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Show HN: Kimu – Open-Source Video Editor

I wanted a proper non-linear video editor built for the web. It always annoyed me how there are practically zero functioning web video editors. And here we are :)<p>Kimu can: - Work with Video, Audio & Text. - Supports Transitions. - Non-Linear Video Editing with z-axis overlays. - Split/trim - Export - A cute AI agent (coming soon!)<p>I'm in uni and I started this project out of sheer annoyance that there are zero good web video editors. It is open-source here (<a href="https://github.com/robinroy03/videoeditor" rel="nofollow">https://github.com/robinroy03/videoeditor</a>).<p>What do y'all think?

Show HN: I spent 6 years building a ridiculous wooden pixel display

I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images.<p><a href="https://kilopx.com/" rel="nofollow">https://kilopx.com/</a>

Show HN: I spent 6 years building a ridiculous wooden pixel display

I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images.<p><a href="https://kilopx.com/" rel="nofollow">https://kilopx.com/</a>

Show HN: I spent 6 years building a ridiculous wooden pixel display

I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images.<p><a href="https://kilopx.com/" rel="nofollow">https://kilopx.com/</a>

Show HN: I spent 6 years building a ridiculous wooden pixel display

I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images.<p><a href="https://kilopx.com/" rel="nofollow">https://kilopx.com/</a>

Show HN: I spent 6 years building a ridiculous wooden pixel display

I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images.<p><a href="https://kilopx.com/" rel="nofollow">https://kilopx.com/</a>

Show HN: I spent 6 years building a ridiculous wooden pixel display

I built the world's most impractical 1000-pixel display and anyone in the world can draw on it. It draws a single pixel at a time and takes 30-60 minutes to complete a single image. Anyone can participate in the project by voting for the next image to be drawn, and submitting images.<p><a href="https://kilopx.com/" rel="nofollow">https://kilopx.com/</a>

My bytecode optimizer beats Copilot by 2x

Show HN: NaturalCron – Human-Readable Scheduling for .NET (With Fluent Builder)

Hi HN!<p>I built NaturalCron because I was tired of writing and debugging CRON syntax like:<p><i>/5 </i> * * 5<p>Now you can write something human-readable in .NET:<p>var expression = new NaturalCronExpression("every 5 minutes on friday");<p>Or use a Fluent Builder for strong typing and IDE support:<p>var expression = NaturalCronExpressionBuilder .Every().Minutes(5) .On(DayOfWeek.Friday) .Build();<p>Great for: - Code-based scheduling in .NET apps - Overriding schedules from configs or databases - Displaying easy-to-read rules in UIs<p>NuGet: <a href="https://www.nuget.org/packages/NaturalCron" rel="nofollow">https://www.nuget.org/packages/NaturalCron</a> GitHub: <a href="https://github.com/hugoj0s3/NaturalCron">https://github.com/hugoj0s3/NaturalCron</a><p>Would love your feedback on syntax, builder design, and what features you'd like to see next!

Show HN: NaturalCron – Human-Readable Scheduling for .NET (With Fluent Builder)

Hi HN!<p>I built NaturalCron because I was tired of writing and debugging CRON syntax like:<p><i>/5 </i> * * 5<p>Now you can write something human-readable in .NET:<p>var expression = new NaturalCronExpression("every 5 minutes on friday");<p>Or use a Fluent Builder for strong typing and IDE support:<p>var expression = NaturalCronExpressionBuilder .Every().Minutes(5) .On(DayOfWeek.Friday) .Build();<p>Great for: - Code-based scheduling in .NET apps - Overriding schedules from configs or databases - Displaying easy-to-read rules in UIs<p>NuGet: <a href="https://www.nuget.org/packages/NaturalCron" rel="nofollow">https://www.nuget.org/packages/NaturalCron</a> GitHub: <a href="https://github.com/hugoj0s3/NaturalCron">https://github.com/hugoj0s3/NaturalCron</a><p>Would love your feedback on syntax, builder design, and what features you'd like to see next!

Show HN: NaturalCron – Human-Readable Scheduling for .NET (With Fluent Builder)

Hi HN!<p>I built NaturalCron because I was tired of writing and debugging CRON syntax like:<p><i>/5 </i> * * 5<p>Now you can write something human-readable in .NET:<p>var expression = new NaturalCronExpression("every 5 minutes on friday");<p>Or use a Fluent Builder for strong typing and IDE support:<p>var expression = NaturalCronExpressionBuilder .Every().Minutes(5) .On(DayOfWeek.Friday) .Build();<p>Great for: - Code-based scheduling in .NET apps - Overriding schedules from configs or databases - Displaying easy-to-read rules in UIs<p>NuGet: <a href="https://www.nuget.org/packages/NaturalCron" rel="nofollow">https://www.nuget.org/packages/NaturalCron</a> GitHub: <a href="https://github.com/hugoj0s3/NaturalCron">https://github.com/hugoj0s3/NaturalCron</a><p>Would love your feedback on syntax, builder design, and what features you'd like to see next!

Show HN: Wordle-style game for Fermi questions

Some months ago @andrewrn tried to create a Wordle-style site for order-of-magnitude thinking. This was a wonderful idea, but the actual site was somewhat over-engineered and confusing. (<a href="https://news.ycombinator.com/item?id=43632278">https://news.ycombinator.com/item?id=43632278</a>)<p>In the past week, I looked at this idea again and built a very simple site which gives you a new Fermi estimation question every day:<p>How many new cars were sold in the US in 2024?; How many humans have ever lived (including those currently alive)?; How many chickens are slaughtered for meat every year?<p>To win, you need a guess within ±20% of the correct answer. For this you have a maximum of 6 tries and after each guess, you can see if your answer was too high or too low.<p>Fermi questions are, by the way, a wonderful way to build up your own numeracy and sense for order-of-magnitude differences. Douglas Hofstadter proposed using them for exactly this reason in his essay "Number Numbness, or Why Innumeracy May Be Just as Dangerous as Illiteracy" (<a href="https://gwern.net/doc/math/1982-hofstadter-2.pdf" rel="nofollow">https://gwern.net/doc/math/1982-hofstadter-2.pdf</a>)

Show HN: Wordle-style game for Fermi questions

Some months ago @andrewrn tried to create a Wordle-style site for order-of-magnitude thinking. This was a wonderful idea, but the actual site was somewhat over-engineered and confusing. (<a href="https://news.ycombinator.com/item?id=43632278">https://news.ycombinator.com/item?id=43632278</a>)<p>In the past week, I looked at this idea again and built a very simple site which gives you a new Fermi estimation question every day:<p>How many new cars were sold in the US in 2024?; How many humans have ever lived (including those currently alive)?; How many chickens are slaughtered for meat every year?<p>To win, you need a guess within ±20% of the correct answer. For this you have a maximum of 6 tries and after each guess, you can see if your answer was too high or too low.<p>Fermi questions are, by the way, a wonderful way to build up your own numeracy and sense for order-of-magnitude differences. Douglas Hofstadter proposed using them for exactly this reason in his essay "Number Numbness, or Why Innumeracy May Be Just as Dangerous as Illiteracy" (<a href="https://gwern.net/doc/math/1982-hofstadter-2.pdf" rel="nofollow">https://gwern.net/doc/math/1982-hofstadter-2.pdf</a>)

Show HN: WebGPU enables local LLM in the browser – demo site with AI chat

Browser LLM demo working on JavaScript and WebGPU. WebGPU is already supported in Chrome, Safari, Firefox, iOS (v26) and Android.<p>Demo, similar to ChatGPT <a href="https://andreinwald.github.io/browser-llm/" rel="nofollow">https://andreinwald.github.io/browser-llm/</a><p>Code <a href="https://github.com/andreinwald/browser-llm">https://github.com/andreinwald/browser-llm</a><p>- No need to use your OPENAI_API_KEY - its local model that runs on your device<p>- No network requests to any API<p>- No need to install any program<p>- No need to download files on your device (model is cached in browser)<p>- Site will ask before downloading large files (llm model) to browser cache<p>- Hosted on Github Pages from this repo - secure, because you see what you are running

Show HN: WebGPU enables local LLM in the browser – demo site with AI chat

Browser LLM demo working on JavaScript and WebGPU. WebGPU is already supported in Chrome, Safari, Firefox, iOS (v26) and Android.<p>Demo, similar to ChatGPT <a href="https://andreinwald.github.io/browser-llm/" rel="nofollow">https://andreinwald.github.io/browser-llm/</a><p>Code <a href="https://github.com/andreinwald/browser-llm">https://github.com/andreinwald/browser-llm</a><p>- No need to use your OPENAI_API_KEY - its local model that runs on your device<p>- No network requests to any API<p>- No need to install any program<p>- No need to download files on your device (model is cached in browser)<p>- Site will ask before downloading large files (llm model) to browser cache<p>- Hosted on Github Pages from this repo - secure, because you see what you are running

Show HN: WebGPU enables local LLM in the browser – demo site with AI chat

Browser LLM demo working on JavaScript and WebGPU. WebGPU is already supported in Chrome, Safari, Firefox, iOS (v26) and Android.<p>Demo, similar to ChatGPT <a href="https://andreinwald.github.io/browser-llm/" rel="nofollow">https://andreinwald.github.io/browser-llm/</a><p>Code <a href="https://github.com/andreinwald/browser-llm">https://github.com/andreinwald/browser-llm</a><p>- No need to use your OPENAI_API_KEY - its local model that runs on your device<p>- No network requests to any API<p>- No need to install any program<p>- No need to download files on your device (model is cached in browser)<p>- Site will ask before downloading large files (llm model) to browser cache<p>- Hosted on Github Pages from this repo - secure, because you see what you are running

Show HN: TraceRoot – Open-source agentic debugging for distributed services

Hey Xinwei and Zecheng here, we are the authors of TraceRoot (<a href="https://github.com/traceroot-ai/traceroot">https://github.com/traceroot-ai/traceroot</a>).<p>TraceRoot (<a href="https://traceroot.ai">https://traceroot.ai</a>) is an open-source debugging platform that helps engineers fix production issues faster by combining structured traces, logs, source code contexts and discussions in Github PRs, issues and Slack channels, etc. with AI Agents.<p>At the heart are our lightweight Python (<a href="https://github.com/traceroot-ai/traceroot-sdk">https://github.com/traceroot-ai/traceroot-sdk</a>) and TypeScript (<a href="https://github.com/traceroot-ai/traceroot-sdk-ts">https://github.com/traceroot-ai/traceroot-sdk-ts</a>) SDKs - they can hook into your app using OpenTelemetry and captures logs and traces. These are either sent to a local Jaeger (<a href="https://www.jaegertracing.io/" rel="nofollow">https://www.jaegertracing.io/</a>) + SQLite backend or to our cloud backend, where we correlate them into a single view. From there, our custom agent takes over.<p>The agent builds a heterogeneous execution tree that merges spans, logs, and GitHub context into one internal structure. This allows it to model the control and data flow of a request across services. It then uses LLMs to reason over this tree - pruning irrelevant branches, surfacing anomalous spans, and identifying likely root causes. You can ask questions like “what caused this timeout?” or “summarize the errors in these 3 spans”, and it can trace the failure back to a specific commit, summarize the chain of events, or even propose a fix via a draft PR.<p>We also built a debugging UI that ties everything together - you explore traces visually, pick spans of interest, and get AI-assisted insights with full context: logs, timings, metadata, and surrounding code. Unlike most tools, TraceRoot stores long-term debugging history and builds structured context for each company - something we haven’t seen many others do in this space.<p>What’s live today:<p>- Python and TypeScript SDKs for structured logs and traces.<p>- AI summaries, GitHub issue generation, and PR creation.<p>- Debugging UI that ties everything together<p>TraceRoot is MIT licensed and easy to self-host (via Docker). We support both local mode (Jaeger + SQLite) and cloud mode. Inspired by OSS projects like PostHog and Supabase - core is free, enterprise features like agent mode multi-tenant and slack integration are paid.<p>If you find it interesting, you can see a demo video here: <a href="https://www.youtube.com/watch?v=nb-D3LM0sJM" rel="nofollow">https://www.youtube.com/watch?v=nb-D3LM0sJM</a><p>We’d love you to try TraceRoot (<a href="https://traceroot.ai">https://traceroot.ai</a>) and share any feedback. If you're interested, our code is available here: <a href="https://github.com/traceroot-ai/traceroot">https://github.com/traceroot-ai/traceroot</a>. If we don’t have something, let us know and we’d be happy to build it for you. We look forward to your comments!

Show HN: TraceRoot – Open-source agentic debugging for distributed services

Hey Xinwei and Zecheng here, we are the authors of TraceRoot (<a href="https://github.com/traceroot-ai/traceroot">https://github.com/traceroot-ai/traceroot</a>).<p>TraceRoot (<a href="https://traceroot.ai">https://traceroot.ai</a>) is an open-source debugging platform that helps engineers fix production issues faster by combining structured traces, logs, source code contexts and discussions in Github PRs, issues and Slack channels, etc. with AI Agents.<p>At the heart are our lightweight Python (<a href="https://github.com/traceroot-ai/traceroot-sdk">https://github.com/traceroot-ai/traceroot-sdk</a>) and TypeScript (<a href="https://github.com/traceroot-ai/traceroot-sdk-ts">https://github.com/traceroot-ai/traceroot-sdk-ts</a>) SDKs - they can hook into your app using OpenTelemetry and captures logs and traces. These are either sent to a local Jaeger (<a href="https://www.jaegertracing.io/" rel="nofollow">https://www.jaegertracing.io/</a>) + SQLite backend or to our cloud backend, where we correlate them into a single view. From there, our custom agent takes over.<p>The agent builds a heterogeneous execution tree that merges spans, logs, and GitHub context into one internal structure. This allows it to model the control and data flow of a request across services. It then uses LLMs to reason over this tree - pruning irrelevant branches, surfacing anomalous spans, and identifying likely root causes. You can ask questions like “what caused this timeout?” or “summarize the errors in these 3 spans”, and it can trace the failure back to a specific commit, summarize the chain of events, or even propose a fix via a draft PR.<p>We also built a debugging UI that ties everything together - you explore traces visually, pick spans of interest, and get AI-assisted insights with full context: logs, timings, metadata, and surrounding code. Unlike most tools, TraceRoot stores long-term debugging history and builds structured context for each company - something we haven’t seen many others do in this space.<p>What’s live today:<p>- Python and TypeScript SDKs for structured logs and traces.<p>- AI summaries, GitHub issue generation, and PR creation.<p>- Debugging UI that ties everything together<p>TraceRoot is MIT licensed and easy to self-host (via Docker). We support both local mode (Jaeger + SQLite) and cloud mode. Inspired by OSS projects like PostHog and Supabase - core is free, enterprise features like agent mode multi-tenant and slack integration are paid.<p>If you find it interesting, you can see a demo video here: <a href="https://www.youtube.com/watch?v=nb-D3LM0sJM" rel="nofollow">https://www.youtube.com/watch?v=nb-D3LM0sJM</a><p>We’d love you to try TraceRoot (<a href="https://traceroot.ai">https://traceroot.ai</a>) and share any feedback. If you're interested, our code is available here: <a href="https://github.com/traceroot-ai/traceroot">https://github.com/traceroot-ai/traceroot</a>. If we don’t have something, let us know and we’d be happy to build it for you. We look forward to your comments!

Show HN: Pontoon – Open-source customer data syncs

Hi HN,<p>We’re Alex and Kalan, the creators of Pontoon (<a href="https://github.com/pontoon-data/Pontoon">https://github.com/pontoon-data/Pontoon</a>). Pontoon is an open-source data export platform that makes it really easy to create data syncs and send data to your enterprise customers. Check out our demo here: <a href="https://app.storylane.io/share/onova7c23ai6">https://app.storylane.io/share/onova7c23ai6</a> or try it out with docker: <a href="https://pontoon-data.github.io/Pontoon/getting-started/quick-start/" rel="nofollow">https://pontoon-data.github.io/Pontoon/getting-started/quick...</a><p>While at our prior roles as data engineers, we’ve both felt the pain of data APIs. We either had to spend weeks building out data pipelines in house or spend a lot on ETL tools like Fivetran (<a href="https://www.fivetran.com/" rel="nofollow">https://www.fivetran.com/</a>). However, there were a few companies that offered data syncs that would sync directly to our data warehouse (eg. Redshift, Snowflake, etc.), and when that was an option, we always chose it. This led us to wonder “Why don’t more companies offer data syncs?”. It turns out, building reliable cross-cloud data syncs is difficult. That’s why we built Pontoon.<p>We designed Pontoon to be:<p>- Easily deployed: we provide a single, self-contained Docker image for easy deployment and Docker Compose for larger workloads (<a href="https://pontoon-data.github.io/Pontoon/getting-started/quick-start/" rel="nofollow">https://pontoon-data.github.io/Pontoon/getting-started/quick...</a>)<p>- Support modern data warehouses: we support syncing to/from Snowflake, BigQuery, Redshift, and Postgres.<p>- Sync cross cloud: sync from BigQuery to Redshift, Snowflake to BigQuery, Postgres to Redshift, etc.<p>- Developer friendly: data syncs can also be built via the API<p>- Open source: Pontoon is free to use by anyone<p>Under the hood, we use Apache Arrow (<a href="https://arrow.apache.org/" rel="nofollow">https://arrow.apache.org/</a>) to move data between sources and destinations. Arrow is very performant - we wanted to use a library that could handle the scale of moving millions of records per minute.<p>In the shorter-term, there are several improvements we want to make, like:<p>- Adding support for DBT models to make adding data models easier<p>- UX improvements like better error messaging and monitoring of data syncs<p>- More sources and destinations (S3, GCS, Databricks, etc.)<p>- Improve the API for a more developer friendly experience (it’s currently tied pretty closely to the front end)<p>In the longer-term, we want to make data sharing as easy as possible. As data engineers, we sometimes felt like second class citizens with how we were told to get the data we needed - “just loop through this api 1000 times”, “you probably won’t get rate limited” (we did), “we can schedule an email to send you a csv every day”. We want to change how modern data sharing is done and make it simple for everyone.<p>Give it a try <a href="https://github.com/pontoon-data/Pontoon">https://github.com/pontoon-data/Pontoon</a>. Cheers!