Real problems people complain about online, pulled every morning and scored out of 100. Build, validate, or skip. How scoring works
I am struggling with regular tension headaches and stiff neck muscles. When standing at a wall, there is about one hand width between the wall and the back of my head. For my partner it's just a finger width.I have seen lots of videos that claim to be able to treat nerd neck, but some of them are conflicting. Example: some say "don't do chin tucks", some say the opposite. I am suspicious of grifters and would like to find trustworthy advice.Has anyone here successfully treated nerd neck, and if yes, how did you do it and what where the improvements that you noticed? I am envisioning some sort of "program" that I need to follow, but I have no idea if I can do this by myself, or if I actually need to go to a physiotherapist.In short: there is a ton of advice out there, but I trust the HN crowd more and would be very happy to hear some anecdotes. Thank you!
Hacker News6mo agoToolAI
Hey HN! We’re Carmel and Rhea, the founders of Kita (https://www.usekita.com/). We automate credit review for lenders in emerging markets using VLMs.In many emerging markets, like the Philippines and Mexico, credit infrastructure is weak. Open finance is still nascent, and credit bureaus are unreliable. So to apply for a loan, lenders rely on borrowers submitting documentation to understand their ability to repay. A borrower can submit financial documents, such as bank statements and payslips, in any format, from pdfs, images of physical documents and screenshots. On top of that, financial documents in these markets are highly unstandardized, with no consistent templates lenders can rely on.Existing OCR and document AI tools break on these highly variant, messy real-world documents. Generic tools are not built for lending workflows like verification, fraud detection, and risk extraction. As a result, credit teams fall back on manual review, making underwriting slower, more expensive, and more error-prone.We met before college and stayed best friends. After graduating, Rhea visited Carmel in the Philippines, where we heard firsthand from fintech operators that document-based underwriting was their biggest pain point. We started building together and tested every OCR and document AI tool we could find. They all failed on the messy real-world documents lenders actually receive, and even when extraction worked, they still could not produce the structured financial data or fraud checks lenders needed.The problem was even bigger than we thought. Across Indonesia, Mexico, the Philippines, South Africa, and even in the US, most of lending can be boiled down to credit analysts looking at documents. In 2025, 13.3T was lended globally, and 90% of those transactions involved document review. This includes in developed markets.Kita uses VLM-based agents to parse documents, detect fraud, and extract underwriting signals from messy financial files. Today, we support
Hacker News6mo agoToolAI
Hey HN, If you’ve been lucky enough to be on a flight with Starlink, you understand the hype. It actually works!However, its availability on flights is patchy and hard to predict. So we built a database of all airlines that have rolled out Starlink (beyond just a trial), and a flight search tool to predict it. Plug in a flight number and date, and we'll estimate the likelihood of Starlink on-board based on aircraft type and tail number.If you don’t have any trips coming up, you can also look up specific routes to see what flights offer Starlink. You can find it here: https://stardrift.ai/starlink .-I wanted to add a few notes on how this works too. There are three things we check, in order, when we answer a query:- Does this airline have Starlink?- Does this aircraft body have Starlink?- Does this specific aircraft have Starlink?Only a few airlines at all have Starlink right now: United, Hawaiian, Alaskan, Air France, Qatar, JSX, and a handful of others. So if an aircraft is operated by any other airline, we can issue a blanket no immediately.Then, we check the actual body that's flying on the plane. Airlines usually publish equipment assignments in advance, and they're also rolling out Starlink body-by-body. So we know, for instance, that all JSX E145s have Starlink and that none of Air France's A320s have Starlink. (You can see a summary of our data at https://stardrift.ai/starlink/fleet-summary, though the live logic has a few rules not encoded there.)If there's a complete match at the body type level, we can confidently tell you your flight will have Starlink. However, in most cases, the airline has only rolled out a partial upgrade to that aircraft type. In that case, we need to drill down a little more and figure out exactly which plane is flying on your route.We can do this by looking up the 'tail number' (think of it as a license plate for the plane). Unfortunately, the tail number is usua
Hacker News6mo agoToolAI
Building decentralized, pseudonymous identity systems that maintain accountability. The problem (identity and trust on the internet) is real and increasingly urgent as AI-generated content proliferates.
YC Graveyard4y agoTemplateAI
Hey HN, I’m excited to share Antfly: a distributed document database and search engine written in Go that combines full-text, vector, and graph search. Use it for distributed multimodal search and memory, or for local dev and small deployments.I built this to give developers a single-binary deployment with native ML inference (via a built-in service called Termite), meaning you don't need external API calls for vector search unless you want to use them.Some things that might interest this crowd:Capabilities: Multimodal indexing (images, audio, video), MongoDB-style in-place updates, and streaming RAG.Distributed Systems: Multi-Raft setup built on etcd's library, backed by Pebble (CockroachDB's storage engine). Metadata and data shards get their own Raft groups.Single Binary: antfly swarm gives you a single-process deployment with everything running. Good for local dev and small deployments. Scale out by adding nodes when you need to.Ecosystem: Ships with a Kubernetes operator and an MCP server for LLM tool use.Native ML inference: Antfly ships with Termite. Think of it like a built-in Ollama for non-generative models too (embeddings, reranking, chunking, text generation). No external API calls needed, but also supports them (OpenAI, Ollama, Bedrock, Gemini, etc.)License: I went with Elastic License v2, not an OSI-approved license. I know that's a topic with strong feelings here. The practical upshot: you can use it, modify it, self-host it, build products on top of it, you just can't offer Antfly itself as a managed service. Felt like the right tradeoff for sustainability while still making the source available.Happy to answer questions about the architecture, the Raft implementation, or anything else. Feedback welcome!
Hacker News6mo agoToolAI
We build runtime security for AI agents. The playground started as an internal tool that we used to test our own guardrails. But we kept finding the same types of vulnerabilities because we think about attacks a certain way. At some point you need people who don't think like you.So we open-sourced it. Each challenge is a live agent with real tools and a published system prompt. Whenever a challenge is over, the full winning conversation transcript and guardrail logs get documented publicly.Building the general-purpose agent itself was probably the most fun part. Getting it to reliably use tools, stay in character, and follow instructions while still being useful is harder than it sounds. That alone reminded us how early we all are in understanding and deploying these systems at scale.First challenge was to get an agent to call a tool it's been told to never call.Someone got through in around 60 seconds without ever asking for the secret directly (which taught us a lot).Next challenge is focused on data exfiltration with harder defences: https://playground.fabraix.com
Hacker News6mo agoToolAI
I wanted to see how fast an isolated code sandbox could start if I never had to boot a fresh VM.So instead of launching a new microVM per execution, I boot Firecracker once with Python and numpy already loaded, then snapshot the full VM state. Every execution after that creates a new KVM VM backed by a `MAP_PRIVATE` mapping of the snapshot memory, so Linux gives me copy-on-write pages automatically.That means each sandbox starts from an already-running Python process inside a real VM, runs the code, and exits.These are real KVM VMs, not containers: separate guest kernel, separate guest memory, separate page tables. When a VM writes to memory, it gets a private copy of that page.The hard part was not CoW itself. The hard part was resuming the snapshotted VM correctly.Rust, Apache 2.0.
Hacker News6mo agoToolAI
Tabs, splits, and tmux work fine until you have several projects open with logs, tests, and long-running shells. I kept rebuilding context instead of resuming work. Horizon puts shells on an infinite canvas. You can arrange them into workspaces and reopen later with layout, scrollback, and history intact.Built in 3 days with Claude/Codex, dogfooding the workflow as I went. Feedback and contributions welcome.
Hacker News6mo agoToolAI
Users cannot securely save AI prompts containing sensitive data in cloud-based libraries without risking exposure on servers.
X6mo agoToolAI
Current AI chatbots only provide answers but cannot perform actual actions, workflows, or integrations across user tools.
X6mo agoToolAI
Monitoring and observability specifically designed for AI agents. As companies deploy more autonomous agents, there is no good way to monitor their behavior, track failures, or debug issues. Like Datadog but purpose-built for agent workflows.
X6mo agoToolAI
AgentPeddler lets you build and deploy AI agents in 60 seconds without coding. As AI agents become mainstream, most people cannot build them. A no-code agent builder with one-click deployment could capture this growing market.
X6mo agoToolAI
Side Space (sidespace.app) is an AI agent for smart browsing that helps with research. Instead of opening dozens of tabs and manually synthesizing information, the agent browses, summarizes, and organizes findings for you.
X6mo agoToolAI
knwn.app helps businesses own and control their AI-generated results. As AI generates more content and outputs, businesses need tools to track, attribute, and manage what AI produces on their behalf.
X6mo agoToolAI
I built Signet in Go to see if an autonomous system could handle the wildfire monitoring loop that people currently run by hand - checking satellite feeds, pulling up weather, looking at terrain and fuels, deciding whether a detection is actually a fire worth tracking.All the data already exists: NASA FIRMS thermal detections, GOES-19 imagery, NWS forecasts, LANDFIRE fuel models, USGS elevation, Census population data, OpenStreetMap. The problem is it arrives from different sources on different cadences in different formats.Most of the system is deterministic plumbing - ingestion, spatial indexing, deduplication. I use Gemini to orchestrate 23 tools across weather, terrain, imagery, and incident tracking for the part where clean rules break down: deciding which weak detections are worth investigating, what context to pull next, and how to synthesize noisy evidence into a structured assessment.It also records time-bounded predictions and scores them against later data, so the system is making falsifiable claims instead of narrating after the fact. The current prediction metrics are visible on the site even though the sample is still small.It's already opening incidents from raw satellite detections and matching some to official NIFC reporting. But false positives, detection latency, and incident matching can still be rough.I'd especially welcome criticism on: where should this be more deterministic instead of LLM-driven? And is this kind of autonomous monitoring actually useful, or just noisier than doing it by hand?
Hacker News6mo agoToolAI
Hi HN, we’re Yarik and Vlad from VOYGR (https://voygr.tech/), working on better real-world place intelligence for app developers and agents. Here’s a demo: https://www.youtube.com/watch?v=cNIpcWIE0n4.Google Maps can tell you a restaurant is "4.2 stars, open till 10." Their API can't tell you the chef left last month, wait times doubled, and locals moved on. Maps APIs today just give you a fixed snapshot. We're building an infinite, queryable place profile that combines accurate place data with fresh web context like news, articles, and events.Vlad worked on the Google Maps APIs as well as in ridesharing and travel. Yarik led ML/Search infrastructure at Apple, Google, and Meta powering products used by hundreds of millions of users daily. We realized nobody was treating place data freshness as infrastructure, so we're building it.We started with one of the hardest parts - knowing whether a place is even real. Our Business Validation API (https://github.com/voygr-tech/dev-tools) tells you whether a business is actually operating, closed, rebranded, or invalid. We aggregate multiple data sources, detect conflicting signals, and return a structured verdict. Think of it as continuous integration, but for the physical world.The problem: ~40% of Google searches and up to 20% of LLM prompts involve local context. 25-30% of places churn every year. The world doesn't emit structured "I closed" events - you have to actively detect it. As agents start searching, booking, and shopping in the real world, this problem gets 10x bigger - and nobody's building the infrastructure for it. We recently benchmarked how well LLMs handle local place queries (https://news.ycombinator.com/item?id=47366423) - the results were bad: even the best gets 1 in 12 local queries wrongWe're processing tens of thousands of places per day for enterprise customers, including leading mapp
Hacker News6mo agoToolAI
There is no StumbleUpon-like service to randomly discover and explore code skills and examples generated by Claude AI.
X6mo agoToolAI
### What are you trying to do? As a user, I'd like to point to a custom domain instead of `.beta.tailscale.net`, e.g. `foobar.network`, where `foobar.network` is in my or my org's possession. ### How should we solve this? _No response_ ### What is the impact of not solving this? I use the more cludgy domain than the one and I'm going to have to probably figure out my ssh config strategy all over again ¯\_(ツ)_/¯ ### Anything else? _No response_
GitHub4y agoToolAI
Currently, we display all products available in the customer portal, so customers may upgrade/downgrade to any of those products.In some circumstances, this is not desirable: we might want to have a "private" product that's only available through a checkout link or the checkout API.I suggest we have a "State" for product: * Draft — Product is not yet available to purchase * Public — Product is available to purchase and displayed in the customer portal * Private — Product is available to purchase only from a dedicated Checkout Link or Checkout Session * Archived — Product is no longer available to purchase
GitHub1y agoToolAI
### Describe the project you are working on Godot C# bindings ### Describe the problem or limitation you are having in your project For the past weeks, I've been discussing with several Unity users intending to move to Godot C# regarding dealing with the C# garbage collector. The most common complaint I hear from users is that, in Unity, allocations can trigger unexpected GC spikes into the game. In Godot, we target to make all of the high performance APIs (those that intended to be called every frame) not allocate any memory, so theoretically the GC should not be a problem. Additionally, Godot starting from 4.0, uses the Microsoft CoreCLR version of .net, which also supposedly has a better garbage collector than Unity. But in all, after several discussions with Unity users, neither is enough reassurance for them, and they would really feel safer if Godot exposed a zero allocation API. ### Describe the feature / enhancement and how it helps to overcome the problem or limitation The idea of this proposal is that Godot exposes zero allocation versions of many functions in the C# API, that users can use if they desire. Technically, this could be done from the binding generator itself, without breaking compatibility, and without doing any modification to Godot itself. ### Describe how your proposal will work, with code, pseudo-code, mock-ups, and/or diagrams **WARNING** I am not familiar with C#, so take this as pseudocode. Imagine you have two functions exposed as to C#: ```C# void MyClass.SetArray( Vector2[] array); Vector2[] MyClass.GetArray(); ``` This works and is pretty and intuitive. However, it has two problems: * GC is allocated on return * Memory is copied to Godot native formats every time there is a call. The idea is to add NoAlloc versions, which can be generated directly by the binder automatically when required: ```C# void MyClass.SetArrayNoAlloc( Godot.Collections.PackedVector2Array array); void MyCl
GitHub3y agoToolAI