This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Software knows exactly what’s happening right before it fails. Then it crashes, and that understanding disappears. Errorcore preserves that moment, the runtime context around the failures. Instead of debugging from logs and stack traces, humans and AI get the runtime evidence behind the failure, so they can understand what happened and fix it faster. We’re turning production failures from mysteries into evidence, getting recovery time down from hours to minutes.
I’ve spent a lot of time building and debugging software close to production, and one thing kept bothering me. When something fails, the system usually had all the context needed to explain it seconds earlier, but we throw most of that context away.
So debugging becomes reconstruction. Logs, traces, stack traces, guesses.
Errorcore came from wanting to change that. Preserve the runtime evidence around a failure so engineers and AI can understand what actually happened, not just where the code broke.
We’re starting with production failures, but the bigger idea is making software execution itself easier to understand.
Would love feedback from anyone who has dealt with painful production bugs.
No comment highlights available yet. Please check back later!
About Errorcore on Product Hunt
“Runtime context layer for production failures”
Errorcore was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #158 on the daily leaderboard. Software knows exactly what’s happening right before it fails. Then it crashes, and that understanding disappears. Errorcore preserves that moment, the runtime context around the failures. Instead of debugging from logs and stack traces, humans and AI get the runtime evidence behind the failure, so they can understand what happened and fix it faster. We’re turning production failures from mysteries into evidence, getting recovery time down from hours to minutes.
Errorcore was featured in SaaS (43.9k followers), Software Engineering (42.9k followers) and Developer Tools (518.5k followers) on Product Hunt. Together, these topics include over 143.8k products, making this a competitive space to launch in.
Who hunted Errorcore?
Errorcore was hunted by hirdesh viikram. 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.
Want to see how Errorcore stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
hirdesh viikram