Hyperprobe: Lets your AI agents debug production without redeploying

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)