I know I need marketing help but giving equity to someone I met online feels like a huge risk. At the same time hiring a paid marketer when you have zero revenue feels just as scary. And I'm not dancing on TikTok, that's for sure.
Have any of you actually taken on a marketing co-founder? What made you say yes to that person specifically? Was it their track record, the way they pitched, a trial period first?
We've played a critical role in developer hiring over the last 15 years, with 30m+ developers on our platform and now going through a founding moment -- reinventing the company for the agentic era.
Specifically, we are changing hiring across 3 dimensions:
> Tasks: Real-world tasks on code repositories vs standard algorithmic-style puzzles
> Evaluation: AI fluency, orchestration skills vs functional correctness
> Candidate experience: Agentic IDE vs a simple code editor
We are already live across many companies and it's exciting to see the world finally move away from the old-school Leetcode style puzzles.
Role The role of the FDE will be to help our customers implement the new hiring process and serve as a bridge between the product & customer teams as we rapidly build the new HackerRank.
Being technically fluent and strong communication skills are critical. You will be working directly with engineering leaders at our customers to redesign how they evaluate talent.
Location Santa Clara, New York, London, Bangalore (hybrid set up with 3 to 4 days/week in-office)
How to apply Send me an email with evidence across these attributes: (a) Smart (b) Curiosity (c) Agency and (d) AI fluency
The glyph "A" in the font has 16 vertical bar contours. The hinting program reads player coordinates from font variation axes via GETVARIATION, does DDA ray marching against a tile map in the storage area, and repositions bar heights with SCFS. It ends up looking like a crude Wolfenstein-style view.
Small visuzlization: https://github.com/4RH1T3CT0R7/ttf-doom/blob/main/docs/media...
About 6.5 KB of bytecode total - 13 functions, 795 storage slots, sin/cos lookup tables.
JS handles movement, enemies, and shooting, then passes the coordinates to the font through CSS font-variation-settings. The font is basically a weird GPU.
The weirdest parts: - TrueType MUL does (ab)/64, not ab. So 1*4=0. The DIV instruction is equally cursed. - No WHILE loops. Everything compiles to recursive FDEFs. FreeType limits call depth to ~64 frames. - SVTCA[0] is Y, SVTCA[1] is X. Of course.
There's a small compiler behind this - lexer, parser, codegen - that turns a C-like DSL into TT assembly.
Demo GIF: https://github.com/4RH1T3CT0R7/ttf-doom/blob/main/docs/media...
Live demo: https://4rh1t3ct0r7.github.io/ttf-doom/ (Chrome/Edge, WASD+arrows, Space to shoot, Tab for debug overlay)
This is a DOOM-style raycaster, not a port of the original engine - similar to DOOMQL and the Excel DOOM. The wall rendering does happen in the font's hinting VM though. Press Tab in the demo to watch the font variation axes change as you move.
* Prezi Prezi pioneered the zooming canvas for presentations and remains the market leader in that space. It recently added AI-powered generation and text editing tools. It's a polished product with real traction.
But Prezi is a closed platform, not a library. You can't use its zoom engine in your own app. Pricing starts at $15/month for meaningful features, and exporting to PowerPoint flattens all zoom effects into static slides. A recurring complaint from users is that the zooming and panning transitions cause motion sickness. And fundamentally, Prezi uses zoom as a storytelling device between pre-arranged frames. It's not a navigation model. It's a presentation model.
* impress.js impress.js brought Prezi-like zooming to the open web. It's a presentation framework based on CSS3 transforms and transitions, directly inspired by Prezi. It was genuinely groundbreaking when it launched. Its architecture is step-based: you position "steps" in 3D space and the camera moves between them. That's great for presentations, but it doesn't help you build an app where users navigate by zooming into content. impress.js has no concept of dynamically mounting views, managing zoom depth, or handling navigation state. It's a slide deck engine with a zoom trick.
* Zumly This is what I built. Full disclosure: I'm the sole developer. The idea is offering an alternative to traditional page navigation using zooming. You mark an element as zoomable, point it to a view, and Zumly handles the transition and inserts new views. That's basically it.
I started Zumly in 2020 after leaving behind Zircle UI (a Vue zooming library), trying to take what I learned further. Framework-agnostic, focused just on the zoom part. Since then I've rewritten the engine several times, changed the approach more than once. Only now I'm actually happy with how it feels.
Views are dynamically mounted and unmounted during zoom transitions. In impress.js, all steps exist in the DOM simultaneously. In Zumly, you zoom into a trigger element, and the target view gets injected and scaled into place. This is closer to how routing works in SPAs than to how slide decks work.
The landing page is built with Zumly itself so you can get the feel before touching any code.
Curious if anyone else has thought about this space. What makes zooming UIs work or fail?
Landing page (built with Zumly): https://zumerlab.github.io/zumly
GitHub: https://github.com/zumerlab/zumly
For the first generation of agents it looked like workflows with minimal tools. 2 years ago we published a package to let AI work in SQL, at that time GPT-4 could write simple scripts. Soon after the first AI App Builders started using AI to make whole websites; we supported that with a serverless deploy system.
But the current generation is going much further, instead of minimal tools and basic serverless apps AI can utilize the full power of a computer (“sandbox”). We’re building sandboxes that are interchangeable with EC2s from your agents perspective, with bonus features:
1. We’ve figured out how to fork a sandbox horizontally without more than a 400ms pause in it. That's not forking the filesystem, we mean forking the whole memory of it. If you’re half way down a browser page with animations running, they’ll be in the same place in all the forks. If you’re running a minecraft server every block and player will be in the same place on the forks. If you’re running a local environment and an error comes up in process that error will be there in all the forks. This works for snapshotting as well, you can save your place and come back weeks later.
2. Our sandboxes start in ~500ms.
Demo: https://www.loom.com/share/8b3d294d515442f296aecde1f42f5524
Compared with other sandboxes, our goal is to be the most powerful. We support full Linux + hardware-virtualization, eBPF, Fuse, etc. We run full Debian with multiple users and we use a systemd init instead of runc. Whatever your AI expects to work on debian should work on these vms, and if it doesn’t send a bug report.
In order to make this possible, we’ve moved to our own bare metal racks. Early in our testing we realized that moving VMs across cloud nodes would not have acceptable performance properties. We asked Google Cloud and AWS for a quote on their bare metal nodes and found that the monthly cost was equivalent to the total cost of the hardware so we did that.
Our goal is to build the necessary infrastructure to replicate the human devloop on the massively multi-tenant scale of AI, so these VMs should be as powerful as the ones you’re used to, while also being available to provision in seconds.
It has historically been extremely tedious though: scanning dozens of janky sites which have interminable page loading times; back buttons take you all the way back to the homepage etc.
The site I built - GovAuctions - lets you search every government surplus auction at once. You can filter by location, category, and price, save items to a watchlist, and get alerts when new auctions match what you're looking for.
Let me know what you think, if you have any suggestions, and if you find any deals in your area!
I’ve been having a lot of fun building Docking, an open-source dock for Linux written in Python with GTK 3 and Cairo. It includes an extensible applet system, 38 built-in applets, 12 themes, multi-monitor support, auto-hide, and works across several Linux/X11 desktop environments.
It also has prebuilt releases for x64 and arm64 across multiple package formats: AppImage, .deb, RPM, Flatpak, Snap, Arch, and Nix outputs.
GitHub: https://github.com/edumucelli/docking
Feedback is very welcome!
LLMs (mostly Claude Code) have been used during development, but I learned early on that it's not _great_ at code at this level, so I've restricted its use to mostly documentation and tests. There's _a little_ AI code in the user space, but I have a strict "no AI code" rule in the kernel itself. I find this helps not only with the quality / functionality of the code, but also with learning - for example, even though I've written multiple kernels in the past, it wasn't until Anos that I _truly_ grokked pagetable management and what was possible with a good VMM interface, and if I'd outsourced that implementation to an LLM I probably wouldn't have learned any of that.
In terms of approach, Anos avoids legacy platform features and outdated wiki / tutorial resources, and instead tries to implement as much as possible from manuals and datasheets, and it's definitely worked out well so far. There's no support for legacy platform features or peripherals, with all IO being memory mapped and MSI/MSI-X interrupts (no PIC), for example, which has helped keep the codebase focused and easy to work on. The kernel compiles to about 100KiB on x86-64, with enough features to be able to support multitasking and device drivers in user space.
As a hobby project, progress ebbs and flows with pressures of my day job etc, and the main branch has been quiet for the last few months. I have however been working on a USB stack as time allows, and hopefully will soon have at least basic HID support to allow me to take the next step and make Anos interactive.
I don't know how useful projects like Anos are any more, given we now live in the age of AI coding, but it's a fun learning experience and helps keep me technically grounded, and I'll carry on with it for as long as those things remain true.
