Show HN: CTON: JSON-compatible, token-efficient text format for LLM prompts
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Show HN: DB Pro – A Modern Desktop Client for Postgres, MySQL, SQLite and LibSQL
Show HN: DB Pro – A Modern Desktop Client for Postgres, MySQL, SQLite and LibSQL Hi HN,<p>Over the past few months I've been building DB Pro with my co-founder. DB Pro is a modern desktop database GUI client designed to make working with Postgres, MySQL, SQLite, libSQL and other engines feel fast, visual, and enjoyable.<p>Our focus has been on the dev-experience. We wanted to absolutely nail the UX and look and feel as we believe most db clients aren't friendly to work with.<p>Some features:<p>Visual change review – See pending inserts/updates/deletes before committing them.<p>Inline data editing – Edit table rows directly without clunky modal dialogs.<p>Raw SQL editor – A focused editor for running queries with results in separate tabs.<p>Full activity logs – Track everything happening in your database for peace of mind.<p>Visual schema explorer – See tables, columns, keys, and relationships in a diagram.<p>Tabs & multi-window support – Keep multiple connections and queries open at once.<p>Custom table tagging – Organise your tables without altering the schema.<p>Tech stack: Electron, React, tRPC, Drizzle ORM, Postgres/MySQL/libSQL/SQLite support, and native builds for macOS at the moment with Windows, and Linux coming very soon.<p>We're super passionate about this project and we're actually documenting our journey through devlogs. The latest one is here: <a href="https://www.youtube.com/watch?v=-T4GcJuV1rM" rel="nofollow">https://www.youtube.com/watch?v=-T4GcJuV1rM</a><p>Thanks, Jay and Jack
Show HN: Superglue – OSS integration tool that understands your legacy systems
Show HN: Superglue – OSS integration tool that understands your legacy systems If you've ever worked in a large company, you've probably encountered "shadow infrastructure": scripts nobody understands or custom connectors written once and never touched again. This glue layer isn't documented, isn't owned by anyone, and tends to break when systems are upgraded or someone leaves. It's also the part everybody dreads working on, because it's hard to understand, painful to work with, and full of unknown unknowns.<p>We built superglue so that engineers stop wasting time on deciphering legacy APIs and documentation.<p>superglue ingests existing glue code, SQL, configs, docs, OpenAPI specs and reverse-engineers what the system is actually doing. It then maps dependencies and regenerates everything as clean javascript code that can run directly or be exposed via MCP or SDK. It also monitors API changes and schema drift, and automatically repairs integrations when upstream systems change.<p>In short: It turns legacy integrations into code you can easily understand, test, and update. So that engineers can do more exciting feature work, and companies can migrate and upgrade systems faster.<p>Think of it as: a context engine + code generator + integration runtime for legacy glue.<p>What we'd love feedback on<p>- How do you deal with "nobody knows what this script does" situations?<p>- What would you want to know about your legacy systems?<p>OSS/community version: <a href="https://github.com/superglue-ai/superglue" rel="nofollow">https://github.com/superglue-ai/superglue</a><p>More info: <a href="https://superglue.ai">https://superglue.ai</a><p>Happy to go deeper on the technical details.
Show HN: Axe - A Systems Programming Language with Builtin Parallelism and No GC
Show HN: Axe - A Systems Programming Language with Builtin Parallelism and No GC I'm writing a compiler for a systems language focused on concurrency and parallelism. It’s a re-engineering of a prior work, with an explicit emphasis on memory management and type safety, plus first-class parallel primitives at the language level.<p>The language is now capable of compiling a substantial portion of its own source code to tokens using a single-pass C back-end. The self-hosted compiler includes a handwritten lexer and a parser, with an arena-based allocator to support fast compilation and eliminate GC complexity.<p>The primary goals for the project are: First-class parallel and concurrent constructs built directly into the language, strong static memory and type guarantees, and a toolchain suitable for building high-performance software<p>Example:<p><pre><code> def main() { parallel local(mut arena: Arena) { arena = Arena.create(1024); val tid = Parallel.thread_id(); val result = worker(ref_of(arena), tid); println $"Thread {tid} computed {result}"; Arena.destroy(ref_of(arena)); } } </code></pre> You can find the repository here: <a href="https://github.com/axelang/axe" rel="nofollow">https://github.com/axelang/axe</a>
Show HN: 13Radar – Real-Time Hedge Fund Portfolio Analytics
Show HN: 13Radar – Real-Time Hedge Fund Portfolio Analytics Hi HN,<p>We’re a small team working on 13Radar.com, which we launched about two weeks ago after 4 months of development. I’m the founder, and together with the team we’re building a platform that tracks hedge fund portfolios in real-time based on SEC Form 13F filings.<p>AI has been a major helper in our workflow. For a single webpage, we often consult multiple AI systems in parallel, generating different versions and comparing them side by side before deciding on the final design or implementation. More than 60% of the research, design, and coding involved AI assistance. For UI design we used Readdy, which gave us a smooth design experience. We experimented with Google Gemini and ChatGPT for research and prototyping, while most of the coding was done with Claude Code (Trae). On the front-end, we started with Bootstrap but later switched to TailwindCSS for a lighter, more responsive framework.<p>Features so far:<p>Real-time tracking of hedge fund holdings from SEC 13F filings<p>Portfolio changes per quarter (new positions, increases, reductions, exits)<p>Sector-level insights and trend analysis<p>Historical tracking and backtesting tools<p>Next steps:<p>Implementing pricing and subscription features<p>Adding email notifications and report export<p>Expanding analytics with insider transaction data<p>Continuing to refine usability and performance<p>We’d love feedback from the community:<p>Does this solve a real pain point for investors/researchers<p>Any thoughts on improving positioning or usability<p>Suggestions for features that would make this more useful<p>Thanks for reading — and if you’re curious, feel free to check out the site and let us know what you think.
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