Lets your AI agents debug production without redeploying
HyperProbe is how backend teams debug production issues they can't reproduce locally. Instead of adding a log line and waiting on a deploy, we let Claude Code, Codex, or Cursor drop read-only probes into a running service and capture the variable state that was never recorded. From there your agent debugs like it has a local repro, closing the bug in one sitting.
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?
👉 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)
About Hyperprobe on Product Hunt
“Lets your AI agents debug production without redeploying”
Hyperprobe launched on Product Hunt on September 5th, 2026 and earned 111 upvotes and 7 comments, earning #3 Product of the Day. HyperProbe is how backend teams debug production issues they can't reproduce locally. Instead of adding a log line and waiting on a deploy, we let Claude Code, Codex, or Cursor drop read-only probes into a running service and capture the variable state that was never recorded. From there your agent debugs like it has a local repro, closing the bug in one sitting.
On the analytics side, Hyperprobe competes within SaaS, Developer Tools and Artificial Intelligence — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Hyperprobe performed against the three products that launched closest to it on the same day.
Who hunted Hyperprobe?
Hyperprobe was hunted by Garry Tan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Hyperprobe including community comment highlights and product details, visit the product overview.
Garry Tan
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 [email protected] or [email protected]
👉 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)