I'm Ivan, one of the founders of Slapdash (https://slapdash.com/). Slapdash lets you work across all of your cloud apps at desktop speed, sort of like an OS for cloud apps.
We have built a uniform, low-latency data browser (kind of like Finder) as well as a unified command line-like interface (kind of like Spotlight) for the applications you use at work.
When we left our big company jobs, one of the difficult things to part with was the tooling. Companies like Facebook and Stripe build a class of tools internally that unifies all the employees and any collaboration apps, so you can find anyone or anything the company knows. Everything is just a quick search away [0]. It\u2019s quite a useful way to work. Common questions in day-to-day work are easy to answer. What\u2019s the history of this code abstraction? What are my colleagues working on? What\u2019s the story with this customer?
Building such a system today means connecting people's cloud apps, because that's where most of the work is happening today. Even for a small team like us, our work spans Drive, Dropbox, Figma, GitHub, Asana, Notion, Docusign, Slack, Quip, etc.
The first thing we built was a low-latency file system for cloud apps. You connect an application like Drive, or GitHub to Slapdash and we give you a way to search and browse the data in a uniform interface (kind of like Finder). It turns your working world into a database you can easily query.
We modeled our file system as a graph and we built our architecture to match, with a focus on performance. We built an import system, which effectively solves a graph replication problem (translating the structure of the app data to the Slapdash graph and keeping it in sync). We then built a graph database on top of Postgres, added a data access layer with graph semantics, with GraphQL API delivering the data to the client.
Of course, the data we store is encrypted on disk, in-transit and in the data store. Slapdash employees can't see the contents of what we index since everything except the reverse index is encrypted. It\u2019s not zero-access yet, but we\u2019re building in that direction [1].
What we discovered is that by applying optimizations to how we store (sharding & colocation) and retrieve data (batching & coalescing) we could achieve an almost zero-latency [2] experience when browsing application data. As a result, it's much faster to browse Google Drive in Slapdash than in the Drive interface itself.
While the low-latency file system is interesting, we learned that being able to search and navigate is not enough utility for a single individual. People don\u2019t search as much as they think they do, and most have their unique information foraging habits that work well-enough.
However, we wanted Slapdash to be useful for anyone, not just an employee at a big company, so we turned our attention to building a new experience on top of the file system. Our goal was to take a leap in speed with which people can control their computers. We thought this was possible because the difference in UX between desktop and cloud app environments was so acute: the desktop OS is principled, integrated and fast, while cloud apps are latency-laden and confined to crowded browser tabs.
To that end, we built the Command Bar (Command Line + Search Bar). The Command Bar is best experienced as a desktop app, where it\u2019s invoked with a global shortcut. You can quickly search your apps, file tasks, peek at your calendar, create zoom meetings, etc: all with a couple of keystrokes. Of course, you can also write your own commands too.
In practice, it meaningfully cuts down the time you spend controlling the computer. For example, filing a task on GitHub might take 10 seconds of just navigating to the right screen, while you can start writing the task title within 2 seconds by invoking the "Create New GitHub Issue" command with the Command Bar. Things like searching for a customer record, doing a quick spreadsheet calculation and even routine things like opening an existing document are measurably faster. [3]
For teams and companies, Slapdash provides a unified interface to a team\u2019s collective knowledge. This has traditionally been reserved for top technology companies, but we are bringing these advantages to everybody else. And for the individual, we are making the use of disparate cloud apps feel closer to the classic experience of a desktop computer OS - fast, integrated and more productive.
We are still figuring out what apps to support, what commands we should build and how we can open up the platform for others to build on as well. We would love to hear from you on any of those counts and any feedback you might have!
[0] Facebook has something called "intern" and Stripe has an internal product called "Stripe Home".
[1] Content is stored using ECIES (with Secp256k1 curve and AES256 cipher in CTR mode), public-key-encrypted with individual per-user, per-app key pairs.
[2] It's actually not zero latency, of course, but by preloading most things on the hover state we can cut ~50ms of perceived latency (as long as the server response time is under that, which we try to do, it feels instant).
[3] We use the keystroke-level GOMS model to evaluate interface speed, but the speed difference here is large enough that it can be intuited.
Example of filing a task on GitHub: Time controlling computer: open browser, command + L ( focus location bar), type partial URL of repo until it auto-completes, wait for page to load, click on Issues, wait for page to load, click on \u201cNew Issue\u201d. Expressing actual intent: typing title of task.
Filing a task with Slapdash: Time controlling computer: Type Command + J, type \u201cCre gi\u201d to fuzzy match \u201cCreate New GitHub Issue\u201d command, hit enter. Expressing actual intent: typing title of task."},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"Launch HN: Slapdash (YC W19) \u2013 A uniform, low-latency interface for cloud apps"}},"_tags":["story","author_kanevski","story_24364811","launch_hn"],"author":"kanevski","children":[24365059,24365350,24365487,24365563,24366045,24367002,24367063,24367095,24367541,24367854,24368017,24368158,24368684,24368826,24369759,24370229,24370412,24371098,24371479,24372234,24374619,24375547,24384734,24386910,24387883],"created_at":"2020-09-03T15:13:38Z","created_at_i":1599146018,"num_comments":68,"objectID":"24364811","points":227,"story_id":24364811,"story_text":"Hello HN,
I'm Ivan, one of the founders of Slapdash (https://slapdash.com/). Slapdash lets you work across all of your cloud apps at desktop speed, sort of like an OS for cloud apps.
We have built a uniform, low-latency data browser (kind of like Finder) as well as a unified command line-like interface (kind of like Spotlight) for the applications you use at work.
When we left our big company jobs, one of the difficult things to part with was the tooling. Companies like Facebook and Stripe build a class of tools internally that unifies all the employees and any collaboration apps, so you can find anyone or anything the company knows. Everything is just a quick search away [0]. It\u2019s quite a useful way to work. Common questions in day-to-day work are easy to answer. What\u2019s the history of this code abstraction? What are my colleagues working on? What\u2019s the story with this customer?
Building such a system today means connecting people's cloud apps, because that's where most of the work is happening today. Even for a small team like us, our work spans Drive, Dropbox, Figma, GitHub, Asana, Notion, Docusign, Slack, Quip, etc.
The first thing we built was a low-latency file system for cloud apps. You connect an application like Drive, or GitHub to Slapdash and we give you a way to search and browse the data in a uniform interface (kind of like Finder). It turns your working world into a database you can easily query.
We modeled our file system as a graph and we built our architecture to match, with a focus on performance. We built an import system, which effectively solves a graph replication problem (translating the structure of the app data to the Slapdash graph and keeping it in sync). We then built a graph database on top of Postgres, added a data access layer with graph semantics, with GraphQL API delivering the data to the client.
Of course, the data we store is encrypted on disk, in-transit and in the data store. Slapdash employees can't see the contents of what we index since everything except the reverse index is encrypted. It\u2019s not zero-access yet, but we\u2019re building in that direction [1].
What we discovered is that by applying optimizations to how we store (sharding & colocation) and retrieve data (batching & coalescing) we could achieve an almost zero-latency [2] experience when browsing application data. As a result, it's much faster to browse Google Drive in Slapdash than in the Drive interface itself.
While the low-latency file system is interesting, we learned that being able to search and navigate is not enough utility for a single individual. People don\u2019t search as much as they think they do, and most have their unique information foraging habits that work well-enough.
However, we wanted Slapdash to be useful for anyone, not just an employee at a big company, so we turned our attention to building a new experience on top of the file system. Our goal was to take a leap in speed with which people can control their computers. We thought this was possible because the difference in UX between desktop and cloud app environments was so acute: the desktop OS is principled, integrated and fast, while cloud apps are latency-laden and confined to crowded browser tabs.
To that end, we built the Command Bar (Command Line + Search Bar). The Command Bar is best experienced as a desktop app, where it\u2019s invoked with a global shortcut. You can quickly search your apps, file tasks, peek at your calendar, create zoom meetings, etc: all with a couple of keystrokes. Of course, you can also write your own commands too.
In practice, it meaningfully cuts down the time you spend controlling the computer. For example, filing a task on GitHub might take 10 seconds of just navigating to the right screen, while you can start writing the task title within 2 seconds by invoking the "Create New GitHub Issue" command with the Command Bar. Things like searching for a customer record, doing a quick spreadsheet calculation and even routine things like opening an existing document are measurably faster. [3]
For teams and companies, Slapdash provides a unified interface to a team\u2019s collective knowledge. This has traditionally been reserved for top technology companies, but we are bringing these advantages to everybody else. And for the individual, we are making the use of disparate cloud apps feel closer to the classic experience of a desktop computer OS - fast, integrated and more productive.
We are still figuring out what apps to support, what commands we should build and how we can open up the platform for others to build on as well. We would love to hear from you on any of those counts and any feedback you might have!
[0] Facebook has something called "intern" and Stripe has an internal product called "Stripe Home".
[1] Content is stored using ECIES (with Secp256k1 curve and AES256 cipher in CTR mode), public-key-encrypted with individual per-user, per-app key pairs.
[2] It's actually not zero latency, of course, but by preloading most things on the hover state we can cut ~50ms of perceived latency (as long as the server response time is under that, which we try to do, it feels instant).
[3] We use the keystroke-level GOMS model to evaluate interface speed, but the speed difference here is large enough that it can be intuited.
Example of filing a task on GitHub: Time controlling computer: open browser, command + L ( focus location bar), type partial URL of repo until it auto-completes, wait for page to load, click on Issues, wait for page to load, click on \u201cNew Issue\u201d. Expressing actual intent: typing title of task.
Filing a task with Slapdash: Time controlling computer: Type Command + J, type \u201cCre gi\u201d to fuzzy match \u201cCreate New GitHub Issue\u201d command, hit enter. Expressing actual intent: typing title of task.","title":"Launch HN: Slapdash (YC W19) \u2013 A uniform, low-latency interface for cloud apps","updated_at":"2024-09-20T06:56:52Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"rbanffy"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"A Technical Analysis of the Capital One Hack \u2013 CloudSploit"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["gmi","cloud"],"value":"https://blog.cloudsploit.com/a-technical-analysis-of-the-capital-one-hack-a9b43d7c8aea?gi=fc097eefa614"}},"_tags":["story","author_rbanffy","story_20679352"],"author":"rbanffy","created_at":"2019-08-12T20:03:26Z","created_at_i":1565640206,"num_comments":0,"objectID":"20679352","points":3,"story_id":20679352,"title":"A Technical Analysis of the Capital One Hack \u2013 CloudSploit","updated_at":"2024-09-20T04:41:07Z","url":"https://blog.cloudsploit.com/a-technical-analysis-of-the-capital-one-hack-a9b43d7c8aea?gi=fc097eefa614"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"rdli"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"Ambassador Adds Cloud UI for CNCF Projects Emissary, Telepresence, and Argo"},"url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["gmi"],"value":"https://blog.getambassador.io/ambassador-adds-clickops-support-for-emissary-telepresence-and-argo-175c5677f7e9?gi=78fceeb9d32"}},"_tags":["story","author_rdli","story_30455490"],"author":"rdli","created_at":"2022-02-24T15:01:17Z","created_at_i":1645714877,"num_comments":0,"objectID":"30455490","points":2,"story_id":30455490,"title":"Ambassador Adds Cloud UI for CNCF Projects Emissary, Telepresence, and Argo","updated_at":"2024-09-20T10:36:32Z","url":"https://blog.getambassador.io/ambassador-adds-clickops-support-for-emissary-telepresence-and-argo-175c5677f7e9?gi=78fceeb9d32"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"ashtavakra"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"WordPress attacks and Cloud Armor protection on GCP \u2013 True story"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["gmi","cloud"],"value":"https://blog.thecloudside.com/wordpress-attacks-cloud-armor-protection-on-gcp-true-story-59ba25ffb7f8?gi=6923e35d97a2"}},"_tags":["story","author_ashtavakra","story_30166558"],"author":"ashtavakra","created_at":"2022-02-01T18:07:20Z","created_at_i":1643738840,"num_comments":0,"objectID":"30166558","points":2,"story_id":30166558,"title":"WordPress attacks and Cloud Armor protection on GCP \u2013 True story","updated_at":"2024-09-20T10:26:42Z","url":"https://blog.thecloudside.com/wordpress-attacks-cloud-armor-protection-on-gcp-true-story-59ba25ffb7f8?gi=6923e35d97a2"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"shahargl"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"From Cloud Run to Kubernetes: Why Internals Matter"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["gmi","cloud"],"value":"https://anecdotes.dev/from-cloud-run-to-kubernetes-how-learning-the-internals-of-your-stack-empowers-you-as-a-developer-3d0cdf7cb7ec?gi=3b548439d3ac"}},"_tags":["story","author_shahargl","story_29066122"],"author":"shahargl","created_at":"2021-11-01T12:56:03Z","created_at_i":1635771363,"num_comments":0,"objectID":"29066122","points":2,"story_id":29066122,"title":"From Cloud Run to Kubernetes: Why Internals Matter","updated_at":"2024-09-20T09:43:16Z","url":"https://anecdotes.dev/from-cloud-run-to-kubernetes-how-learning-the-internals-of-your-stack-empowers-you-as-a-developer-3d0cdf7cb7ec?gi=3b548439d3ac"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"nathan_tarbert"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"Exploring Cloud Hexagonal Design with Wing"},"url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["gmi"],"value":"https://itnext.io/hello-winglang-hexagon-6f2bdb550f37?gi=b7df0c3ecb24"}},"_tags":["story","author_nathan_tarbert","story_39228327"],"author":"nathan_tarbert","created_at":"2024-02-02T13:32:45Z","created_at_i":1706880765,"num_comments":0,"objectID":"39228327","points":1,"story_id":39228327,"title":"Exploring Cloud Hexagonal Design with Wing","updated_at":"2024-09-20T16:15:07Z","url":"https://itnext.io/hello-winglang-hexagon-6f2bdb550f37?gi=b7df0c3ecb24"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"anupamchugh"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"Heyoo \u2013 An Open-Source Python Wrapper for WhatsApp Cloud API"},"url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["gmi"],"value":"https://betterprogramming.pub/programming-whatsapp-is-now-even-easier-for-python-developers-e1a4343deed6?gi=23b1009fb82c"}},"_tags":["story","author_anupamchugh","story_31475594"],"author":"anupamchugh","created_at":"2022-05-23T05:27:06Z","created_at_i":1653283626,"num_comments":0,"objectID":"31475594","points":1,"story_id":31475594,"title":"Heyoo \u2013 An Open-Source Python Wrapper for WhatsApp Cloud API","updated_at":"2024-09-20T11:13:13Z","url":"https://betterprogramming.pub/programming-whatsapp-is-now-even-easier-for-python-developers-e1a4343deed6?gi=23b1009fb82c"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"rsecora"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"Snaring the Bad Folks / Cloud security is a hard problem"},"url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["gmi"],"value":"https://netflixtechblog.com/snaring-the-bad-folks-66726a1f4c80?gi=b8d807cbea97"}},"_tags":["story","author_rsecora","story_29563970"],"author":"rsecora","created_at":"2021-12-15T10:13:08Z","created_at_i":1639563188,"num_comments":0,"objectID":"29563970","points":1,"story_id":29563970,"title":"Snaring the Bad Folks / Cloud security is a hard problem","updated_at":"2024-09-20T10:05:54Z","url":"https://netflixtechblog.com/snaring-the-bad-folks-66726a1f4c80?gi=b8d807cbea97"},{"_highlightResult":{"author":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["cloud"],"value":"clouddrover"},"title":{"matchLevel":"none","matchedWords":[],"value":"For your eyes only: improving Netflix video quality with neural networks (2022)"},"url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["gmi"],"value":"https://netflixtechblog.com/for-your-eyes-only-improving-netflix-video-quality-with-neural-networks-5b8d032da09c?gi=65bdf98dcfbf"}},"_tags":["story","author_clouddrover","story_38255587"],"author":"clouddrover","created_at":"2023-11-13T21:22:31Z","created_at_i":1699910551,"num_comments":0,"objectID":"38255587","points":3,"story_id":38255587,"title":"For your eyes only: improving Netflix video quality with neural networks (2022)","updated_at":"2024-09-20T15:38:58Z","url":"https://netflixtechblog.com/for-your-eyes-only-improving-netflix-video-quality-with-neural-networks-5b8d032da09c?gi=65bdf98dcfbf"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"LargeModGames"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["gmi","cloud"],"value":"About 11 months ago i revived the amazing but unfortunately unmaintained spotify-tui. Since then I have been working on it almost non stop, finding a lot of problems on the way.
One of the main issues I ran into were the Spotify web API rate limits. Third party clients like spotatui are dependent on a developer app made in the Spotify developer dashboard, which get rate limited a lot and Spotify has slowly been deprecating endpoints from it. The workaround for this used to be using a shared client id from ncspot but unfortunately that got rate limited too. This is when i started adding other playback sources, including YouTube, Navidrome/Subsonic, Internet radio with +- 30.000 stations, local files, Qobuz for lossless audio and Apple Music for macOS only where it controls the music app remotely.
I fixed both the deprecated endpoints and the rate limits with one solution. It still uses librespot in the back, my spotatui specific fork, but gets all data from it instead of only playback. The data comes from the internal API of the official clients, that API gives metadata, playlists, the user library, devices, lyrics and audio analysis. For searching it uses Pathfinder, the internal GraphQL API.
There are no web API rate limits because there is no shared app quota. Every user uses their own session as if it was the official client. The only potential problem is that Spotify does not document this API so any change on their side would break it. I intend to fix any of those issues as soon as they pop up.
It all started as a TUI back in 2019 but since then I've added a GUI to it too. The GUI is still a bit behind the TUI in terms of features, it only ships Spotify for now, but full parity between the TUI and GUI is coming soon. After that full parity with the official client is next. That is also why I made the GUI looks almost the same as the official client. That way its easier for me and users to find missing features.
Spotatui also has lua scripting support, a optional Web companion on spotatui.com, and if you have a AI coding agent like ChatGPT codex or Claude Code you can enable the MCP tools, which lets AI become your personal DJ just by talking to it.
Its written in Rust, uses ratatui for the terminal UI and Tauri 2 for the GUI. The Rust core starts a small web server with localhost that only your pc can reach which the GUI then serves. Both frontends share the same playback logic, the same login and the same Spotify code. The only difference is how you interact with it.
On first launch it opens a web browser where you need to login with your Spotify premium account (premium is not optional), that is the whole setup done. I would love any feedback about bugs you encounter or features you would like to see.\nGitHub: https://github.com/LargeModGames/spotatui\nReleases: https://github.com/LargeModGames/spotatui/releases/latest\nWebsite: https://spotatui.com/
Thanks to librespot for making this all possible"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["gmi"],"value":"Show HN: Spotatui, a Spotify TUI/GUI without web API rate limits"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://github.com/LargeModGames/spotatui"}},"_tags":["story","author_LargeModGames","story_50070010","show_hn"],"author":"LargeModGames","children":[50079087,50080072,50081580,50081673,50082703,50087058,50091774],"created_at":"2026-10-13T11:32:00Z","created_at_i":1791891120,"num_comments":19,"objectID":"50070010","points":91,"story_id":50070010,"story_text":"About 11 months ago i revived the amazing but unfortunately unmaintained spotify-tui. Since then I have been working on it almost non stop, finding a lot of problems on the way.
One of the main issues I ran into were the Spotify web API rate limits. Third party clients like spotatui are dependent on a developer app made in the Spotify developer dashboard, which get rate limited a lot and Spotify has slowly been deprecating endpoints from it. The workaround for this used to be using a shared client id from ncspot but unfortunately that got rate limited too. This is when i started adding other playback sources, including YouTube, Navidrome/Subsonic, Internet radio with +- 30.000 stations, local files, Qobuz for lossless audio and Apple Music for macOS only where it controls the music app remotely.
I fixed both the deprecated endpoints and the rate limits with one solution. It still uses librespot in the back, my spotatui specific fork, but gets all data from it instead of only playback. The data comes from the internal API of the official clients, that API gives metadata, playlists, the user library, devices, lyrics and audio analysis. For searching it uses Pathfinder, the internal GraphQL API.
There are no web API rate limits because there is no shared app quota. Every user uses their own session as if it was the official client. The only potential problem is that Spotify does not document this API so any change on their side would break it. I intend to fix any of those issues as soon as they pop up.
It all started as a TUI back in 2019 but since then I've added a GUI to it too. The GUI is still a bit behind the TUI in terms of features, it only ships Spotify for now, but full parity between the TUI and GUI is coming soon. After that full parity with the official client is next. That is also why I made the GUI looks almost the same as the official client. That way its easier for me and users to find missing features.
Spotatui also has lua scripting support, a optional Web companion on spotatui.com, and if you have a AI coding agent like ChatGPT codex or Claude Code you can enable the MCP tools, which lets AI become your personal DJ just by talking to it.
Its written in Rust, uses ratatui for the terminal UI and Tauri 2 for the GUI. The Rust core starts a small web server with localhost that only your pc can reach which the GUI then serves. Both frontends share the same playback logic, the same login and the same Spotify code. The only difference is how you interact with it.
On first launch it opens a web browser where you need to login with your Spotify premium account (premium is not optional), that is the whole setup done. I would love any feedback about bugs you encounter or features you would like to see.\nGitHub: https://github.com/LargeModGames/spotatui\nReleases: https://github.com/LargeModGames/spotatui/releases/latest\nWebsite: https://spotatui.com/
Thanks to librespot for making this all possible","title":"Show HN: Spotatui, a Spotify TUI/GUI without web API rate limits","updated_at":"2026-10-16T06:40:48Z","url":"https://github.com/LargeModGames/spotatui"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"stray"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["gmi","cloud"],"value":"When Apple left Clozure Common Lisp behind by switching to Apple Silicon, I started kicking around the idea of building my own Lisp/Objective-C bridge by combining Apple Documentation, the clang AST, and introspection of the Objective-C runtime.
There was a CCL porting effort, but I really wanted to use SBCL anyway.
Truth be told \u2014 what I really wanted was a 21st-century CLIM variant on top of modern AppKit 26. So I let that idea rattle around in my skull for a while \u2014 and eventually it bounced up against the memory of Ck (Curses-based Tk).
Anybody remember that?
I liked Tcl/Tk and [incr Tcl] and it had always stuck in my head how great an idea it was to have something along the lines of CLIM for regular terminals as well as GUI.
So anyway, I stumbled upon the open-source CLIM2 source still maintained by Franz, and the wheels commenced to turn.
Oh yeah, and my very first programming environment had been Turbo Pascal. That integrated debugger was really something.
And y'know, it all started to come together as an idea about modernizing CLIM and modifying Portable Hemlock to run on top of it \u2014 and integrating a Debugger with conditional breakpoints and Step In/Step Out/Step Over, CLIM presentations, Inspector...
And in years past, I'd have just dreamed about it.
But the past three years have been crazy. GPT4 was the first time I seriously tried to build things with an LLM. And I've been pushing the LLMs as far as they would go to build my intuition mainly.
But up until this year they've been mostly crap.
I used "Build Common Lisp" as my north star because the Dietz ANSI tests seemed like a nearly perfect product specification.
Long story short: I threw away 7 attempts before I won ANSI \u2014 https://gitlab.com/patchwork1-ai/whateverlisp \u2014 and while I was waiting for Claude and Codex to grovel through ANSI I was trying my hand at my grand idea of Turbo Lisp.
Side note: my high score on ANSI is 21,916/21,925 passing (99.96%); 21,925 executed; 9 failing. And those 9? Yeah I don't think you could pass those without failing 30+ other ones.
So anyway \u2014 It\u2019s called *Turbo Lisp* (based on SBCL). It brings together a Listener, debugger, object inspector, conditional breakpoints + stepper, and Zeta\u2014a variant of Portable Hemlock that uses WhateverCLIM as its front-end.
On macOS, it uses native AppKit UI through *Chattanooga, a Lisp/Objective-C bridge I built*. It also runs in the terminal through *Oak Ridge, my Lisp port of Ratatui*. Both use *WhateverCLIM*, which is the CLIM2 code from Franz plus my own modernization, including *presentations*: displayed Lisp objects you can click and inspect.
*v0.2.1 patch release* is available for Apple Silicon Macs, Intel Macs, and Linux x86-64. The Mac builds currently require macOS 26.
I\u2019m especially interested in hearing:
* Does it install and start properly on your machine?\n* Can you find your way around the Listener, editor, and debugger?\n* Does the terminal interface work with your terminal emulator?\n* Where does it feel confusing, awkward, or broken?
A report that says \u201cI tried this and got stuck here\u201d is useful. Please include your OS, CPU architecture, and terminal emulator where relevant.
It\u2019s still early, and I\u2019m looking for honest feedback from people using it outside my own setup."},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Turbo Lisp \u2013 A Common Lisp IDE for macOS and the Terminal"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://gitlab.com/patchwork1-ai/turbolisp"}},"_tags":["story","author_stray","story_50110159","show_hn"],"author":"stray","created_at":"2026-10-15T21:00:36Z","created_at_i":1792098036,"num_comments":0,"objectID":"50110159","points":2,"story_id":50110159,"story_text":"When Apple left Clozure Common Lisp behind by switching to Apple Silicon, I started kicking around the idea of building my own Lisp/Objective-C bridge by combining Apple Documentation, the clang AST, and introspection of the Objective-C runtime.
There was a CCL porting effort, but I really wanted to use SBCL anyway.
Truth be told \u2014 what I really wanted was a 21st-century CLIM variant on top of modern AppKit 26. So I let that idea rattle around in my skull for a while \u2014 and eventually it bounced up against the memory of Ck (Curses-based Tk).
Anybody remember that?
I liked Tcl/Tk and [incr Tcl] and it had always stuck in my head how great an idea it was to have something along the lines of CLIM for regular terminals as well as GUI.
So anyway, I stumbled upon the open-source CLIM2 source still maintained by Franz, and the wheels commenced to turn.
Oh yeah, and my very first programming environment had been Turbo Pascal. That integrated debugger was really something.
And y'know, it all started to come together as an idea about modernizing CLIM and modifying Portable Hemlock to run on top of it \u2014 and integrating a Debugger with conditional breakpoints and Step In/Step Out/Step Over, CLIM presentations, Inspector...
And in years past, I'd have just dreamed about it.
But the past three years have been crazy. GPT4 was the first time I seriously tried to build things with an LLM. And I've been pushing the LLMs as far as they would go to build my intuition mainly.
But up until this year they've been mostly crap.
I used "Build Common Lisp" as my north star because the Dietz ANSI tests seemed like a nearly perfect product specification.
Long story short: I threw away 7 attempts before I won ANSI \u2014 https://gitlab.com/patchwork1-ai/whateverlisp \u2014 and while I was waiting for Claude and Codex to grovel through ANSI I was trying my hand at my grand idea of Turbo Lisp.
Side note: my high score on ANSI is 21,916/21,925 passing (99.96%); 21,925 executed; 9 failing. And those 9? Yeah I don't think you could pass those without failing 30+ other ones.
So anyway \u2014 It\u2019s called *Turbo Lisp* (based on SBCL). It brings together a Listener, debugger, object inspector, conditional breakpoints + stepper, and Zeta\u2014a variant of Portable Hemlock that uses WhateverCLIM as its front-end.
On macOS, it uses native AppKit UI through *Chattanooga, a Lisp/Objective-C bridge I built*. It also runs in the terminal through *Oak Ridge, my Lisp port of Ratatui*. Both use *WhateverCLIM*, which is the CLIM2 code from Franz plus my own modernization, including *presentations*: displayed Lisp objects you can click and inspect.
*v0.2.1 patch release* is available for Apple Silicon Macs, Intel Macs, and Linux x86-64. The Mac builds currently require macOS 26.
I\u2019m especially interested in hearing:
* Does it install and start properly on your machine?\n* Can you find your way around the Listener, editor, and debugger?\n* Does the terminal interface work with your terminal emulator?\n* Where does it feel confusing, awkward, or broken?
A report that says \u201cI tried this and got stuck here\u201d is useful. Please include your OS, CPU architecture, and terminal emulator where relevant.
It\u2019s still early, and I\u2019m looking for honest feedback from people using it outside my own setup.","title":"Show HN: Turbo Lisp \u2013 A Common Lisp IDE for macOS and the Terminal","updated_at":"2026-10-16T02:56:47Z","url":"https://gitlab.com/patchwork1-ai/turbolisp"}],"hitsPerPage":50,"nbHits":34,"nbPages":1,"page":0,"params":"query=GMI+Cloud&tags=story&hitsPerPage=50&advancedSyntax=true&analyticsTags=backend","processingTimeMS":74,"processingTimingsMS":{"_request":{"queue":161,"roundTrip":20},"afterFetch":{"format":{"highlighting":1,"total":2},"merge":{"mergeLoop":{"prepareNextHit":4,"total":4},"total":4},"total":4},"fetch":{"query":7,"scanning":11,"total":19},"getIdx":{"load":{"dicts":10,"gens":38,"total":49},"total":49},"total":74},"query":"GMI Cloud","serverTimeMS":238}