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Hey HN, I am Dimittri and we’re building Sonarly (<a href="https:&#x2F;&#x2F;sonarly.com">https:&#x2F;&#x2F;sonarly.com</a>): an AI engineer for production. It connects to your observability tools like Sentry, Datadog, or user feedback channels, triages issues, and fixes them to cut your resolution time.Before starting this company, my co-founder and I had a B2C app in edtech and had, some days, thousands of users using the app. We pushed several times a day without proper testing and started by relying on user feedback. Then we set up Sentry, it was catching a lot of bugs, but we had up to 50 alerts a day. With 2 people it&#x27;s a lot. We took a lot of time filtering the noise to find the real signal so we knew which bug to focus on.At the same time, we saw how important it is to fix a bug fast when it hits users. The majority are not patient, and that&#x27;s not their job. For us, a bug means in the worst case a churn and in the best a frustrated user. And there are always bugs in production, due to code errors, database mismatches, infrastructure overload, and whole bunches of issues that are linked to a specific user behavior. You can&#x27;t catch these before, even with E2E tests or AI code reviews (which catch a lot of bugs but obviously not all, plus it takes time to run at each deployment). This is even more true with vibe-coding (or agentic engineering).We started Sonarly with this idea. More software than ever is being built and users should have the best experience possible on every product. The main idea of Sonarly is to reduce the MTTR (Mean Time To Repair).We started by recreating a Sentry-like tool but without the noise, using only text and session replays as the interface. We built our own frontend tracker (based on open-source rrweb) and used the backend Sentry SDK (open source as well). Companies could just add another tracker in the frontend and add a DSN in their Sentry config to send data to us in addition to Sentry.We wanted to build an interface where you don&#x27;t need to check logs, dashboards, traces, metrics, and code, as the agent would do it for you with plain English to explain the &quot;what,&quot; &quot;why,&quot; and &quot;how do I fix it.&quot;We quickly realized companies don&#x27;t want to add a new tracker or change their monitoring stack, as these platforms do the job they&#x27;re supposed to do. So we decided to build above them. Now we connect to tools like Sentry, Datadog, Slack user feedback channels, and other integrations.Claude Code is so good at writing code, but handling runtime issues requires more than just raw coding ability. It demands deep runtime context, immediate reactivity, and intelligent triage, you can’t simply pipe every alert directly into an agent. That’s why our first step is converting noise into signal. We group duplicates and filter false positives to isolate clear issues. Once we have a confirmed signal, we trigger Claude Code with the exact context it needs, like the specific Sentry issue and relevant logs fetched via MCP (mostly using grep on Datadog&#x2F;Grafana). However, things get exponentially harder with multi-repo and multi-service architectures.So we built an internal map of the production system that is basically a .md file updated dynamically. It shows every link between different services, logs, and metrics so that Claude Code can understand the issue faster.One of our users using Sentry was receiving ~180 alerts&#x2F;day. Here is what their workflow looked like:- Receive the alert- 1) Defocus from their current task or wake up, or 2) don&#x27;t look at the alert at all (most of the time)- Go check dashboards to find the root cause (if infra type) or read the stack trace, events, etc.- Try to figure out if it was a false positive or a real problem (or a known problem already in the fixes pipeline)- Then fix by giving Claude Code the correct contextWe started by cutting the noise and went from 180&#x2F;day to 50&#x2F;day (by grouping issues) and giving a severity based on the impact on the user&#x2F;infra. This brings it down to 5 issues to focus on in the current day. Triage happens in 3 steps: deduplicating before triggering a coding agent, gathering the root cause for each alert, and re-grouping by RCA.Sonarly is really about removing the noise from production alerts by grouping duplicates and returning a root cause analysis to save time to on-call engineers and literally cut your MTTR.<a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=rr3VHv0eRdw" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=rr3VHv0eRdw</a>We launched self-serve (<a href="https:&#x2F;&#x2F;sonarly.com">https:&#x2F;&#x2F;sonarly.com</a>) and we would love to have feedback from engineers. Especially curious about your current workflows when you receive an alert from any of these channels like Sentry (error tracking), Datadog (APM), or user feedback. How do you assign who should fix it? Where do you take your context from to fix the issue? Do you have any automated workflow to fix every bug, and do you have anything you use currently to filter the noise from alerts? We have a large free tier as we mainly want feedback. You can self-serve under 2 min. I&#x27;ll be in the thread with my co-founder to answer your questions, give more technical details, and take your feedback—positive, negative, brutal, everything constructive!

Launch HN: Sonarly (YC W26) – AI agent to triage and fix your production alerts

Hi HN,I’ve been experimenting with archive format design and built 6cy as a research project.The goal is not to replace zip&#x2F;7z, but to explore:
• block-level codec polymorphism (different compression per block)
• streaming-first layout (no global seek required)
• better crash recovery characteristics
• plugin-based architecture so proprietary codecs can exist without changing the formatRight now this is an experimental v0.x format.
The specification may still change and compatibility is not guaranteed yet.I’m mainly looking for feedback on the format design rather than performance comparisons.Thanks for taking a look.

Show HN: 6cy – Experimental streaming archive format with per-block codecs

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Fun little side project I built after learning about circuit bending in cameras for intentional glitch effect. It is browser based camera toy where you &quot;rewire&quot; CCD pin pairs, turn knobs to get different glitch artefacts in real time to capture as photos. I had fun learning to simulate different pin modes - channel split, hue&#x2F;phase shifts, horizontal clock delays, colour kill etc.Here are some photos taken: <a href="https:&#x2F;&#x2F;glitchycam.com&#x2F;gallery" rel="nofollow">https:&#x2F;&#x2F;glitchycam.com&#x2F;gallery</a>I intentionally leaned towards skeuomorphic design for nostalgia. I miss the days where I&#x27;d spend hours making a button to look like a physical button. Here I chose to make it look like a &quot;good enough&quot; Teenage Engineering device UI.I tested&#x2F;used GPT-5.3-Codex to build this from scratch, since there was a lot of hype around it on X. Maybe I wasn’t using it right, but I found it needed a lot of code cleanup at every step and a lot of hand holding along the way. It missed details&#x2F;nuances and didn&#x27;t land the skeuomorphic buttons or the interaction polish. It mostly helped with boilerplate where there wasn&#x27;t much thinking&#x2F;detailing. It did give a basic starting point for the effect calculations, but didn&#x27;t really move the needle on the details.Please give it a go and let me know what you think - your photos and video never leave your browser (you can download them if you choose to). Everything is processed locally in your browser (works offline), nothing is uploaded or seen by anyone.

Show HN: Glitchy camera – a circuit-bent camera simulator in the browser

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Dear HN,My wife and I both love nature and have always wanted a Pokémon go style app, to collect and learn about different species we find.All the usual species identifying apps were didn’t feel fun enough, so we designed and built one together!Would love for you guys to give it a try and share any thoughts you have.

Show HN: Wildex – Pokémon Go for real wildlife

5:23:36 PM TUESDAY FEBRUARY 17, 2026

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