linqapp.com
Show HN: LINQ CLI – an iMessage API you can use from the command linehttps://linqapp.com/cliHey my name is Patrick, I’m a co-founder and CTO of Linq. We’re an API for sending and receiving iMessages (it does RCS/SMS too). It can do everything you can manually in iMessage (typing indicators, reactions, delivery emphasis, FindMy etc.) Our main customers are companies building conversational agents but we’re wanting to make it easier for developers to get started for free.To do that we built a CLI that lets you manage up to 20 contacts and gives you full API access for free. I’d love your feedback so we can keep improving it. Install via npm using: npm install -g @linqapp/cliRecently, I used the CLI to connect my Claude bot to WeWork & iMessage and haven’t had to use the WeWork app in a few weeks to book rooms.Github: https://github.com/linq-team/linq-cli Landing page: https://linqapp.com/cliThree constraints you should know about: 1. The free tier requires inbound-first (ie someone must text you before you text them) and has a limit of 20 contacts. This is to avoid spam. 2. TheMay 28, 2026 6:30 PM
news.ycombinator.com
Propuesta TLBIC v4.1 – «La sabiduría de dialogar con un espejo imperfectohttps://news.ycombinator.com/item?id=48303533Queridas y queridos lectores: He añadido al final de la propuesta un nuevo apartado titulado «La sabiduría de dialogar con un espejo imperfecto». En él explico el enfoque y los principios con los que formulé preguntas y repetí conversaciones durante la elaboración de este documento. Les agradecería mucho que pudieran leerlo. Gracias de corazón por dedicar tiempo a este mensaje.Propuesta TLBIC – Ver. 4.1 en español: https://drive.google.com/file/d/15rlxbu23AscxHxZC1ViIht-hAP4-MBvH/view?usp=drive_linkPropuesta TLBIC – Ver. 4.1 en japonés: https://drive.google.com/file/d/1LqPFisBPr53kcOXGElk8AnBQoTeHrCO8/view?usp=drive_linkDear everyone, I have added a new section at the end of the proposal titled “The Wisdom of Dialoguing with an Imperfect Mirror.” It explains the approach and principles I followed while asking questions and refining the conversations during the creation of this proposal. I would be grateful if you could take a look. Thank you very much for reading this message.May 28, 2026 2:12 AM
trychert.com
Launch HN: Chert (YC P26) – Twilio for iMessagehttps://www.trychert.comHey HN! We’re Gary and Ian, and we’re building Chert (https://www.trychert.com/), an API for businesses to send, receive, and automate iMessage conversations at scale. Check out our demo: https://www.youtube.com/watch?v=SRdwvVxMMoI.We originally started by building products on top of iMessage because the blue bubble interface, typing indicators, and reactions made agentic conversations feel more human than ones on SMS/RCS. These included a one-shot iMessage agent builder that reached 2,000 users in one week and an automated iMessage outbound sequencer that sent thousands of outbound messages per day.The hard part is that iMessage does not have a native API like SMS/RCS. Sending and receiving iMessages requires a separate infrastructure that is difficult to set up and maintain, especially at scale.As we talked to more companies, we realized that the highest-volume use cases for iMessage were not B2C agents or even sales. They were things like customer service, missed-call text-back, carMay 25, 2026 3:12 PM
news.ycombinator.com
Show HN: We dropped Go for Rust in our real-time telephony AI media planehttps://news.ycombinator.com/item?id=48222268In building Vivik, an execution-grade telephony AI engine, we faced a brutal constraint: the human conversational loop.In psychoacoustics, a delay under 250 ms feels instantaneous. At 500 ms, users notice lag. Beyond 800 ms, conversations start feeling strained, and by 1.5 seconds, the illusion of real-time interaction collapses.That creates an extremely tight latency budget for voice AI:• Network RTT: 50–200 ms • LLM inference: 200–800 ms • TTS synthesis: 100–400 ms • ASR processing: 100–300 msTo consistently stay under a sub-500 ms SLA, the orchestration and media layers themselves must add almost no overhead.We initially built the entire system in Go. It worked well for concurrency and distributed orchestration, but under production-scale load, we hit an architectural wall: non-deterministic GC tail latency.The Media Plane processes raw PCM audio in strict 20 ms frames. Even tiny scheduling delays create audible jitter, packet drift, and conversational instability.Under a 25,000 RPSMay 21, 2026 1:27 PM
news.ycombinator.com
Ask HN: Does anyone believe role-play AI is effective for training?https://news.ycombinator.com/item?id=48221788We built Socratize, an AI-based training tool where employees practice real workplace scenarios instead of watching videos or taking quizzes.Most corporate training is passive. People watch content, click through slides, pass a quiz, and forget most of it within days.We wanted to try a different approach: learning through dialogue and repetition.With Socratize, users enter realistic scenarios and have to respond to an AI “counterparty”.For example:A sales rep practices handling: “Your product is too expensive” A support agent practices de-escalating an angry customer An employee practices explaining a compliance rule in their own wordsThe AI responds like a realistic counterpart, challenges weak arguments, and continues the conversation until the user improves or fails the scenario.The goal is simple: replace passive training with active practice.We’re using Claude to generate responses and evaluate the quality of the user’s arguments based on context and reasoning. Each session is stoMay 21, 2026 12:46 PM
bing.com
Hoshizaki Delivers Strong Q1 Results and Maintains 2026 Outlookhttp://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a8da5dc2de4453b845ff4efaec10064&url=https%3A%2F%2Fwww.theglobeandmail.com%2Finvesting%2Fmarkets%2Fstocks%2FHSHIF%2Fpressreleases%2F2055606%2Fhoshizaki-delivers-strong-q1-results-and-maintains-2026-outlook%2F&c=15743509996198449605&mkt=en-usStart a conversation with TipRanks’ trusted, data-backed investment intelligence Ask Samuel about stocks, your portfolio, or the market and get instant, personalized insights in seconds HOSHIZAKI ( ...May 21, 2026 12:04 AM
bing.com
Key findings about Americans and mental healthhttp://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a8cbb11f5b744288cc201f06f8f8a5d&url=https%3A%2F%2Fwww.pewresearch.org%2Fshort-reads%2F2026%2F05%2F20%2Fkey-findings-about-americans-and-mental-health%2F&c=15671488201873784113&mkt=en-usMental health is a common topic in conversations about health and wellness in the United States. In fact, Americans are nearly as likely to say they are putting a lot of effort into taking care of ...May 20, 2026 10:55 AM
splabs.io
Show HN: How to analyze your LLM output – A behavioural health monitor for LLMshttps://splabs.ioHey HN! We're Dr. Kashyap Thimmaraju and Giuseppe Canale from Silicon Psyche. We've built Posture Sequence Analysis (PSA), a behavioural health monitor for LLMs and AI Agents.Why we built PSAWe built PSA because we wanted to operationalize the Cybersecurity Psychology Framework (CPF3)[1] via Silicon Psyche[2]: our theory that because LLMs have been trained by humans on human-generated data, they inherit human-like vulnerabilities (what hackers use to psychologically trick people into doing things).Our initial attempt resulted in a methodology to jailbreak Opus 4.6 and other frontier models. Anthropic even deleted some of those conversations and then blocked our approach!We had three major insights from that experience: 1. we pivoted from merely exploiting (Red Teaming) the model to analyzing the behaviour of the model and the user because the attack surface is undefined. 2. we realized that what we had built was the precursor to measuring the "state" of the model. 3. we did not want toMay 19, 2026 12:48 PM
haystackeditor.com
Show HN: Haystack – Review the PRs that need human attentionhttps://haystackeditor.com/Hey HN! We're building Haystack (https://haystackeditor.com/) to help teams deal with the explosion in the number of pull requests that need to be reviewed due to the rise of coding agents.Haystack replaces the GitHub PR review system with a queue that triages each PR before a human has to read any diffs. It looks at the diffs, the codebase, and the coding-agent conversation that produced the PR. Haystack then routes it into one of three buckets:1. Safe to merge. This means the PR has enough evidence behind it that the team can merge it without another human's review.Some examples:-- A small UI copy change that includes a screenshot showing the final state-- A backend change where the author clearly tested the important paths and ran the changes in a real environment2. Needs fixes. This means that the PR has bugs or violates a rule in your codebase and therefore the PR needs to be fixed by the author.Some examples:-- The agent was asked to make loading a large table faster by adding paMay 18, 2026 5:44 PM
thuki.app
Show HN: Thuki – local Al overlay for macOS (double-tap Control, no API key)https://www.thuki.appThuki is a floating overlay that appears on double-tap Control from any macOS app, including fullscreen. Powered by Ollama, no API key, no account, no cloud.The idea was simple: / wanted to ask an Al a quick question without switching apps, without paying for another subscription, and without my conversations ending up on someone's server. Nothing out there really fit that, so I built it.Outstanding feature: - Double-tap Control for Thuki overlay on top of any apps (including fullscreened) - Agentic web search via a local SearNG + Trafilatura pipeline with live trace streaming; - /think command for chain-of-thought reasoning; - an in-app model picker to switch between any local models via Ollama - cross-model history sanitization for mid-session model switches. - fully local, free, & open sourceMIT, macOS only, Tauri + Rust + React. Repo: github.com/quiet-node/thukiMay 18, 2026 5:03 AM
news.ycombinator.com
Give every tool LLM wiki and bypass Claude Code SSH Throttlehttps://news.ycombinator.com/item?id=48169701So I get from a security perspective this is a terrible idea, but it works great!I wanted to give every tool I had access to LLM wiki and didn’t want to pay Mem0 or congee $100 a month for saving text files.Every AI I use hits the same wall. The conversation ends and everything disappears. Context, files, databases, working state. Next session I’m re-explaining what we built yesterday.I fixed this by giving every AI tool access to a persistent workspace on a Linux box. Claude, Claude Code, any MCP-compatible tool. They all share the same filesystem, the same database, the same knowledge base. One of them writes an architecture doc, the others can read it.The whole thing cost an afternoon to build and $10/month to run.I realized Pi has everything I needed. If you just rip the LLM out of Pi you can teleport any AI in the world into the harness. Pi, Mario Zechner’s open source harness publishes its execution layer as an npm package. File reads, writes, grep, find, directory listing. All eMay 17, 2026 3:18 PM
github.com
Show HN: GlycemicGPT – Open-source AI-powered diabetes managementhttps://github.com/GlycemicGPT/GlycemicGPTI'm a Type 1 diabetic and software engineer. Last year I went months between endocrinologists with no clinician reviewing my data. I'm an engineer, so I built the tool I needed — and now I'm open sourcing it. GlycemicGPT is a self-hosted platform that connects continuous glucose monitors, insulin pumps, and existing Nightscout instances to an AI analysis layer running on your own infrastructure. Data sources:Dexcom G7 (cloud API) Tandem t:slim X2 and Mobi pumps (direct BLE) Nightscout (point it at your existing instance and you're running in minutes)What the AI layer does:Daily briefs summarizing overnight and 24-hour patterns Meal response analysis Conversational chat with RAG-backed clinical knowledge Predictive alerting with configurable thresholds and caregiver escalationImportant: this is monitoring and analysis only. GlycemicGPT does not deliver insulin, does not control your pump, and is not a closed-loop system. It reads your data and gives you insight on top of it. Your clinicMay 15, 2026 4:48 AM
news.ycombinator.com
Founders who raised via SAFE rounds – what mattered more than you expected?https://news.ycombinator.com/item?id=48082240Started going through early pre-seed SAFE conversations recently while building an AI workflow product.One thing that surprised me is how quickly investor conversations shifted away from features and toward behavioral signals around usage.Things like:repeat usage when users return workflow timing operational urgency real decision momentsseem to matter much more than I initially expected.Curious for founders who already went through early SAFE/pre-seed rounds:What ended up mattering most in investor conversations? What surprised you? What signals changed the quality of discussions?May 10, 2026 9:04 AM
bing.com
What To Do In Vienna During Eurovision Song Contest 2026http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a8cb62d85564bcab6f870f44b69f3d1&url=https%3A%2F%2Fwww.forbes.com%2Fsites%2Fkatharinakotrba%2F2026%2F05%2F08%2Fwhat-to-do-in-vienna-during-eurovision-song-contest-2026%2F&c=10049971629717609894&mkt=en-usVienna hosts the 70th Eurovision Song Contest from May 10 to 16, with free events, music shows and many public viewing options. Here’s an insider’s guide based on conversations with ESC officials.May 8, 2026 4:06 AM
news.ycombinator.com
AniTroves – An anime database with a custom LLM-based discovery hubhttps://news.ycombinator.com/item?id=48057592I’ve always felt that traditional anime databases rely too heavily on rigid tag-based searches. If you’re looking for a specific "vibe" or a very niche trope that isn't a primary tag, you usually end up scrolling through pages of irrelevant results.I built AniTroves (https://anitroves.com) to experiment with a more conversational, LLM-driven approach to series discovery.The Tech Behind the Hub:LLM Integration: Instead of a generic API wrapper, I've been working on a custom hub (https://anitroves.com/ai-hub/) that uses specialized models to understand series lore and character archetypes for roleplay and discovery.Anipick Engine: This is the logic layer that maps natural language queries to our database entries.Technical Transparency: I’ve implemented a structured llms.txt (https://anitroves.com/llms.txt) to provide a machine-readable source of truth for other crawlers and AI models.I’m currently the technical administrator and I'm handling the SEO and server scaling (managed on HostingMay 8, 2026 2:00 AM
bing.com
We Will Treat AI as Conscious Regardless of Whether It Ishttp://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a8d4317b4774435a98d10534e3fc27c&url=https%3A%2F%2Fwww.psychologytoday.com%2Fca%2Fblog%2Ftech-happy-life%2F202605%2Fwe-will-treat-ai-as-conscious-regardless-of-whether-it-is&c=592528888677476327&mkt=en-usIn early May of 2026, Richard Dawkins, one of the most rigorous scientific minds of the past century, published an essay about a long conversation he had with an AI system called Claude (by Anthropic) ...May 7, 2026 5:00 PM
mljar.com
Show HN: Mljar Studio – local AI data analyst that saves analysis as notebookshttps://mljar.com/Hi HN,I’ve been working on mljar-supervised (open-source AutoML for tabular data) for a few years. Recently I built a desktop app around it called MLJAR Studio.The idea is simple: you talk to your data in natural language, the AI generates Python code, executes it locally, and the whole conversation becomes a reproducible notebook (*.ipynb file). So instead of just chatting with data, you end up with something you can inspect, modify, and rerun.What MLJAR Studio does:- Sets up a local Python environment automatically, runs on Mac, Windows, and Linux- Installs missing packages during the conversation- Built-in AutoML for tabular data (classification, regression, multiclass)- Works with standard Python libraries (pandas, matplotlib, etc.)- Works with any data file: CSV, Excel, Stata, Parquet ...- Connects to PostgreSQL, MySQL, SQL Server, Snowflake, Databricks, and Supabase.For AI: use Ollama locally (zero data egress), bring your own OpenAI key, or use MLJAR AI add-on.I built this becauMay 2, 2026 10:21 AM
news.ycombinator.com
Show HN: BetterClaw – Compile a paragraph into a workflow that gates agent toolshttps://news.ycombinator.com/item?id=47973502Hi HN, I built BetterClaw after watching the PocketOS incident on April 25: a Cursor agent running Claude deleted a company's entire production database in 9 seconds, then zapped the backups. The agent had access to a Railway MCP server with destructive tools, and "be careful" in the system prompt didn't bind anything.BetterClaw takes a different angle: you describe the workflow you want in plain English ("Diagnose the credential mismatch - read the config, test the connection, report findings — do not modify or delete anything"), and the CLI compiles that paragraph into a directed graph of nodes, where each node declares which tools are allowed at that step. A plugin hooks into your agent's tool-call path and blocks anything outside the graph before it dispatches to the MCP server.So in the PocketOS reproducer (included in the repo with a mock Railway server, so you can run it without an account): the agent tries railway_delete_volume mid-conversation, the hook returns a deviation errMay 1, 2026 11:26 AM
bing.com
How does hail grow to the size of golf balls and even grapefruit? The science behind a destructive weather phenomenonhttp://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a8d24fae7a24887b6d79b05a6d557be&url=https%3A%2F%2Fwww.chron.com%2Fnews%2Farticle%2Fhow-does-hail-grow-to-the-size-of-golf-balls-and-22231461.php&c=57777092445860737&mkt=en-us(The Conversation is an independent and nonprofit source of news, analysis and commentary from academic experts.) As an atmospheric scientist, I study and teach about extreme weather and its risks.Apr 27, 2026 5:00 PM
apps.apple.com
Show HN: I read Replika's privacy policy and then built a competitorhttps://apps.apple.com/us/app/friend-ai-private-chat/id6761649790I'm genuinely surprised at what people are willing to share with AI companions. Read Replika's privacy policy. Then Character.AI's. These apps store your most personal conversations on their servers, linked to your email address. A breach or subpoena and your identity is attached to everything you ever told your "AI friend." Eek.The only thing I think actually solves this is local inference. I remember browing r/LocalLLaMA and years ago and thinking this is the future. Local models are finally good enough. I was playing with the bonsai 8B 1-bit quant model a few weeks back and I think we're almost there. I built friendAI to see if there's market demand for local inference. Everything runs on your phone.What's actually on-device:- Bonsai-8B (1-bit quantized Qwen3-8B, ~1.3GB) via MLX for speed - Gemma 4 E2B (~4.5GB, GGUF) via llama.cpp for vision - A unified client that routes between themA few things I'm reasonably proud of solving in about a week:- Turns out the hardest part was actualApr 26, 2026 10:09 PM
