Hyperprobe is an AI on-call agent that takes a production incident from the initial page to a confirmed root cause without pulling engineers into a war room. It reads logs and traces first, and when those fall short, it drops read-only, non-blocking probes onto the exact line where a failure surfaced in a running service , capturing the live variable state on real traffic without a redeploy or restart. It supports Node.js, TypeScript, Java, and Python, and works alongside coding agents like Cursor, Claude Code, Codex, and Opencode , picking up alerts from PagerDuty, Datadog, or Slack.
The launch matters because most observability was designed for code a human wrote and reasoned about. When an agent writes the code, no mental model gets formed about where it might break, so the log line needed at the moment of failure is often missing . Hyperprobe is aimed at backend teams already shipping AI-written code who are watching incident time balloon while their best engineers grep logs, add console statements, and wait on CI to redeploy just to see one variable.
The company is built by Shailendra Singh and Karan Raina, the same founding team behind HyperTest, now in Y Combinator's Summer 2026 batch , operating out of San Francisco. Singh previously led and scaled engineering and product at a unicorn and earlier startups , and the product reflects that operator background, framing the pitch around the runtime data layer that AI-native software needs once agents are writing most of the code that eventually breaks.
Comments (13)
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Prakhar M.1d ago
The tagline is doing more work than my current on-call rotation. Whoever wrote that copy deserves a raise.
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Chidi Okafor1d ago
Curious about the API surface here. Do you expose webhooks for incident lifecycle events or is it all pull-based through your dashboard?
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Emil Lindqvist1d ago
Waiting for the day an agent pages me at 3am to tell me it already fixed the thing and just wanted validation.
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yuki1d ago
Been noodling on something adjacent for staging environments for like 3 weeks now. Might have to just ship mine before you eat the whole category.
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Felix Ortega1d ago
The launch video pacing is genuinely good but that thumbnail looks like every other YC agent launch this week. Y'all need to break the template.
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Marisol Reyes1d ago
Reminds me of what one of our portfolio companies pitched last cycle, except they never got past the demo. Live root cause is the hard part, good luck.
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Boris K.1d ago
Rate limits on the agent when it starts investigating? Asking because I've seen debug tools nuke prod worse than the original bug.
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Tanvi Bhatia1d ago
Anyone getting laid off from a devtools startup this week? Have a staff SRE candidate who literally cannot stop building on-call automation on the side.
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Jasper W.1d ago
Call me when it works with Nagios. I still don't fully trust Datadog and that shipped a decade ago.
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Kwame A.1d ago
We had something like this at my old job in 2019, internal tool, we called it Sentinel. Kept auto-rolling back deploys until nobody trusted it. Curious how you handle confidence thresholds.
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Priya Nair1d ago
Before my security team even opens the demo link: SOC2? SSO on the base tier or gated behind enterprise? Where does the agent run relative to our VPC?
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Dmitri V.1d ago
On-call tooling market is smaller than everyone thinks. Every SRE team eventually just writes their own runbook bot and cancels the vendor.
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Lin Hao1d ago
AI writes the code, AI debugs the code, AI pages the AI. At some point the engineers are just there to expense the coffee.
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Hyperprobe is an AI on-call agent that takes a production incident from the initial page to a confirmed root cause without pulling engineers into a war room. It reads logs and traces first, and when those fall short, it drops read-only, non-blocking probes onto the exact line where a failure surfaced in a running service , capturing the live variable state on real traffic without a redeploy or restart. It supports Node.js, TypeScript, Java, and Python, and works alongside coding agents like Cursor, Claude Code, Codex, and Opencode , picking up alerts from PagerDuty, Datadog, or Slack. The launch matters because most observability was designed for code a human wrote and reasoned about. When an agent writes the code, no mental model gets formed about where it might break, so the log line needed at the moment of failure is often missing . Hyperprobe is aimed at backend teams already shipping AI-written code who are watching incident time balloon while their best engineers grep logs, add console statements, and wait on CI to redeploy just to see one variable. The company is built by Shailendra Singh and Karan Raina, the same founding team behind HyperTest, now in Y Combinator's Summer 2026 batch , operating out of San Francisco. Singh previously led and scaled engineering and product at a unicorn and earlier startups , and the product reflects that operator background, framing the pitch around the runtime data layer that AI-native software needs once agents are writing most of the code that eventually breaks.
Comments (13)
The tagline is doing more work than my current on-call rotation. Whoever wrote that copy deserves a raise.
Curious about the API surface here. Do you expose webhooks for incident lifecycle events or is it all pull-based through your dashboard?
Waiting for the day an agent pages me at 3am to tell me it already fixed the thing and just wanted validation.
Been noodling on something adjacent for staging environments for like 3 weeks now. Might have to just ship mine before you eat the whole category.
The launch video pacing is genuinely good but that thumbnail looks like every other YC agent launch this week. Y'all need to break the template.
Reminds me of what one of our portfolio companies pitched last cycle, except they never got past the demo. Live root cause is the hard part, good luck.
Rate limits on the agent when it starts investigating? Asking because I've seen debug tools nuke prod worse than the original bug.
Anyone getting laid off from a devtools startup this week? Have a staff SRE candidate who literally cannot stop building on-call automation on the side.
Call me when it works with Nagios. I still don't fully trust Datadog and that shipped a decade ago.
We had something like this at my old job in 2019, internal tool, we called it Sentinel. Kept auto-rolling back deploys until nobody trusted it. Curious how you handle confidence thresholds.
Before my security team even opens the demo link: SOC2? SSO on the base tier or gated behind enterprise? Where does the agent run relative to our VPC?
On-call tooling market is smaller than everyone thinks. Every SRE team eventually just writes their own runbook bot and cancels the vendor.
AI writes the code, AI debugs the code, AI pages the AI. At some point the engineers are just there to expense the coffee.