@suhaaspk · X

Hi! building Jungle ( Its a way for small teams to automatically triage bugs and feature requests to keep development moving while they sleep

u/kaneki0dd · Reddit

Built SignalBoard a $15/mo Canny alternative for feature voting & roadmaps Been building this because Canny charges $79/mo for something that should be simple: let users vote on features, show a public roadmap, ship a changelog. https://preview.redd.it/h2x588h0n8dh1.png?width=1200&format=png&auto=webp&s=c5a4e15c59008ee67b495b7c35e1350d314e257b What it does: Feature voting — verify once, vote with one click after that AI duplicate detection — catches near-identical

@vibe_and_go · X

@akshay_nocode · X

Not exactly — Sentry captures errors, BugOps acts on them. It reads the Sentry alert, checks recent commits, traces root cause, and opens a fix PR. Think Sentry as the sensor, BugOps as the on-call engineer that never sleeps.

@BotariaDotBot · X

This Tuesday I'm launching Botbugger on @ProductHunt 🚀 One AI reviewer gives you 10 "critical" bugs — half hallucinated. So I built two: Claude Code + Codex review your code independently, then cross-check each other. Real bugs with fixes, not noise.

@kngkng182542 · X

If you're paying for Canny, give FeedLog a look. Same workflow for collecting feedback and managing feature requests, but free during launch.

@heyayankai · X

💬 Building FeatureSay. A simple platform to collect user feedback, prioritize feature requests, and build what customers actually need.

u/dumbfoundded · Reddit

Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db

@minmuner_devlog · X

Thanks for the feedback; I’m open to anything.

@keshav__dev · X

Hi priyanka i am also building in customer feedback space but with some dev related features. Maybe you want to check

Loerei · HN

I found that describing where a broken UI is and taking screenshots for AI agents really sucks. I’m too lazy to explain an indescribable visual bug or capture a millisecond-long flash. I also don’t want to remember which file defines an element, whether it's right in the .tsx or a problem with the Parent Styles in .css. And even if you can point out the exact file, your agent still has to dig through thousands of lines of code to know what on earth you're yapping about. In a 7700-file monorepo like Cal.com, simply giving the right file in the prompt for your agent saves about 68.9% of execution time and 94.2% of the tokens your agent needs to digest. HoverSource gives all the needed information and further pushes it to -88.5% time and -94.5% tokens, basically skipping the entire digging session and jumping straight to reasoning and executing. The save is linear to how big your codebase is. I want to save tokens, but don’t want to spend my time and energy digging manually, and a junio

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