Can I get insurance for company renting humanoids for parties?
2 by cpsk | 1 comments on Hacker News.
It feels like an daunting and impossible task to find insurance for a company trying to rent humanoids for events and parties. How in the world are Neos and Telsa Optimus going to get insurance coverage if they are inside a home? Are they just big players so they can get hold of risk underwriters and get them to approve it. But a small company that is trying to build rent robots for parties or conduct educational workshops using humanoids cannot get even general liability.
Hack Nux
Watch the number of websites being hacked today, one by one on a page, increasing in real time.
New Show Hacker News story: Show HN: Halo 3's Guardian, playable in the browser, as my personal website
Show HN: Halo 3's Guardian, playable in the browser, as my personal website
8 by runshouse | 3 comments on Hacker News.
I've never had a personal website, and I didn't want to make a resume/portfolio site, so I rebuilt Guardian and hid a treasure hunt through my life inside it. You start in the Halo 3 main menu, go through the lobby, spawn in the map, and explore. There are photos, stories, quests, mini-games, and Easter eggs scattered around. Movement is via WASD and mouse, no signup. Guardian was my third place growing up. Starting in 9th grade, my friends and I would get home after school, get on Halo, and hang out in a Guardian free-for-all with MLG settings until everyone came online, then play customs or ranked for hours. On weekends we'd bring our Xboxes and monitors to each other's houses, stay up all night, and play in local tournaments. Guardian was probably the closest thing I had to a digital home, so I wanted my site to live there. Playing it and hearing the theme music for the first time in 10+ years in a place I knew by heart felt a bit like coming home. The map itself isn't AI-generated. It uses an original Guardian asset export distributed through the fan-run Halo Archive: an OBJ with 115,250 faces, the original UV coordinates, and 42 referenced diffuse textures, loaded through Three.js. What was AI-generated was everything on top needed to turn it into a complete game: shaders, lighting, scenario tags, physics, animations, collision, movement, sky and fog, lifts, pickups, weapon handling, and quest routing. Every pickup was placed by hand against the geometry using callout maps and a dev-only coordinate locator. This was surprisingly tedious to get right - I think it took me 10 iterations just to get the blue lift on Camo to line up parallel with the ledge. The Guardian geometry and texture assets are 21 MB, so the load is hidden inside the lobby countdown and scorecard screen while the shaders warm up. It targets 60 FPS and feels smooth on a recent MacBook in Chrome. Touch controls work on mobile, but the field of view is roughly 20 degrees in portrait, so desktop is definitely the best way to play it. I built it with Codex using Astra. It wrote essentially all of the code: 20,552 lines of TypeScript across 118 files, 973M tokens, 37 hours of runtime, and about 25-30 hours of my time. Coding wasn't the hard part. The time-consuming part was deciding which memories belonged in the map, where each should live, what game mechanic fit each one best, and then playing it over and over to fix bugs and get the movement and user flow to feel right. I'll write up more about the Codex/Astra side in a comment since I had a lot of interesting learnings from building something this large with it. This is an unofficial fan project and I'm not making money from it. The geometry, textures, UI, and many of the sound effects are Halo material and belong to their respective owners. Some things are still rough. There's occasional lag when picking up a power weapon. The lifts don't feel quite natural - it was hard to replicate the vacuum effect of the real lifts. On some browsers like Firefox, audio needs a click before it starts. Would love feedback on how it could be improved, especially from anyone else who spent a lot of time on this map.
8 by runshouse | 3 comments on Hacker News.
I've never had a personal website, and I didn't want to make a resume/portfolio site, so I rebuilt Guardian and hid a treasure hunt through my life inside it. You start in the Halo 3 main menu, go through the lobby, spawn in the map, and explore. There are photos, stories, quests, mini-games, and Easter eggs scattered around. Movement is via WASD and mouse, no signup. Guardian was my third place growing up. Starting in 9th grade, my friends and I would get home after school, get on Halo, and hang out in a Guardian free-for-all with MLG settings until everyone came online, then play customs or ranked for hours. On weekends we'd bring our Xboxes and monitors to each other's houses, stay up all night, and play in local tournaments. Guardian was probably the closest thing I had to a digital home, so I wanted my site to live there. Playing it and hearing the theme music for the first time in 10+ years in a place I knew by heart felt a bit like coming home. The map itself isn't AI-generated. It uses an original Guardian asset export distributed through the fan-run Halo Archive: an OBJ with 115,250 faces, the original UV coordinates, and 42 referenced diffuse textures, loaded through Three.js. What was AI-generated was everything on top needed to turn it into a complete game: shaders, lighting, scenario tags, physics, animations, collision, movement, sky and fog, lifts, pickups, weapon handling, and quest routing. Every pickup was placed by hand against the geometry using callout maps and a dev-only coordinate locator. This was surprisingly tedious to get right - I think it took me 10 iterations just to get the blue lift on Camo to line up parallel with the ledge. The Guardian geometry and texture assets are 21 MB, so the load is hidden inside the lobby countdown and scorecard screen while the shaders warm up. It targets 60 FPS and feels smooth on a recent MacBook in Chrome. Touch controls work on mobile, but the field of view is roughly 20 degrees in portrait, so desktop is definitely the best way to play it. I built it with Codex using Astra. It wrote essentially all of the code: 20,552 lines of TypeScript across 118 files, 973M tokens, 37 hours of runtime, and about 25-30 hours of my time. Coding wasn't the hard part. The time-consuming part was deciding which memories belonged in the map, where each should live, what game mechanic fit each one best, and then playing it over and over to fix bugs and get the movement and user flow to feel right. I'll write up more about the Codex/Astra side in a comment since I had a lot of interesting learnings from building something this large with it. This is an unofficial fan project and I'm not making money from it. The geometry, textures, UI, and many of the sound effects are Halo material and belong to their respective owners. Some things are still rough. There's occasional lag when picking up a power weapon. The lifts don't feel quite natural - it was hard to replicate the vacuum effect of the real lifts. On some browsers like Firefox, audio needs a click before it starts. Would love feedback on how it could be improved, especially from anyone else who spent a lot of time on this map.
New ask Hacker News story: Zuck's bot increased our Vercel bill 10x
Zuck's bot increased our Vercel bill 10x
2 by Marciok | 0 comments on Hacker News.
I’m writing this after receiving a Vercel bill that was 10x higher than usual. The worst part: The increase wasn’t caused by more users, but by +1M requests from meta-externalagent/1.1. The requests targeted a Vercel preview deployment that we had shared on WhatsApp to test whether its link-preview metadata was working correctly. We naively never bothered with bot calls; they had never caused any problems in the previous four years of our app on Vercel, but that changed when Meta’s crawler began repeatedly visiting this preview deployment. If you host on Vercel, review your bot-protection settings and make sure preview deployments aren’t unnecessarily exposed. Otherwise, an aggressive crawler could leave you with a surprisingly large bill. And unfortunately, Vercel declined to help to ease this bill. Zuck is definitely not slowing down.
2 by Marciok | 0 comments on Hacker News.
I’m writing this after receiving a Vercel bill that was 10x higher than usual. The worst part: The increase wasn’t caused by more users, but by +1M requests from meta-externalagent/1.1. The requests targeted a Vercel preview deployment that we had shared on WhatsApp to test whether its link-preview metadata was working correctly. We naively never bothered with bot calls; they had never caused any problems in the previous four years of our app on Vercel, but that changed when Meta’s crawler began repeatedly visiting this preview deployment. If you host on Vercel, review your bot-protection settings and make sure preview deployments aren’t unnecessarily exposed. Otherwise, an aggressive crawler could leave you with a surprisingly large bill. And unfortunately, Vercel declined to help to ease this bill. Zuck is definitely not slowing down.
New Show Hacker News story: Show HN: Pizza Bot – An inbox for AI agents that work in the background
Show HN: Pizza Bot – An inbox for AI agents that work in the background
9 by jd_ | 2 comments on Hacker News.
Hi HN - long-time lurker (since 2012!), first time poster. Pizza Bot is a self-hosted desktop app for Mac, Windows, and Linux that runs AI agents in the background and exposes them through an email-like UI. Finished work shows up in Unread, and anything waiting on your approval shows up in Action. It's Apache 2.0-licensed, there's no signup and no telemetry, and you bring your own model provider: Anthropic, Amazon Bedrock, Google Gemini, OpenAI, OpenRouter, or a local model through Ollama. There are builds on the releases page, or you can run it from source. Pizza Bot started as an internal passion project I worked on with a small team at Amazon. The whole thing came out of my frustration at having to manually log CRM activities through a browser form. I built a simple REST API called "JoeBot" that connected to my authenticated browser session over CDP and filled out the form for me using Playwright. Then I hacked up a quick Obsidian plugin so I could trigger it from my local notes (no AI and no MCP servers involved). This caught on quickly. My fellow AWS Solutions Architect Igor Fil joined up with me, and we rebranded the project as "Pizza Bot," named after Amazon's two-pizza teams. We started seeing what other automations we could build. We found a GraphQL API we could query and hacked up some "recipes" to pull data out of the CRM to help with meeting prep. That worked great, and it was right around the time MCP servers seemed to be taking off, so we decided to expose Pizza Bot as an MCP server instead, so it would be available to AI tools through natural language. This was a decent solution for technical users, but the Account Managers who live inside our CRM system wanted something too. We decided to rebuild Pizza Bot as an Electron desktop app modeled after an email inbox, so it would be familiar to non-technical users and would run on both Mac and Windows. We also bundled internal MCP servers as OCI images and hosted them in Amazon ECR as an "addon marketplace" so users could install them with one click without having to set up Amazon developer tooling. The project took off organically and expanded outside of AWS into the wider Amazon organization globally. More than 2,000 people ended up using it for meeting prep, email drafting, Slack summaries, CRM logging, prioritizing their day, and web research. Once apps like Claude Cowork and Amazon's own Quick Desktop came out, we realized the real growth opportunity was outside of Amazon. Rather than try to rip out the Amazon-specific integrations, we rebuilt Pizza Bot once more as an open source project. We leaned on coding agents heavily, which is the only reason a team our size could pull off a full rewrite. I'm pleased to say it's finally public, and we're hoping to bring in community members and see where it goes. We'd like to do for knowledge workers what Claude Code and Codex have done for programmers. A couple of things to know up front. Most of what made Pizza Bot useful on day one inside Amazon came from that internal catalog of skills and MCP servers for Amazon's own systems, and none of it could come out with the app. So it ships thinner than the version those 2,000 people used, and building that catalog back up for tools other people actually use is where we need the most help. It's also a community project and not an AWS service, so there's no support or SLA behind it. The Windows and Linux builds aren't signed yet either. On the technical side, Pizza Bot is a server and a client. The desktop app bundles both, or you can point a client at a remote backend; personally, I self-host the server on my home network and reach it from my phone over Tailscale. The server owns the thread lifecycle and checkpoints state with DeepAgents and LangGraph, and clients rehydrate from it as needed, so you can disconnect mid-run and pick the thread back up from another client. Approval pauses outlive the session that created them and collect in an Action filter, so you can answer an hour later from a different device. The agent you talk to has a sandboxed QuickJS interpreter that can reach your filesystem only if you grant it a folder, but its main job is to delegate. Each subagent is a 1:1 mapping of a Skill, and an Activity bar shows that subagent and the tool calls it's making as it works. Memory is opt-in and stored as plain markdown files on your machine. Every tool call is explicit, including looking up a memory - we err on the side of transparency to reduce surprises. Tools come from MCP servers, and skills are ordinary SKILL.md files with a per-tool approval policy, so existing skills that don't require a code interpreter should still work. What I'd most like to hear about is where the app itself gets in your way, the kind of problem you can't fix by writing a skill or an MCP server. I'm around today to answer questions!
9 by jd_ | 2 comments on Hacker News.
Hi HN - long-time lurker (since 2012!), first time poster. Pizza Bot is a self-hosted desktop app for Mac, Windows, and Linux that runs AI agents in the background and exposes them through an email-like UI. Finished work shows up in Unread, and anything waiting on your approval shows up in Action. It's Apache 2.0-licensed, there's no signup and no telemetry, and you bring your own model provider: Anthropic, Amazon Bedrock, Google Gemini, OpenAI, OpenRouter, or a local model through Ollama. There are builds on the releases page, or you can run it from source. Pizza Bot started as an internal passion project I worked on with a small team at Amazon. The whole thing came out of my frustration at having to manually log CRM activities through a browser form. I built a simple REST API called "JoeBot" that connected to my authenticated browser session over CDP and filled out the form for me using Playwright. Then I hacked up a quick Obsidian plugin so I could trigger it from my local notes (no AI and no MCP servers involved). This caught on quickly. My fellow AWS Solutions Architect Igor Fil joined up with me, and we rebranded the project as "Pizza Bot," named after Amazon's two-pizza teams. We started seeing what other automations we could build. We found a GraphQL API we could query and hacked up some "recipes" to pull data out of the CRM to help with meeting prep. That worked great, and it was right around the time MCP servers seemed to be taking off, so we decided to expose Pizza Bot as an MCP server instead, so it would be available to AI tools through natural language. This was a decent solution for technical users, but the Account Managers who live inside our CRM system wanted something too. We decided to rebuild Pizza Bot as an Electron desktop app modeled after an email inbox, so it would be familiar to non-technical users and would run on both Mac and Windows. We also bundled internal MCP servers as OCI images and hosted them in Amazon ECR as an "addon marketplace" so users could install them with one click without having to set up Amazon developer tooling. The project took off organically and expanded outside of AWS into the wider Amazon organization globally. More than 2,000 people ended up using it for meeting prep, email drafting, Slack summaries, CRM logging, prioritizing their day, and web research. Once apps like Claude Cowork and Amazon's own Quick Desktop came out, we realized the real growth opportunity was outside of Amazon. Rather than try to rip out the Amazon-specific integrations, we rebuilt Pizza Bot once more as an open source project. We leaned on coding agents heavily, which is the only reason a team our size could pull off a full rewrite. I'm pleased to say it's finally public, and we're hoping to bring in community members and see where it goes. We'd like to do for knowledge workers what Claude Code and Codex have done for programmers. A couple of things to know up front. Most of what made Pizza Bot useful on day one inside Amazon came from that internal catalog of skills and MCP servers for Amazon's own systems, and none of it could come out with the app. So it ships thinner than the version those 2,000 people used, and building that catalog back up for tools other people actually use is where we need the most help. It's also a community project and not an AWS service, so there's no support or SLA behind it. The Windows and Linux builds aren't signed yet either. On the technical side, Pizza Bot is a server and a client. The desktop app bundles both, or you can point a client at a remote backend; personally, I self-host the server on my home network and reach it from my phone over Tailscale. The server owns the thread lifecycle and checkpoints state with DeepAgents and LangGraph, and clients rehydrate from it as needed, so you can disconnect mid-run and pick the thread back up from another client. Approval pauses outlive the session that created them and collect in an Action filter, so you can answer an hour later from a different device. The agent you talk to has a sandboxed QuickJS interpreter that can reach your filesystem only if you grant it a folder, but its main job is to delegate. Each subagent is a 1:1 mapping of a Skill, and an Activity bar shows that subagent and the tool calls it's making as it works. Memory is opt-in and stored as plain markdown files on your machine. Every tool call is explicit, including looking up a memory - we err on the side of transparency to reduce surprises. Tools come from MCP servers, and skills are ordinary SKILL.md files with a per-tool approval policy, so existing skills that don't require a code interpreter should still work. What I'd most like to hear about is where the app itself gets in your way, the kind of problem you can't fix by writing a skill or an MCP server. I'm around today to answer questions!
New ask Hacker News story: Ask HN: Slow OpenAI Inference on AWS Bedrock
Ask HN: Slow OpenAI Inference on AWS Bedrock
2 by timedude | 1 comments on Hacker News.
Inference on AWS Bedrock for OpenAI models has been very slow and glitchy the last few days with today being the worst. Very long latency of over 5 minutes to first token. What's going on?
2 by timedude | 1 comments on Hacker News.
Inference on AWS Bedrock for OpenAI models has been very slow and glitchy the last few days with today being the worst. Very long latency of over 5 minutes to first token. What's going on?