Audio
🔊 Turn AI Coding Chats Into Shareable Training Data
📦 peteromallet/dataclaw
DataClaw is a small command-line tool that converts your Claude Code chat history into a clean, structured dataset and can publish it to Hugging Face (a popular place to host machine-learning datasets). It solves a messy, risky process: raw chat logs are hard to organize and may contain private details like usernames, emails, file paths, or secret keys. DataClaw helps by formatting the conversations, adding useful metadata, and applying redaction steps before export, with a review step before anything is uploaded. This makes it easier for developers to safely reuse their AI-assisted coding sessions for research, analysis, or improving future coding models.
🔗 https://github.com/peteromallet/dataclaw
📰 https://news.ycombinator.com/item?id=47147604
📢 @hackernewsgithubprojects
📦 peteromallet/dataclaw
DataClaw is a small command-line tool that converts your Claude Code chat history into a clean, structured dataset and can publish it to Hugging Face (a popular place to host machine-learning datasets). It solves a messy, risky process: raw chat logs are hard to organize and may contain private details like usernames, emails, file paths, or secret keys. DataClaw helps by formatting the conversations, adding useful metadata, and applying redaction steps before export, with a review step before anything is uploaded. This makes it easier for developers to safely reuse their AI-assisted coding sessions for research, analysis, or improving future coding models.
🔗 https://github.com/peteromallet/dataclaw
📰 https://news.ycombinator.com/item?id=47147604
📢 @hackernewsgithubprojects
Audio
🔊 Claude Context Mode Stops AI Output Overload
📦 mksglu/claude-context-mode
Claude Context Mode is an add-on for Claude Code that shrinks large tool outputs before they fill up the AI’s limited memory space (its context window). Instead of dumping long logs, web pages, test results, or issue lists straight into the chat, it runs them in a sandbox, keeps the raw data outside the conversation, and returns compact summaries or searchable snippets. It can also index documents and fetched web pages so you can pull only the relevant parts later. This makes longer coding sessions stay useful for more time, reduces wasted context, and helps with research, debugging, and multi-step tasks.
🔗 https://github.com/mksglu/claude-context-mode
📰 https://news.ycombinator.com/item?id=47148025
📢 @hackernewsgithubprojects
📦 mksglu/claude-context-mode
Claude Context Mode is an add-on for Claude Code that shrinks large tool outputs before they fill up the AI’s limited memory space (its context window). Instead of dumping long logs, web pages, test results, or issue lists straight into the chat, it runs them in a sandbox, keeps the raw data outside the conversation, and returns compact summaries or searchable snippets. It can also index documents and fetched web pages so you can pull only the relevant parts later. This makes longer coding sessions stay useful for more time, reduces wasted context, and helps with research, debugging, and multi-step tasks.
🔗 https://github.com/mksglu/claude-context-mode
📰 https://news.ycombinator.com/item?id=47148025
📢 @hackernewsgithubprojects
Audio
🔊 Where AI Builds and Humans Stay in Charge
📦 chorus-aidlc/chorus
Chorus is an open-source workspace that helps people and AI agents build software together in a controlled way. It organizes work from idea to plan, coding, review, and completion, while showing who (human or AI) is doing what in real time through boards, task maps, and activity logs. The platform follows a simple rule: AI proposes and works, but humans approve and verify the results. This solves a common problem with AI-assisted development: gaining speed without losing visibility or accountability. Chorus is useful for teams that want faster delivery from AI tools while keeping clear oversight, coordination, and a reliable record of decisions and progress.
🔗 https://github.com/Chorus-AIDLC/Chorus
📰 https://news.ycombinator.com/item?id=47148537
📢 @hackernewsgithubprojects
📦 chorus-aidlc/chorus
Chorus is an open-source workspace that helps people and AI agents build software together in a controlled way. It organizes work from idea to plan, coding, review, and completion, while showing who (human or AI) is doing what in real time through boards, task maps, and activity logs. The platform follows a simple rule: AI proposes and works, but humans approve and verify the results. This solves a common problem with AI-assisted development: gaining speed without losing visibility or accountability. Chorus is useful for teams that want faster delivery from AI tools while keeping clear oversight, coordination, and a reliable record of decisions and progress.
🔗 https://github.com/Chorus-AIDLC/Chorus
📰 https://news.ycombinator.com/item?id=47148537
📢 @hackernewsgithubprojects
Audio
🔊 Doom, Powered by a Database
📦 dreamnik/pg_doom
pg_doom is a playful project that runs the classic game Doom inside PostgreSQL, a popular database system. It combines a custom PostgreSQL extension with a small terminal script: the script sends your key presses into the database, and SQL functions send back the next game frame as text to draw on screen. It solves a fun but real engineering challenge by showing how database extensions can handle much more than storing data. That makes it useful as a hands-on learning example for PostgreSQL extension building, low-level input/output ideas, and system integration, while also being a memorable demo you can try with Docker and a legally obtained Doom data file.
🔗 https://github.com/DreamNik/pg_doom
📰 https://news.ycombinator.com/item?id=47148609
📢 @hackernewsgithubprojects
📦 dreamnik/pg_doom
pg_doom is a playful project that runs the classic game Doom inside PostgreSQL, a popular database system. It combines a custom PostgreSQL extension with a small terminal script: the script sends your key presses into the database, and SQL functions send back the next game frame as text to draw on screen. It solves a fun but real engineering challenge by showing how database extensions can handle much more than storing data. That makes it useful as a hands-on learning example for PostgreSQL extension building, low-level input/output ideas, and system integration, while also being a memorable demo you can try with Docker and a legally obtained Doom data file.
🔗 https://github.com/DreamNik/pg_doom
📰 https://news.ycombinator.com/item?id=47148609
📢 @hackernewsgithubprojects
Audio
🔊 Claude Code: An AI Coding Helper That Works in Your Terminal
📦 anthropics/claude-code
`claude-code` is the open-source repository behind Claude Code, a command-line assistant that helps people build and maintain software by understanding plain-English requests. Instead of manually hunting through files, writing repetitive edits, or running many commands yourself, you can ask it to inspect a project, explain code, make changes, and automate common development tasks. It solves the problem of slow, fragmented coding workflows by combining guidance and execution in one place. This is useful because it can save time, reduce mistakes, and help both experienced developers and learners move through larger codebases more confidently.
🔗 https://github.com/anthropics/claude-code
📰 https://news.ycombinator.com/item?id=47149042
📢 @hackernewsgithubprojects
📦 anthropics/claude-code
`claude-code` is the open-source repository behind Claude Code, a command-line assistant that helps people build and maintain software by understanding plain-English requests. Instead of manually hunting through files, writing repetitive edits, or running many commands yourself, you can ask it to inspect a project, explain code, make changes, and automate common development tasks. It solves the problem of slow, fragmented coding workflows by combining guidance and execution in one place. This is useful because it can save time, reduce mistakes, and help both experienced developers and learners move through larger codebases more confidently.
🔗 https://github.com/anthropics/claude-code
📰 https://news.ycombinator.com/item?id=47149042
📢 @hackernewsgithubprojects
Audio
🔊 Guitar Pedal Effects, but in Code
📦 torvalds/audionoise
AudioNoise is a small open-source project from Linus Torvalds that applies guitar-pedal-style effects to audio files in software, including echo, flanger, phaser, distortion, and simple modulation effects. Instead of building or wiring physical pedals, it lets people experiment with sound digitally and hear results quickly. The code is intentionally simple and focused on basics, so it helps beginners understand how digital audio effects work without needing expensive gear or advanced math tools. It also includes a visualizer script for viewing waveforms. That makes it useful as a hands-on learning sandbox, a demo of real-time audio ideas, and a starting point for hobby audio projects.
🔗 https://github.com/torvalds/AudioNoise
📰 https://news.ycombinator.com/item?id=47149252
📢 @hackernewsgithubprojects
📦 torvalds/audionoise
AudioNoise is a small open-source project from Linus Torvalds that applies guitar-pedal-style effects to audio files in software, including echo, flanger, phaser, distortion, and simple modulation effects. Instead of building or wiring physical pedals, it lets people experiment with sound digitally and hear results quickly. The code is intentionally simple and focused on basics, so it helps beginners understand how digital audio effects work without needing expensive gear or advanced math tools. It also includes a visualizer script for viewing waveforms. That makes it useful as a hands-on learning sandbox, a demo of real-time audio ideas, and a starting point for hobby audio projects.
🔗 https://github.com/torvalds/AudioNoise
📰 https://news.ycombinator.com/item?id=47149252
📢 @hackernewsgithubprojects
Audio
🔊 Common Lisp, Now With Guardrails
📦 coalton-lang/coalton
Coalton is an open-source programming language project that plugs into Common Lisp and adds stronger error checking before code runs. In simple terms, it lets developers keep Lisp’s fast, interactive workflow while getting earlier warnings about mismatched data and function inputs that can otherwise hide until testing or production. This repository contains the Coalton compiler, standard library, examples, and documentation. It is useful for teams building complex software in Lisp because it can reduce avoidable bugs, make code easier to understand, and support larger projects without forcing a rewrite into a completely different language.
🔗 https://github.com/coalton-lang/coalton
📰 https://news.ycombinator.com/item?id=47149590
📢 @hackernewsgithubprojects
📦 coalton-lang/coalton
Coalton is an open-source programming language project that plugs into Common Lisp and adds stronger error checking before code runs. In simple terms, it lets developers keep Lisp’s fast, interactive workflow while getting earlier warnings about mismatched data and function inputs that can otherwise hide until testing or production. This repository contains the Coalton compiler, standard library, examples, and documentation. It is useful for teams building complex software in Lisp because it can reduce avoidable bugs, make code easier to understand, and support larger projects without forcing a rewrite into a completely different language.
🔗 https://github.com/coalton-lang/coalton
📰 https://news.ycombinator.com/item?id=47149590
📢 @hackernewsgithubprojects
Audio
🔊 Your Project, Finally in One Visual Space
📦 3xpyth0n/ideon
Ideon is an open-source, self-hosted workspace that puts the important parts of a project on one visual canvas. Instead of hunting through folders, chats, bookmarks, and docs, teams can place repositories, notes, links, files, and people as simple cards and see how everything connects. It solves a common problem: when project context gets scattered, people waste time rebuilding their understanding before they can do real work. Ideon makes that shared context visible, easier to revisit, and easier to discuss. Features like real-time collaboration, snapshots, and quick paste-to-card tools help teams stay aligned and pick up where they left off faster.
🔗 https://github.com/3xpyth0n/ideon
📰 https://news.ycombinator.com/item?id=47149766
📢 @hackernewsgithubprojects
📦 3xpyth0n/ideon
Ideon is an open-source, self-hosted workspace that puts the important parts of a project on one visual canvas. Instead of hunting through folders, chats, bookmarks, and docs, teams can place repositories, notes, links, files, and people as simple cards and see how everything connects. It solves a common problem: when project context gets scattered, people waste time rebuilding their understanding before they can do real work. Ideon makes that shared context visible, easier to revisit, and easier to discuss. Features like real-time collaboration, snapshots, and quick paste-to-card tools help teams stay aligned and pick up where they left off faster.
🔗 https://github.com/3xpyth0n/ideon
📰 https://news.ycombinator.com/item?id=47149766
📢 @hackernewsgithubprojects
Audio
🔊 Next.js, Rebuilt for Faster Cloudflare Deploys
📦 cloudflare/vinext
vinext is an open-source Cloudflare project that lets developers run many existing Next.js websites on Vite (a faster app build tool) and deploy them to Cloudflare Workers (Cloudflare’s serverless hosting platform). It solves a common problem: taking a Next.js app to a different hosting setup can be complicated, slow, or brittle. vinext adds tools to check compatibility, help migrate projects, build the app, and deploy it, while preserving most existing project files and structure. That makes it useful for teams who want faster development, easier moves to Cloudflare, and less rework. It is experimental, so users should expect some rough edges.
🔗 https://github.com/cloudflare/vinext
📰 https://news.ycombinator.com/item?id=47149811
📢 @hackernewsgithubprojects
📦 cloudflare/vinext
vinext is an open-source Cloudflare project that lets developers run many existing Next.js websites on Vite (a faster app build tool) and deploy them to Cloudflare Workers (Cloudflare’s serverless hosting platform). It solves a common problem: taking a Next.js app to a different hosting setup can be complicated, slow, or brittle. vinext adds tools to check compatibility, help migrate projects, build the app, and deploy it, while preserving most existing project files and structure. That makes it useful for teams who want faster development, easier moves to Cloudflare, and less rework. It is experimental, so users should expect some rough edges.
🔗 https://github.com/cloudflare/vinext
📰 https://news.ycombinator.com/item?id=47149811
📢 @hackernewsgithubprojects
Audio
🔊 A Safer Sandbox for AI-Generated Code
📦 earendil-works/gondolin
Gondolin is an open-source tool that lets developers run AI-generated or untrusted code inside a small local virtual machine instead of directly on their computer. It solves a growing safety problem: agents often need internet access and secrets like API keys, but giving them full access can leak data or damage files. Gondolin keeps the risky code isolated while the host machine enforces clear rules for network calls, file access, and secret use. It also includes a CLI and SDK for creating sessions, snapshots, and controlled connections. This makes experimentation faster and safer for people building AI-powered workflows.
🔗 https://github.com/earendil-works/gondolin
📰 https://news.ycombinator.com/item?id=47150817
📢 @hackernewsgithubprojects
📦 earendil-works/gondolin
Gondolin is an open-source tool that lets developers run AI-generated or untrusted code inside a small local virtual machine instead of directly on their computer. It solves a growing safety problem: agents often need internet access and secrets like API keys, but giving them full access can leak data or damage files. Gondolin keeps the risky code isolated while the host machine enforces clear rules for network calls, file access, and secret use. It also includes a CLI and SDK for creating sessions, snapshots, and controlled connections. This makes experimentation faster and safer for people building AI-powered workflows.
🔗 https://github.com/earendil-works/gondolin
📰 https://news.ycombinator.com/item?id=47150817
📢 @hackernewsgithubprojects
Audio
🔊 Minesweeper, Rebuilt for Speed
📦 oug-t/zsweep
zsweep is an open-source, browser-based version of Minesweeper that updates the classic puzzle game for modern players. Instead of the old, clunky interfaces many clones use, it offers a cleaner design, quick keyboard controls, and modes for both regular games and timed play. It solves a common problem for fans of Minesweeper: finding a version that feels polished and helps you improve. zsweep includes useful features like performance stats, play history, and saved scores (with optional online storage), making it great for casual players, competitive speed players, or anyone who wants a smoother, more enjoyable way to play a familiar game.
🔗 https://github.com/oug-t/zsweep
📰 https://news.ycombinator.com/item?id=47150901
📢 @hackernewsgithubprojects
📦 oug-t/zsweep
zsweep is an open-source, browser-based version of Minesweeper that updates the classic puzzle game for modern players. Instead of the old, clunky interfaces many clones use, it offers a cleaner design, quick keyboard controls, and modes for both regular games and timed play. It solves a common problem for fans of Minesweeper: finding a version that feels polished and helps you improve. zsweep includes useful features like performance stats, play history, and saved scores (with optional online storage), making it great for casual players, competitive speed players, or anyone who wants a smoother, more enjoyable way to play a familiar game.
🔗 https://github.com/oug-t/zsweep
📰 https://news.ycombinator.com/item?id=47150901
📢 @hackernewsgithubprojects
Audio
🔊 PHP’s Race to Crunch 100 Million Rows
📦 tempestphp/100-million-row-challenge
This repository is a programming challenge for PHP developers: take a huge file with 100 million website visit records and write code that quickly turns it into a summary report (users, pages, and top visitors). It solves a practical problem many teams face when working with very large datasets: how to process lots of information fast without running out of time or memory. The repo provides the dataset format, rules, a starter project, and a leaderboard so people can compare results. It is useful as a learning tool, a benchmark for PHP performance, and a fun way to practice writing efficient data-processing code.
🔗 https://github.com/tempestphp/100-million-row-challenge
📰 https://news.ycombinator.com/item?id=47149752
📢 @hackernewsgithubprojects
📦 tempestphp/100-million-row-challenge
This repository is a programming challenge for PHP developers: take a huge file with 100 million website visit records and write code that quickly turns it into a summary report (users, pages, and top visitors). It solves a practical problem many teams face when working with very large datasets: how to process lots of information fast without running out of time or memory. The repo provides the dataset format, rules, a starter project, and a leaderboard so people can compare results. It is useful as a learning tool, a benchmark for PHP performance, and a fun way to practice writing efficient data-processing code.
🔗 https://github.com/tempestphp/100-million-row-challenge
📰 https://news.ycombinator.com/item?id=47149752
📢 @hackernewsgithubprojects
Audio
🔊 AI Memory That Learns From Mistakes
📦 alibaizhanov/mengram
Mengram is an open-source toolkit and cloud API that gives AI assistants a better memory. Instead of only saving facts, it can also store past events and step-by-step routines, then improve those routines when a task fails. This solves a common problem with AI agents: they forget user preferences, repeat mistakes, and lose context between conversations. Developers can connect it to Python, JavaScript, or API-based apps, import old chats or notes, and generate a profile that personalizes future responses. In plain terms, it helps AI tools remember what matters, learn from experience, and become more useful over time.
🔗 https://github.com/alibaizhanov/mengram
📰 https://news.ycombinator.com/item?id=47151177
📢 @hackernewsgithubprojects
📦 alibaizhanov/mengram
Mengram is an open-source toolkit and cloud API that gives AI assistants a better memory. Instead of only saving facts, it can also store past events and step-by-step routines, then improve those routines when a task fails. This solves a common problem with AI agents: they forget user preferences, repeat mistakes, and lose context between conversations. Developers can connect it to Python, JavaScript, or API-based apps, import old chats or notes, and generate a profile that personalizes future responses. In plain terms, it helps AI tools remember what matters, learn from experience, and become more useful over time.
🔗 https://github.com/alibaizhanov/mengram
📰 https://news.ycombinator.com/item?id=47151177
📢 @hackernewsgithubprojects
Audio
🔊 Build a Whiteboard Without Starting From Zero
📦 tldraw/tldraw
tldraw is an open-source toolkit for building online whiteboards and “infinite canvas” drawing spaces used for brainstorming, diagrams, and collaborative planning. Instead of building drawing tools, shapes, zooming, undo/redo, and live collaboration from scratch, developers can add tldraw to a web app and customize the experience. It powers the tldraw whiteboard app itself, so it is both a real product and a reusable foundation. The main benefit is speed and reliability: teams can launch visual editing features much faster, avoid many hard-to-build canvas details, and start from a polished base rather than reinventing everything.
🔗 https://github.com/tldraw/tldraw
📰 https://news.ycombinator.com/item?id=47151545
📢 @hackernewsgithubprojects
📦 tldraw/tldraw
tldraw is an open-source toolkit for building online whiteboards and “infinite canvas” drawing spaces used for brainstorming, diagrams, and collaborative planning. Instead of building drawing tools, shapes, zooming, undo/redo, and live collaboration from scratch, developers can add tldraw to a web app and customize the experience. It powers the tldraw whiteboard app itself, so it is both a real product and a reusable foundation. The main benefit is speed and reliability: teams can launch visual editing features much faster, avoid many hard-to-build canvas details, and start from a polished base rather than reinventing everything.
🔗 https://github.com/tldraw/tldraw
📰 https://news.ycombinator.com/item?id=47151545
📢 @hackernewsgithubprojects
Audio
🔊 Can Your AI Call Out Nonsense?
📦 petergpt/bullshit-benchmark
This repository is a benchmark for testing whether AI chatbots can recognize nonsense questions and push back instead of confidently making things up. It provides a curated set of intentionally bogus prompts (like mixing unrelated business, science, or technical terms), scripts to run many models against them, and a scoring system that grades whether each model clearly challenges the bad premise. The results can be published into a simple viewer and leaderboard for side-by-side comparison. It solves a real trust problem: models often sound helpful even when a question is incoherent. That makes this project useful for evaluating model reliability, safety tuning, and product choices.
🔗 https://github.com/petergpt/bullshit-benchmark
📰 https://news.ycombinator.com/item?id=47151505
📢 @hackernewsgithubprojects
📦 petergpt/bullshit-benchmark
This repository is a benchmark for testing whether AI chatbots can recognize nonsense questions and push back instead of confidently making things up. It provides a curated set of intentionally bogus prompts (like mixing unrelated business, science, or technical terms), scripts to run many models against them, and a scoring system that grades whether each model clearly challenges the bad premise. The results can be published into a simple viewer and leaderboard for side-by-side comparison. It solves a real trust problem: models often sound helpful even when a question is incoherent. That makes this project useful for evaluating model reliability, safety tuning, and product choices.
🔗 https://github.com/petergpt/bullshit-benchmark
📰 https://news.ycombinator.com/item?id=47151505
📢 @hackernewsgithubprojects
Audio
🔊 Turn Your Browser Into an AI-Powered Automation Assistant
📦 browserwing/browserwing
BrowserWing is an app and toolkit that helps people automate Chrome/Chromium through a local web interface, simple APIs, or AI assistants. Instead of repeating the same clicks, page visits, form filling, or data collection by hand, you can record a browser workflow once and replay it later. It also supports conversational commands and structured data extraction, which lowers the barrier for people who do not want to write much code. This is useful for repetitive research, website testing, page monitoring, and routine business tasks because it combines visual recording, browser control, and reusable integrations in one place.
🔗 https://github.com/browserwing/browserwing
📰 https://news.ycombinator.com/item?id=47151607
📢 @hackernewsgithubprojects
📦 browserwing/browserwing
BrowserWing is an app and toolkit that helps people automate Chrome/Chromium through a local web interface, simple APIs, or AI assistants. Instead of repeating the same clicks, page visits, form filling, or data collection by hand, you can record a browser workflow once and replay it later. It also supports conversational commands and structured data extraction, which lowers the barrier for people who do not want to write much code. This is useful for repetitive research, website testing, page monitoring, and routine business tasks because it combines visual recording, browser control, and reusable integrations in one place.
🔗 https://github.com/browserwing/browserwing
📰 https://news.ycombinator.com/item?id=47151607
📢 @hackernewsgithubprojects
Audio
🔊 AI Helpers for Airflow, in One Toolkit
📦 astronomer/agents
Astronomer’s agents repository is an open-source toolkit that adds practical AI help to data engineering work, especially for Apache Airflow (a popular system for scheduling data jobs). It combines ready-made “skills” for coding assistants, an Airflow connector/server, and a simple terminal tool so people can inspect pipelines, trigger runs, check logs, and work with data warehouses without jumping across many tools. The main problem it solves is setup friction: AI assistants often lack the right context or safe ways to interact with data systems. This repo gives them structured access and repeatable workflows, which makes debugging, building, and maintaining data pipelines faster and easier.
🔗 https://github.com/astronomer/agents
📰 https://news.ycombinator.com/item?id=47151588
📢 @hackernewsgithubprojects
📦 astronomer/agents
Astronomer’s agents repository is an open-source toolkit that adds practical AI help to data engineering work, especially for Apache Airflow (a popular system for scheduling data jobs). It combines ready-made “skills” for coding assistants, an Airflow connector/server, and a simple terminal tool so people can inspect pipelines, trigger runs, check logs, and work with data warehouses without jumping across many tools. The main problem it solves is setup friction: AI assistants often lack the right context or safe ways to interact with data systems. This repo gives them structured access and repeatable workflows, which makes debugging, building, and maintaining data pipelines faster and easier.
🔗 https://github.com/astronomer/agents
📰 https://news.ycombinator.com/item?id=47151588
📢 @hackernewsgithubprojects
Audio
🔊 One Dashboard to Run Your Django App
📦 yassi/dj-control-room
Django Control Room is an open-source add-on for Django (a popular Python web framework) that creates a single “control room” inside the site’s admin area. Instead of jumping between separate tools to check things like cache data, Redis, background jobs, or URL routes, teams can use one dashboard and add panels for the tasks they need. It solves the problem of scattered admin and maintenance tools, which can slow down troubleshooting and routine operations. The plug-in approach also makes it flexible: you can start with a few panels and expand later. It’s useful because it saves time, improves visibility, and reduces custom admin work.
🔗 https://github.com/yassi/dj-control-room
📰 https://news.ycombinator.com/item?id=47151995
📢 @hackernewsgithubprojects
📦 yassi/dj-control-room
Django Control Room is an open-source add-on for Django (a popular Python web framework) that creates a single “control room” inside the site’s admin area. Instead of jumping between separate tools to check things like cache data, Redis, background jobs, or URL routes, teams can use one dashboard and add panels for the tasks they need. It solves the problem of scattered admin and maintenance tools, which can slow down troubleshooting and routine operations. The plug-in approach also makes it flexible: you can start with a few panels and expand later. It’s useful because it saves time, improves visibility, and reduces custom admin work.
🔗 https://github.com/yassi/dj-control-room
📰 https://news.ycombinator.com/item?id=47151995
📢 @hackernewsgithubprojects
Audio
🔊 Build Your Own AI Workflow Engine
📦 strongdm/attractor
Attractor is a blueprint repository that explains how to build an AI-powered workflow system and coding assistant loop, rather than a finished app you install and run. It focuses on describing the architecture, data formats, and execution flow for complex tasks that need multiple steps, decisions, and retries. The problem it solves is the mess of one-off scripts and hard-to-maintain automation when teams try to connect AI tools together. By providing clear specifications and examples, it helps developers create systems that are easier to visualize, test, extend, and adapt to different AI providers or internal tools.
🔗 https://github.com/strongdm/attractor
📰 https://news.ycombinator.com/item?id=47152719
📢 @hackernewsgithubprojects
📦 strongdm/attractor
Attractor is a blueprint repository that explains how to build an AI-powered workflow system and coding assistant loop, rather than a finished app you install and run. It focuses on describing the architecture, data formats, and execution flow for complex tasks that need multiple steps, decisions, and retries. The problem it solves is the mess of one-off scripts and hard-to-maintain automation when teams try to connect AI tools together. By providing clear specifications and examples, it helps developers create systems that are easier to visualize, test, extend, and adapt to different AI providers or internal tools.
🔗 https://github.com/strongdm/attractor
📰 https://news.ycombinator.com/item?id=47152719
📢 @hackernewsgithubprojects
Audio
🔊 A Database That Also Runs Your App
📦 clockworklabs/spacetimedb
SpacetimeDB is an open-source project that combines a database and backend server into one system for building real-time applications. Instead of splitting data storage, server logic, and live updates across different tools, developers can keep the app’s rules close to the data and connect clients to a single platform. It helps solve a common problem: products like multiplayer games, chat apps, and collaborative tools are often hard to build, sync, and scale. By reducing moving parts and handling fast shared updates, SpacetimeDB can make development simpler, cut backend complexity, and help teams ship interactive software faster.
🔗 https://github.com/clockworklabs/SpacetimeDB
📰 https://news.ycombinator.com/item?id=47152859
📢 @hackernewsgithubprojects
📦 clockworklabs/spacetimedb
SpacetimeDB is an open-source project that combines a database and backend server into one system for building real-time applications. Instead of splitting data storage, server logic, and live updates across different tools, developers can keep the app’s rules close to the data and connect clients to a single platform. It helps solve a common problem: products like multiplayer games, chat apps, and collaborative tools are often hard to build, sync, and scale. By reducing moving parts and handling fast shared updates, SpacetimeDB can make development simpler, cut backend complexity, and help teams ship interactive software faster.
🔗 https://github.com/clockworklabs/SpacetimeDB
📰 https://news.ycombinator.com/item?id=47152859
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