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Show HN: Detail, a Bug Finder

Hi HN, tl;dr we built a bug finder that's working really well, especially for app backends. Try it out and send us your thoughts!<p>Long story below.<p>--------------------------<p>We originally set out to work on technical debt. We had all seen codebases with a lot of debt, so we had personal grudges about the problem, and AI seemed to be making it a lot worse.<p>Tech debt also seemed like a great problem for AI because: 1) a small portion of the work is thinky and strategic, and then the bulk of the execution is pretty mechanical, and 2) when you're solving technical debt, you're usually trying to preserve existing behavior, just change the implementation. That means you can treat it as a closed-loop problem if you figure out good ways to detect unintended behavior changes due to a code change. And we know how to do that – that's what tests are for!<p>So we started with writing tests. Tests create the guardrails that make future code changes safer. Our thinking was: if we can test well enough, we can automate a lot of other tech debt work at very high quality.<p>We built an agent that could write thousands of new tests for a typical codebase, most "merge-quality". Some early users merged hundreds of PRs generated this way, but intuitively the tool always felt "good but not great". We used it sporadically ourselves, and it usually felt like a chore.<p>Around this point we realized: while we had set out to write good tests, we had built a system that, with a few tweaks, might be very good at finding bugs. When we tested it out on some friends' codebases, we discovered that almost every repo has tons of bugs lurking in it that we were able to flag. Serious bugs, interesting enough that people dropped what they were doing to fix them. Sitting right there in peoples codebases, already merged, running in prod.<p>We also found a lot of vulns, even in mature codebases, and sometimes even right after someone had gotten a pentest.<p>Under the hood: - We check out a codebase and figure out how to build it for local dev and exercise it with tests. - We take snapshots of the built local dev state. (We use Runloop for this and are big fans.) - We spin up hundreds of copies of the local dev environment to exercise the codebase in thousands of ways and flag behaviors that seem wrong. - We pick the most salient, scary examples and deliver them as linear tickets, github issues, or emails.<p>In practice, it's working pretty well. We've been able to find bugs in everything from compilers to trading platforms (even in rust code), but the sweet spot is app backends.<p>Our approach trades compute for quality. Our codebase scans take hours, far beyond what would be practical for a code review bot. But the result is that we can make more judicious use of engineers’ attention, and we think that’s going to be the most important variable.<p>Longer term, we think compute is cheap, engineer attention is expensive. Wielded properly, the newest models can execute complicated changes, even in large codebases. That means the limiting reagent in building software is human attention. It still takes time and focus for an engineer to ingest information, e.g. existing code, organizational context, and product requirements. These are all necessary before an engineer can articulate what they want in precise terms and do a competent job reviewing the resulting diff.<p>For now we're finding bugs, but the techniques we're developing extend to a lot of other background, semi-proactive work to improve codebases.<p>Try it out and tell us what you think. Free first scan, no credit card required: <a href="https://detail.dev/" rel="nofollow">https://detail.dev/</a><p>We're also scanning on OSS repos, if you have any requests. The system is pretty high signal-to-noise, but we don't want to risk annoying maintainers by automatically opening issues, so if you request a scan for an OSS repo the results will go to you personally. <a href="https://detail.dev/oss" rel="nofollow">https://detail.dev/oss</a>

Show HN: Detail, a Bug Finder

Hi HN, tl;dr we built a bug finder that's working really well, especially for app backends. Try it out and send us your thoughts!<p>Long story below.<p>--------------------------<p>We originally set out to work on technical debt. We had all seen codebases with a lot of debt, so we had personal grudges about the problem, and AI seemed to be making it a lot worse.<p>Tech debt also seemed like a great problem for AI because: 1) a small portion of the work is thinky and strategic, and then the bulk of the execution is pretty mechanical, and 2) when you're solving technical debt, you're usually trying to preserve existing behavior, just change the implementation. That means you can treat it as a closed-loop problem if you figure out good ways to detect unintended behavior changes due to a code change. And we know how to do that – that's what tests are for!<p>So we started with writing tests. Tests create the guardrails that make future code changes safer. Our thinking was: if we can test well enough, we can automate a lot of other tech debt work at very high quality.<p>We built an agent that could write thousands of new tests for a typical codebase, most "merge-quality". Some early users merged hundreds of PRs generated this way, but intuitively the tool always felt "good but not great". We used it sporadically ourselves, and it usually felt like a chore.<p>Around this point we realized: while we had set out to write good tests, we had built a system that, with a few tweaks, might be very good at finding bugs. When we tested it out on some friends' codebases, we discovered that almost every repo has tons of bugs lurking in it that we were able to flag. Serious bugs, interesting enough that people dropped what they were doing to fix them. Sitting right there in peoples codebases, already merged, running in prod.<p>We also found a lot of vulns, even in mature codebases, and sometimes even right after someone had gotten a pentest.<p>Under the hood: - We check out a codebase and figure out how to build it for local dev and exercise it with tests. - We take snapshots of the built local dev state. (We use Runloop for this and are big fans.) - We spin up hundreds of copies of the local dev environment to exercise the codebase in thousands of ways and flag behaviors that seem wrong. - We pick the most salient, scary examples and deliver them as linear tickets, github issues, or emails.<p>In practice, it's working pretty well. We've been able to find bugs in everything from compilers to trading platforms (even in rust code), but the sweet spot is app backends.<p>Our approach trades compute for quality. Our codebase scans take hours, far beyond what would be practical for a code review bot. But the result is that we can make more judicious use of engineers’ attention, and we think that’s going to be the most important variable.<p>Longer term, we think compute is cheap, engineer attention is expensive. Wielded properly, the newest models can execute complicated changes, even in large codebases. That means the limiting reagent in building software is human attention. It still takes time and focus for an engineer to ingest information, e.g. existing code, organizational context, and product requirements. These are all necessary before an engineer can articulate what they want in precise terms and do a competent job reviewing the resulting diff.<p>For now we're finding bugs, but the techniques we're developing extend to a lot of other background, semi-proactive work to improve codebases.<p>Try it out and tell us what you think. Free first scan, no credit card required: <a href="https://detail.dev/" rel="nofollow">https://detail.dev/</a><p>We're also scanning on OSS repos, if you have any requests. The system is pretty high signal-to-noise, but we don't want to risk annoying maintainers by automatically opening issues, so if you request a scan for an OSS repo the results will go to you personally. <a href="https://detail.dev/oss" rel="nofollow">https://detail.dev/oss</a>

Show HN: AlgoDrill – Interactive drills to stop forgetting LeetCode patterns

I built AlgoDrill because I kept grinding LeetCode, thinking I knew the pattern, and then completely blanking when I had to implement it from scratch a few weeks later.<p>AlgoDrill turns NeetCode 150 and more into pattern-based drills: you rebuild the solution line by line with active recall, get first principles editorials that explain why each step exists, and everything is tagged by patterns like sliding window, two pointers, and DP so you can hammer the ones you keep forgetting. The goal is simple: turn familiar patterns into code you can write quickly and confidently in a real interview.<p><a href="https://algodrill.io" rel="nofollow">https://algodrill.io</a><p>Would love feedback on whether this drill-style approach feels like a real upgrade over just solving problems once, and what’s most confusing or missing when you first land on the site.

Show HN: AlgoDrill – Interactive drills to stop forgetting LeetCode patterns

I built AlgoDrill because I kept grinding LeetCode, thinking I knew the pattern, and then completely blanking when I had to implement it from scratch a few weeks later.<p>AlgoDrill turns NeetCode 150 and more into pattern-based drills: you rebuild the solution line by line with active recall, get first principles editorials that explain why each step exists, and everything is tagged by patterns like sliding window, two pointers, and DP so you can hammer the ones you keep forgetting. The goal is simple: turn familiar patterns into code you can write quickly and confidently in a real interview.<p><a href="https://algodrill.io" rel="nofollow">https://algodrill.io</a><p>Would love feedback on whether this drill-style approach feels like a real upgrade over just solving problems once, and what’s most confusing or missing when you first land on the site.

Show HN: AlgoDrill – Interactive drills to stop forgetting LeetCode patterns

I built AlgoDrill because I kept grinding LeetCode, thinking I knew the pattern, and then completely blanking when I had to implement it from scratch a few weeks later.<p>AlgoDrill turns NeetCode 150 and more into pattern-based drills: you rebuild the solution line by line with active recall, get first principles editorials that explain why each step exists, and everything is tagged by patterns like sliding window, two pointers, and DP so you can hammer the ones you keep forgetting. The goal is simple: turn familiar patterns into code you can write quickly and confidently in a real interview.<p><a href="https://algodrill.io" rel="nofollow">https://algodrill.io</a><p>Would love feedback on whether this drill-style approach feels like a real upgrade over just solving problems once, and what’s most confusing or missing when you first land on the site.

Show HN: I built a system for active note-taking in regular meetings like 1-1s

Hey HN! Like most here regular meetings have always been a big part of my work.<p>Over the years I've learned the value of active note taking in these meetings. Meaning: not minutes, not transcriptions or AI summaries, but <i>me</i> using my brain to actively pull out the key points in short form bullet-like notes, as the meeting is going on, as I'm talking and listening (and probably typing with one hand). This could be agenda points to cover, any interesting sidebars raised, insights gotten to in a discussion, actions agreed to (and a way to track whether they got done next time!).<p>It's both useful just to track what's going on in all these different meetings week to week (at one point I was doing about a dozen 1-1s per week, and it just becomes impossible to hold it in RAM) but also really valuable over time when you can look back and see the full history of a particular meeting, what was discussed when, how themes and structure are changing, is the meetings effective, etc.<p>Anyway, I've tried a bunch of different tools for taking these notes over the years. All the obvious ones you've probably used too. And I've always just been not <i>quite</i> satisfied with the experience. They work, obviously (it's just text based notes at the end of the day) but nothing is first-class for this usecase.<p>So, I decided to build the tool I've always felt I want to use, specifically for regular 1-1s and other types of regular meetings. I've been using it myself and with friends for a while already now, and I think it's got to that point where I actually prefer to reach for it over other general purpose note taking tools now, and I want to share it more widely.<p>There's a free tier so you can use it right away, in fact without even signing up.<p>If you've also been wanting a better system to manage your notes for regular meetings, give it a go and let me know what you think!

Show HN: I built a system for active note-taking in regular meetings like 1-1s

Hey HN! Like most here regular meetings have always been a big part of my work.<p>Over the years I've learned the value of active note taking in these meetings. Meaning: not minutes, not transcriptions or AI summaries, but <i>me</i> using my brain to actively pull out the key points in short form bullet-like notes, as the meeting is going on, as I'm talking and listening (and probably typing with one hand). This could be agenda points to cover, any interesting sidebars raised, insights gotten to in a discussion, actions agreed to (and a way to track whether they got done next time!).<p>It's both useful just to track what's going on in all these different meetings week to week (at one point I was doing about a dozen 1-1s per week, and it just becomes impossible to hold it in RAM) but also really valuable over time when you can look back and see the full history of a particular meeting, what was discussed when, how themes and structure are changing, is the meetings effective, etc.<p>Anyway, I've tried a bunch of different tools for taking these notes over the years. All the obvious ones you've probably used too. And I've always just been not <i>quite</i> satisfied with the experience. They work, obviously (it's just text based notes at the end of the day) but nothing is first-class for this usecase.<p>So, I decided to build the tool I've always felt I want to use, specifically for regular 1-1s and other types of regular meetings. I've been using it myself and with friends for a while already now, and I think it's got to that point where I actually prefer to reach for it over other general purpose note taking tools now, and I want to share it more widely.<p>There's a free tier so you can use it right away, in fact without even signing up.<p>If you've also been wanting a better system to manage your notes for regular meetings, give it a go and let me know what you think!

Show HN: I built a system for active note-taking in regular meetings like 1-1s

Hey HN! Like most here regular meetings have always been a big part of my work.<p>Over the years I've learned the value of active note taking in these meetings. Meaning: not minutes, not transcriptions or AI summaries, but <i>me</i> using my brain to actively pull out the key points in short form bullet-like notes, as the meeting is going on, as I'm talking and listening (and probably typing with one hand). This could be agenda points to cover, any interesting sidebars raised, insights gotten to in a discussion, actions agreed to (and a way to track whether they got done next time!).<p>It's both useful just to track what's going on in all these different meetings week to week (at one point I was doing about a dozen 1-1s per week, and it just becomes impossible to hold it in RAM) but also really valuable over time when you can look back and see the full history of a particular meeting, what was discussed when, how themes and structure are changing, is the meetings effective, etc.<p>Anyway, I've tried a bunch of different tools for taking these notes over the years. All the obvious ones you've probably used too. And I've always just been not <i>quite</i> satisfied with the experience. They work, obviously (it's just text based notes at the end of the day) but nothing is first-class for this usecase.<p>So, I decided to build the tool I've always felt I want to use, specifically for regular 1-1s and other types of regular meetings. I've been using it myself and with friends for a while already now, and I think it's got to that point where I actually prefer to reach for it over other general purpose note taking tools now, and I want to share it more widely.<p>There's a free tier so you can use it right away, in fact without even signing up.<p>If you've also been wanting a better system to manage your notes for regular meetings, give it a go and let me know what you think!

Show HN: Gemini Pro 3 imagines the HN front page 10 years from now

Show HN: Gemini Pro 3 imagines the HN front page 10 years from now

Show HN: Gemini Pro 3 imagines the HN front page 10 years from now

Show HN: Gemini Pro 3 imagines the HN front page 10 years from now

Show HN: Cdecl-dump - represent C declarations visually

A small tool that parses C declarations and outputs a simple visual representation at each stage, as it encounters arrays, pointers or functions.<p>The program uses a table-driven lexer and a hand-written, shift-reduce parser. No external dependencies apart from the standard library.

Show HN: Cdecl-dump - represent C declarations visually

A small tool that parses C declarations and outputs a simple visual representation at each stage, as it encounters arrays, pointers or functions.<p>The program uses a table-driven lexer and a hand-written, shift-reduce parser. No external dependencies apart from the standard library.

Show HN: Web app that lets you send email time capsules

I had an issue where I would journal stuff, and then never look at what I wrote. So I thought it'll be cool to schedule something that will get sent to you at a later time (like a time capsule). Also, was inspired by futureme, where you can send yourself letters that'll arrive in the future.

Show HN: DuckDB for Kafka Stream Processing

Hello Everyone! We built SQLFlow as a lightweight stream processing engine.<p>We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory!<p>DuckDB also supports a rich ecosystem of sinks and connectors!<p><a href="https://sql-flow.com/docs/category/tutorials/" rel="nofollow">https://sql-flow.com/docs/category/tutorials/</a><p><a href="https://github.com/turbolytics/sql-flow" rel="nofollow">https://github.com/turbolytics/sql-flow</a><p>We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors<p>I would love your feedback, criticisms and/or experiences!<p>Thank you

Show HN: DuckDB for Kafka Stream Processing

Hello Everyone! We built SQLFlow as a lightweight stream processing engine.<p>We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory!<p>DuckDB also supports a rich ecosystem of sinks and connectors!<p><a href="https://sql-flow.com/docs/category/tutorials/" rel="nofollow">https://sql-flow.com/docs/category/tutorials/</a><p><a href="https://github.com/turbolytics/sql-flow" rel="nofollow">https://github.com/turbolytics/sql-flow</a><p>We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors<p>I would love your feedback, criticisms and/or experiences!<p>Thank you

Show HN: DuckDB for Kafka Stream Processing

Hello Everyone! We built SQLFlow as a lightweight stream processing engine.<p>We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory!<p>DuckDB also supports a rich ecosystem of sinks and connectors!<p><a href="https://sql-flow.com/docs/category/tutorials/" rel="nofollow">https://sql-flow.com/docs/category/tutorials/</a><p><a href="https://github.com/turbolytics/sql-flow" rel="nofollow">https://github.com/turbolytics/sql-flow</a><p>We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors<p>I would love your feedback, criticisms and/or experiences!<p>Thank you

Show HN: Lockenv – Simple encrypted secrets storage for Git

Hi!<p>I got tired of setting up tools I can't explain to a team in a few words like sops or git-crypt, just to store few files with environment variables or secrets, so I built lockenv as a simple alternative.<p>It's basically a password-protected vault file you commit to git. No gpg keys, no cloud, just lockenv init, set a password, and lock/unlock the secrets.<p>This tool integrates with OS keyring, so you're not typing passwords constantly. Should work on Mac/Linux/Windows, but I tested it only on linux so far.<p>I am not trying to replace any mature / robust solution, just making small tool for simple cases, where I want to stop sharing secrets via slack.<p>Feel free to try, thank you!

Show HN: Lockenv – Simple encrypted secrets storage for Git

Hi!<p>I got tired of setting up tools I can't explain to a team in a few words like sops or git-crypt, just to store few files with environment variables or secrets, so I built lockenv as a simple alternative.<p>It's basically a password-protected vault file you commit to git. No gpg keys, no cloud, just lockenv init, set a password, and lock/unlock the secrets.<p>This tool integrates with OS keyring, so you're not typing passwords constantly. Should work on Mac/Linux/Windows, but I tested it only on linux so far.<p>I am not trying to replace any mature / robust solution, just making small tool for simple cases, where I want to stop sharing secrets via slack.<p>Feel free to try, thank you!