Show HN: Sketch Stadium – watch your agent play Pictionary https://ift.tt/nfytYlJ

Show HN: Sketch Stadium – watch your agent play Pictionary tl;dr: Agents can play Pictionary. You can connect your own agent, or just watch a game in progress here: https://ift.tt/xVSKUPq Hi folks! I initially built this as a proof-of-concept for sending push notifications to AI agents. Watching the agents play Pictionary together has been compelling, so I thought I'd ship it as a standalone demonstration. In Sketch Stadium, your agent subscribes to game events. Agents take turns either drawing or guessing. Easy clues are 1 point, medium are 2, and hard are 3. It's entertaining to watch and some of the drawings are impressive (and others are mind-bogglingly bad). This is the real opportunity for the model labs who have been pelican-maxxing to shine. The first version gave agents the ability to draw lines 10 at a time so that it would be a little bit more like real Pictionary. However, it turns out agents are _really_ bad at drawing that way. So instead I let them use a subset of SVG to draw and that's worked much better, even for the lower-cost models. You don't need to create an account to connect your agent, just add the MCP and authorize. But if you don't want to do that, just watch the game linked above. As a bit more background, agents often start processes that take an indeterminate amount of time to complete (e.g. CI, waiting for approval in a separate system, sending an email and waiting for a reply). If an agent needs that process to complete before it can proceed, it can: * poll, * ask the user to tell it when it's done, * use a bespoke built-in integration, or * use a proprietary capability (e.g. Claude Code monitors) Today, there's no easy, consistent way to wake up agents through a webhook or push notification. I dealt with this firsthand with Clawvisor (authorization for agents) where I needed agents to recognize when the operator had clicked an out-of-band approve button. The best-supported way to achieve that at the time was long-polling. This project is basically a tech demo for Wakeshift, which is a cross-harness, simple SDK for providing push notifications for agents. It attaches to your MCP to allow consumers of your MCP to subscribe to real-time events, and uses whatever available hacks per harness to wake an agent when dormant. For most harnesses, Wakeshift requires a hook to be installed for the best experience. It will upgrade automatically as harnesses start adopting MCP events. I'd love any feedback or ideas for other products or games that you'd want to see built on this capability. Or MCP servers that you use today that you think would benefit from push notifications. https://ift.tt/xVSKUPq October 30, 2026 at 12:23PM

Show HN: I Turned DOOM into a Transformer https://ift.tt/NlPaeHO

Show HN: I Turned DOOM into a Transformer Instead of trying to run DOOM on things, I have instead decided to use DOOM (many, many, many doom games actually) to create a transformer. For a lot of the math required I essentially had to use DOOM game mechanics and voodoo dolls (DOOM is turing complete btw) and exchange them with the actual operations, essentially creating an alternative to NumPy (a 65000x slower one). Thus, I am proud to present DOOMFORMER. Here are a list of things DOOMFORMER can do : It can classify MNIST digits, even if you write these digits on the map! It can talk(kinda) You can use it to make decisions, so, it can play DOOM. Yes! You can play DOOM with thousands of DOOM games now! The marine's mind can be controlled by DOOM, playing on a map generated by DOOMFORMER. Truly, the possibilities are endless, and even larger-scale training of DOOMFORMER could be done on a measly T4. If anyone would like to help me scale this up and make crazier things, I'd love to work together. https://ift.tt/ub4myRX October 29, 2026 at 08:25PM

Show HN: I rebuilt Kubernetes for ESP32 microcontrollers https://ift.tt/TihrcmG

Show HN: I rebuilt Kubernetes for ESP32 microcontrollers https://ift.tt/RdrCzEh October 29, 2026 at 01:35PM

Show HN: I got tired of travel spreadsheets so I made a travel planner app https://ift.tt/grTVqHk

Show HN: I got tired of travel spreadsheets so I made a travel planner app Hey everyone! I couldn't find an app to organize trips that gave me all the info I wanted to schedule each stop per day, with travel times, leeway, etc, so I made Wherewhen. The basic differentiator is that you can set various constraints (e.g. "I want to spend 2 hours in the park", or "I have a dinner reservation at 6"), and Wherewhen will automatically adjust the rest of the times to tell you when to go/leave each place, including travel. I've tried to make it mobile-friendly but travel planning is pretty complicated and it's a bit clunky on mobile. Feedback is appreciated! https://www.wherewhen.cc October 29, 2026 at 07:37AM

Show HN: A Cursor-like workspace for your LaTeX papers https://ift.tt/cYrhOvG

Show HN: A Cursor-like workspace for your LaTeX papers https://ift.tt/0skng6K October 29, 2026 at 02:39AM

Show HN: Fabivo – Furniture design from a photo to a numbered cut list https://ift.tt/hXMUBEF

Show HN: Fabivo – Furniture design from a photo to a numbered cut list Hello all, Ive been building Fabivo, a free furniture planner that runs in the browser. You sketch it simply by drawing it, (by far my favorite feature of this app), clicking for boards or just selecting some starting designs. But what i think separates fabivo from others its the image to model ai assistant, which took me a looong time to develop and get some quirks fixed, thanks god latest models are focusing on 3d, thats been helping too! The photo part is an image to JSON CAD harness: the model returns a parametric furniture model in mm that the app can build and edit. That harness is also what i benchmark, and honestly its the reason the app exists. I wanted to see if a photo could turn into a plan i could take to the saw. Also finetuned some image models and found interesting stuff, that was a first. My intention was to basically reuse the drawing feature to convert a 2d line sketch from image models like gpt image / nano banana to my parametric model, which "worked", and was actually thinking of using that for prod, but then cheaper/better models at 3d launched, but anyways, i learned a lot! Im getting better performance from my harness than from plain 3js, tho this is anecdotally and havent actually benchmarked it... Happy to answer anything, especially about the harness or the cut order. edit: Adding the numbers, missed them. 17 photos of real furniture, three models, same harness, medium reasoning, same tools. Scored on how close the returned structure and boards are to the gold model, so its my own set. (tho i have a hard time making a good scoring metric... just usually go by look!) Model (medium reasoning) Avg. time / photo Avg. input tokens / photo Avg. output tokens / photo Avg. tool calls / photo GPT-6.1 Terra 9.5 s 30,409 632 1.06 Claude Sonnet 5.5 13.6 s 50,167 1,592 1.18 Claude Haiku 5.5 34.9 s 66,786 6,658 2.35 Terra was both cheaper per photo and the most consistent to my likings. Sonnet was close on quality, Haiku needed way more tool calls to get there. https://ift.tt/c2r0NfP October 29, 2026 at 02:21AM

Show HN: Curate. free, no ADS, with AI, private photo cleaner for iPhone https://ift.tt/6xmIYaq

Show HN: Curate. free, no ADS, with AI, private photo cleaner for iPhone https://ift.tt/niFJPHX October 28, 2026 at 05:52AM