats on the launch, team! Debugging runtime production issues when using coding agents has always felt like the biggest bottleneck. Giving agents dynamic, real variable state right from the IDE instead of digging through logs and constantly redeploying is an absolute game-changer.Excited to see how HyperProbe transforms AI-assisted workflows. Wishing you guys massive success today! 🙌

How do you make sure this doesn't slow down my app?

Congrats on today's launch!!

Read only isn't the same as safe here. The probe still lifts live variable values, so the first question from any security team is what happens when an agent probes the frame holding a card number or a session token, and whether that value ends up in your storage. Zero overhead is doing a lot of work in that sentence too, I'd put a p99 next to it. The 9.5 minutes is the number that actually sells this.

AI agents write and ship almost all our code to production. So when something breaks in production at 2AM, nobody can explain why the running system behaved that way.Worse, these failures don't reproduce locally. They pass tests and code review. So when they fire in prod, your agent guesses from logs and traces that never captured the in-memory state at failure. Engineers add console.logs, redeploy, and wait, while the issue keeps bleeding users.HyperProbe eliminates this loop. When something breaks at 2AM, your agent (Claude Code, Codex, Cursor) can now drop read-only probes into the running service using our MCP, and capture the exact variable values logs, traces never had. Probes are non-blocking and add zero-overhead. So instead of guessing and burning thousands of tokens, agents debug live issues like a local repro, without risking more downtime.One of our users solved a payments issue in 9.5 minutes that previously took their engineers 4 hours. We think the shape of telemetry will change from always-on to on-demand with agents. We have both spent years building and running production at scale, previously at OYO and LimeTray. We have seen how the context engineers carry was critical to running systems reliably. That context is shrinking fast with coding agents. We'd love feedback from engineers and teams shipping fast who want their agents to have safe eyes and ears into running code. When was the last time you were pulled into a war room for something you could have fixed in 10 minutes if you had the right data?Find a time at hyperprobe.co or write to shailendra@hyperprobe.co or karan@hyperprobe.co👉 Add the SDK to your backend, plug our MCP into Cursor/Claude Code in 60 seconds and let it debug a issue in your staging environment (move to prod later)