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1931 Ford Model a Hot Rod Bridges Generations with a Civic Type R Engine

https://www.thedrive.com/news/this-1931-ford-model-a-hot-rod-bridges-a-generational-gap-with-a-ci...
1•PaulHoule•2m ago•0 comments

AI Lazyslop and Personal Responsibility

https://danielsada.tech/blog/ai-lazyslop-and-personal-responsibility/
1•dshacker•2m ago•0 comments

When do most people have the day off?

https://www.not-ship.com/when-do-most-people-have-the-day-off/
1•speckx•7m ago•1 comments

Graviton: Create Complex Generative AI pipelines, auto-export as API

https://github.com/jaskirat05/Graviton
1•jaskirat05•9m ago•0 comments

How could Claude Code ever justify "a small game engine" (technical deepdive)

https://clifford.ressel.fyi/blog/drawing-monospace-text/
3•csressel•9m ago•1 comments

No US-Style AI Investment Boom to Drive EU Growth

https://www.oxfordeconomics.com/resource/no-us-style-ai-investment-boom-to-drive-eu-growth/
1•jandrewrogers•10m ago•0 comments

Show HN: PolyMCP Skills – Scalable Tool Organization for MCP-Based AI Agents

1•justvugg•12m ago•0 comments

Continuous Autoregressive Language Models (Calm): A New LLM Architecture [video]

https://www.youtube.com/watch?v=DDowKmd4qe4
1•znpy•14m ago•0 comments

The Three Projections of Doctor Futamura (2009)

http://blog.sigfpe.com/2009/05/three-projections-of-doctor-futamura.html
2•measurablefunc•15m ago•0 comments

Gold Price Tops $5k for First Time

https://www.wsj.com/livecoverage/stock-market-today-dow-sp-500-nasdaq-01-26-2026
1•bookofjoe•17m ago•1 comments

Notes on Not Posting

https://www.workingtheorys.com/p/notes-on-not-posting
2•imartin2k•19m ago•0 comments

Design System: the art of documented compromise

https://medium.com/doctolib/design-system-the-art-of-documented-compromise-04a7a5fab937
1•rognjen•20m ago•0 comments

Timeline of Diffusion Language Models

https://github.com/VILA-Lab/Awesome-DLMs
1•tilt•20m ago•0 comments

Silver Thursday

https://en.wikipedia.org/wiki/Silver_Thursday
1•ValentineC•21m ago•0 comments

Show HN: Minima – Open-source micro-learning LMS (alternative to Moodle)

https://github.com/cobel1024/minima
1•pigon1002•22m ago•0 comments

The Home Computer Hybrids: Atari, TI, and the FCC

https://technicshistory.com/2026/01/25/the-home-computer-hybrids/
2•cfmcdonald•23m ago•0 comments

Show HN: FilaMeter – Local-first filament inventory management for 3D printing

https://filameter.com/
1•ldrrp•23m ago•0 comments

Show HN: VLM Inference Engine in Rust

https://mixpeek.com/blog/building-a-production-ready-vlm-inference-server-in-rust
1•Beefin•23m ago•0 comments

Browsh the modern text-based browser

https://www.brow.sh/docs/installation/
1•ungawatkt•24m ago•0 comments

Home Lab Developments

https://zitseng.com/archives/25229
2•todsacerdoti•25m ago•0 comments

Show HN: Poast – Publish Quickly from Claude, Cursor, ChatGPT

https://www.poast.sh/post/acb2475e-7871-4f62-9f25-3e60d38861d4
1•k0mplex•27m ago•0 comments

Show HN: ScaleLighthouse – Bulk Lighthouse, Playwright smoke tests, CrUX metrics

https://github.com/acenji/lighthouse
1•acenji•28m ago•0 comments

The WABL Test: Would anything of value be lost if you delete this?

https://www.gkogan.co/would-anything-of-value-be-lost/
1•gk1•30m ago•0 comments

The "Bucket Bumping" problem of airline tickets

https://www.dodgycoder.net/2026/01/the-bucket-bumping-problem-of-airline-tickets.html
1•abnercoimbre•31m ago•1 comments

Tesla FSD vs. Snow Ice Emergency Avoidance Braking Lane Perception

https://www.youtube.com/watch?v=6nwhbIOipXQ
1•hnburnsy•31m ago•0 comments

What Are the Greatest Sequels of All Time? A Statistical Analysis (2025)

https://www.statsignificant.com/p/what-are-the-greatest-sequels-of
1•speckx•33m ago•2 comments

The Underground Node Network

https://github.com/mevdschee/underground-node-network/blob/main/README.md
3•insom•34m ago•0 comments

How animators and AI researchers made 'Dear Upstairs Neighbors'

https://blog.google/innovation-and-ai/models-and-research/google-deepmind/dear-upstairs-neighbors/
2•saikatsg•34m ago•0 comments

Dithering – Part 2: The Ordered Dithering

https://visualrambling.space/dithering-part-2/
3•ChrisArchitect•34m ago•2 comments

Show HN: Cmpsbl OS v5.5.0 – A Self-Hosting Cognitive Substrate (131k LOC)

https://zenodo.org/records/18379258
1•promptfluid•36m ago•0 comments
Open in hackernews

Show HN: Ourguide – OS wide task guidance system that shows you where to click

https://ourguide.ai
1•eshaangulati•1h ago
Hey! I'm eshaan and I dropped out of college at 19 to build Ourguide -an on-screen task guidance system that can show you where to click step-by-step when you need help.

I started building this because whenever I didn’t know how to do something on my computer, I found myself constantly tabbing between chatbots and the app, pasting screenshots, and asking “what do I do next?” Ourguide solves this with two modes. In Guide mode, the app overlays your screen and highlights the specific element to click next, eliminating the need to leave your current window. There is also Ask mode, which is a vision-integrated chat that captures your screen context—which you can toggle on and off anytime -so you can ask, "How do I fix this error?" without having to explain what "this" is.

It’s an Electron app that works OS-wide, is vision-based, and isn't restricted to the browser.

Figuring out how to show the user where to click was the hardest part of the process. I originally trained a computer vision model with 2300 screenshots to identify and segment all UI elements on a screen and used a VLM to find the correct icon to highlight. While this worked extremely well—better than SOTA grounding models like UI Tars—the latency was just too high. I'll be making that CV+VLM pipeline OSS soon, but for now, I’ve resorted to a simpler implementation that achieves <1s latency.

You may ask: if I can show you where to click, why can't I just click too? While trying to build computer-use agents during my job in Palo Alto, I hit the core limitation of today’s computer-use models where benchmarks hover in the mid-50% range (OSWorld). VLMs often know what to do but not what it looks like; without reliable visual grounding, agents misclick and stall. So, I built computer use—without the "use." It provides the visual grounding of an agent but keeps the human in the loop for the actual execution to prevent misclicks.

I personally use it for the AWS Console's "treasure hunt" UI, like creating a public S3 bucket with specific CORS rules. It’s also been surprisingly helpful for non-technical tasks, like navigating obscure settings in Gradescope or Spotify. Ourguide really works for any task when you’re stuck or don't know what to do.

You can download and test Ourguide here: https://ourguide.ai/downloads

The project is still very early, and I’d love your feedback on where it fails, where you think it worked well, and which specific niches you think Ourguide would be most helpful for.