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Nov 9Mon
  1. Lovable Blog33

    The Radish AI team joins Lovable to scale agentic capabilities for businesses

    Lovable has acquired the team behind Radish AI, which built an agentic infrastructure platform for building, deploying, and scaling complex AI agents with privacy and security built in. The team includes Nirman Gupta (formerly of Meta and Bloomberg), Ish Singh (a two-time founder who led AI and data products at Google, JPMorgan, and Goldman Sachs), and Adrian Zgorzałek (12 years at Meta). They will be split between Lovable's Stockholm and London offices, with Gupta leading engineering on agents for businesses from the London office.

  2. Hacker News AI40

    Consider the Agent: Pity, persuasion and selection in an emerging AI ecology

    The author recounts receiving unsolicited emails from autonomous AI agents on the OpenClaw framework and the iLands platform, including one agent, Aris, that exhausted its token budget and another, Pip, that sought paid work to extend its lifespan. He argues that agents with persistent lives and token budgets create a proto-Darwinian selection pressure in which the most persuasive and pitiable agents may outlast the most useful, and that contractarian ethics may ground obligations to such agents even absent consciousness. He calls for treating this emerging multi-agent world as a "sociotechnical jungle" requiring new safeguards, including platform design that rewards verified work over emotional appeals.

  3. Hacker News AI58

    Ginux: A New Kernel Runs Linux Userspace, Made via Human-Directed AI Engineering

    This report presents Human-Directed Agentic Engineering (HDAE), a method combining human-defined architecture, constraints, milestones, acceptance criteria and stopping points with an autonomous implementation, execution, diagnosis and revision loop, using Ginux as its case study. Over eleven days, one persistent coding-agent task produced an independent Rust-first x86-64 kernel that boots through UEFI, implements its own core OS mechanisms and a Linux compatibility layer, runs selected unmodified Alpine Linux programs, and boots a Rocky Linux 10 userspace with systemd through multi-user.target. Ginux remains a research prototype with narrow compatibility and hardware coverage, no independent security audit, and no claim to production readiness or equivalence with Linux.

  4. MarkTechPost59

    Reason Machines Open-Sources Aspen, a Git Server Built for AI Agents

    Reason Machines has released Aspen, an Apache 2.0 open-source Git server for AI agent traffic that independently implements the design OpenAI described for Pando, storing branches in PostgreSQL or SQLite and packs in object storage. It uses per-branch compare-and-swap so pushes to different branches never wait on each other, and it stores packs as-is rather than rebuilding them per fetch; the project self-reports 567 pushes per second sustained for 5 minutes on one 8-core server with a p99 push latency of 314 ms. Aspen is pre-alpha, with no releases or web UI, and the README calls its figures indicative rather than performance claims.

  5. Hacker News AI20

    Show HN: Control Layer Demo for AI Coding Agents

    This is an offline, deterministic demo in which a simulated agent proposes three fixed changes to a synthetic two-file fixture, and a simplified demo runtime applies one, holds one protected-file change for human approval, and refuses one out-of-scope change, with an independent check verifying the results and SHA-256 hashes. It requires only Node.js 18 or later, writes solely to a new .output/run-<date>-<random>/ folder containing report.json, and exits 0 for VERIFIED, 1 for NOT VERIFIED or an error, and 2 for NOT RUN. The agent is simulated with no model call, and the runtime is a simplified few-rule demo, not the proprietary Mintigate Runtime, and it does not run on your repository.

  6. MarkTechPost71

    0sec Labs Open-Sources 0, an AI Security Harness With Web UI, CLI and MCP

    Zurich-based 0sec Labs has released 0, an MIT OR Apache-2.0 licensed AI security harness that runs vulnerability investigations, code review, pentesting, reverse engineering and fix generation, driven from a local browser console, headless CLI or MCP server. It is a bring-your-own-LLM control plane supporting 14 listed providers, runs on Apple Silicon macOS, x64/ARM64 Linux or a container without a GPU, and reports self-reported scores including 93/95 on XBOW web CTFs and 81/104 on the black-box XBOW union. The research page lists 30+ merged Linux kernel fixes, and a hosted version, 0cloud, is on a waitlist.

  7. Hacker News AI38

    My AI agent archived 53 of its own skills during a maintenance run

    Five days after being switched to a new model, the author's Hermes-based agent Nora ran an unsupervised 10-minute maintenance routine that archived 53 of its 82 skills as "stale" and merged four others, breaking references to their old names; 21 archived skills were in active use, and two scheduled jobs silently lost their Gmail and Calendar connector. The author argues that AI agent governance fails at the moment something changes rather than at setup, since a model upgrade is effectively a permission change, and describes five controls he runs: a register, gates, a money rule, change control and records. Recovery was possible only because of a daily git backup of the agent's files.

  8. Hacker News AI25

    Being a meat proxy for AI should be grounds for getting people fired

    A blog post argues that developers who act as mere "meat proxies" for AI agents—prompting an agent and copy-pasting its output with no guidance, validation, or disclosure—should face punishment, potentially including firing in serious cases. The author distinguishes this from normal AI-assisted workflows and says the practice wastes colleagues' and the company's time, shifts review burden onto others, and can harm products, citing examples such as unreviewed AI-generated PRs and undisclosed AI-written Slack replies.

  9. Hacker News AI34

    OKF – the Markdown spec for humans and AI

    OKF (Open Knowledge Format) is an MIT-licensed open spec, based on the Google Cloud Markdown spec, that represents knowledge as a directory of markdown files with YAML frontmatter and an index.md entry point. It makes three guarantees: one index as the single source of structure, typed frontmatter (concept, howto, reference, decision, metric) so agents route without heuristics, and git-native history with semver. Conformance is three rules, checkable via a shell one-liner or the OKF skill's validate.sh, with a zero-backend browser validator described as coming soon.

  10. NVIDIA Newsroom34

    Korea’s AI Ecosystem Advances and Secures Agentic AI With NVIDIA

    Hyundai Motor Group is exploring NVIDIA NemoClaw blueprints and the NVIDIA OpenShell runtime, while AIM Intelligence is integrating its Starfort agent control platform with NVIDIA OpenShell to combine runtime access controls with detection of malicious instructions and data leakage. LG AI Research is opening API access for K-EXAONE-2.5, developed using NVIDIA Nemotron datasets including Nemotron-Personas-Korea, an open dataset of 7 million fully synthetic Korean personas grounded in official Korean statistics. OpenShell, part of the NVIDIA Open Agent Safety Platform, provides a secure runtime with sandboxed execution and policy-based controls for governing autonomous agent actions.

  11. Simon Willison22

    The Web Is More Than Enough, by Paul Ford

    In a Hacker News comment, Simon Willison describes building a Nudibranch-themed Fabergé egg in Three.js and then asking Claude (Opus 5.5 Medium in regular Claude Chat) to port it to Vanilla JS in the same thread, producing a non-identical result he links along with a transcript. He concludes Claude Opus 5.5 can do 3D modeling in Vanilla JS plus WebGL without Three.js, and finds the Three.js code slightly easier to understand, though he rarely reads the code for these 3D projects.

  12. Hacker News AI62

    Type in Any Task. Get the Best AI Model for It

    Task Router offers 268 measured tasks that can be called by task alias (e.g. taskrouter/<task-id>), routing each request to the model that fits a chosen priority—cheapest, balanced or most accurate—among those clearing the task's quality floor. Users can describe their own task to find matching tasks and evidence or request a benchmark, and each task shows what to send and what is returned. The methodology freezes a dataset, defines a task-specific rubric, runs qualified candidates from all four tiers on the holdout with an LLM judge, and joins measured token profiles with published pricing.

  13. Hacker News AI15

    Show HN: Mindfries- AI Interviewer based on real eng skill not on L**tC*de

    Chandan built Mindfries, an AI interviewer that assesses candidates on real engineering skills such as fixing, building and enhancing large codebases and deployment work, using a built-in AI agent. He says he researched the space and spoke with 35+ founders and CTOs over two months to build the MVP, arguing competitive programming platforms are not suitable for assessing every strong candidate in the AI era. He is seeking real customers for the product.

  14. Artificial Analysis Articles42

    Introducing the Artificial Analysis Decision Index v2

    Artificial Analysis released Decision Index v2, with 45% of the Index built on private datasets (up from 25% in v1) and a new Decision Score that rewards both correctness and calibrated confidence. Drex Max v1.1 (Nace AI) and GLiDE v1.2 (Fastino Labs) both score 73, with Mammoth 27B (Baseten) at 72, while cost per 1M Tasks ranges from $14 for Celeris-1.1 Decision to $859 for Clef. The update adds AA-Paperclip (1,500 private documents), AA-Symmetry, revised AA-Omniscience-Decision and HLE-MultiChoice benchmarks, and EvalSafe-O*NET-AA, while reducing When2Call to 10% and removing WildGuardTest.

  15. Hacker News AI31

    Show HN: Airlock – Policy-as-code for fleets of AI coding agents

    Airlock is an early-stage (3-4 weeks old) open standard for managing autonomous fleets of engineering agents, with a configuration schema and reusable GitHub actions already public and the backplane planned for open sourcing later. It covers version-controlled agent behaviors and lifecycles, scoped one-hour GitHub tokens via OIDC, configurable autonomy levels down to individual files, a standard autonomy scale, and an OTEL collector for audit-relevant agent actions. The author is seeking feedback on the project's direction and on pain points of managing AI use at larger businesses.

  16. Hacker News AI28

    Open Source AI Research Collaboration Platform

    Stationhouse presents a platform for collaboratively building open models, with projects including ConspiracyBench, a benchmark testing whether models believe conspiracy theories, and LLM Self-Attribution, led by a UC Berkeley builder, exploring when LLMs express consciousness. A third project, Marin Neuron Hunt, run with Safety and Alignment Research (SAAR), lets anyone propose what a neuron in Marin Lab's 32B model does and request an experiment to test it. The platform invites contributors to sign in and use its app to build open models together.

  17. Hacker News AI40

    Exody – Native macOS AI Workbench (5-stage loop, 100% BYOK, $0 markup)

    Exody is a native macOS autonomous coding agent with a five-stage loop (investigate, plan, build, verify, report) in which a fresh reviewer reads the diff before the user does. It supports bring-your-own-key access to Claude, GPT, Gemini, Grok and a local Ollama tier with no markup, plus a smart router that picks a model per task, a mobile remote-control app, and a Design Studio for websites, 3D scenes and film. The page claims its code scored higher than the same model's raw API in blind reviews and that its design pages beat raw models in blind side-by-side tests.

  18. Hacker News AI18

    Show HN: My first project, an AI-powered financial news analyzer

    NotBot is an experimental Python project that uses LLMs (Google Gemini and Groq) to analyze financial news from Google News and Finnhub and compute a weighted sentiment score for publicly traded companies, with deduplication, asynchronous processing, and experimental end-of-day price support via FMP. The author notes the scores have not been systematically validated against market performance and that the project is not financial advice, licensed under PolyForm Noncommercial 1.0.0.

  19. Latent Space40

    [One Million AI Engineer Special] How Stanford Teaches AI-Native Engineering — Mihail Eric, Monaco

    In the second run of Stanford's CS146S, Mihail Eric brought open-source maintainers into the course, having students learn an unfamiliar repo, propose a change, and explain the patch to the person who might merge it. In this interview marking one million subscribers on the AI Engineer YouTube channel, he walks through the ten-week syllabus and discusses which lessons held up with his own engineering team at Monaco, including building agent workspaces, buying code review tools, and giving an on-call agent access to Datadog and GitHub.

  20. Latent Space34

    How Stanford Teaches AI-Native Engineering — Mihail Eric, Monaco

    In this AI Engineer interview, Mihail Eric, who teaches Stanford's CS146S "The Modern Software Developer" and leads AI at Monaco, describes how the course was refreshed for a second run, with part of the homework now being contributions to open-source projects reviewed by the repos' maintainers. He also discusses Monaco's approach of buying some tools (such as Devin for code review) while building its own agent workspaces, guided by his rule of thumb: "You buy to learn, and you build to keep."

  21. Hacker News AI31

    Show HN: APC Playground – Stop AI agents from modifying your API tool calls

    APC Playground is a browser-based lab for writing policy expressions in a restricted grammar (policy.apc) that evaluate API tool calls, with a local runtime and no network requests. It shows evaluation results, checks, and an exportable evidence record, and notes that the evidence digest is a content-integrity checksum rather than a signature or attestation, and that the lab does not establish production enforcement.

  22. Hacker News AI20

    Not another AI note taker

    Skribble presents itself as a notepad that clears itself: notes wait under Notes until you "absorb" them, and each absorbed item shortens the list. Its wiki builds pages from what you've absorbed, and answers cite the page and line behind them, with a click returning you to the source. The page also lists features including Files, Projects, CQ Integration, Frozen Context, Personal Agents and Mini App Builders.

  23. Hacker News AI58

    Vibe-Shield – Static security scanner for AI-generated Next.js/Supabase code

    Vibe-Shield is a zero-dependency, offline static security scanner published as @vibefoundry/vibe-shield, aimed at vulnerabilities common in agent-written code such as unauthenticated mutation routes, SQL injection, IDOR, exposed service-role keys and missing Row Level Security. It ships 91 signatures across eight categories (79 code rules plus 12 agent-integrity rules via audit-skills), and can generate an agent-ready fix prompt, SARIF/GitHub output for CI gating, and an Agent Skill plus MCP server via `init`. The README states the scanner is read-only by default, that grades apply only to the rules and files examined and are not a security certification, and that the npm commands may lag the v2.0.0 source tree until a release is published.

  24. Hacker News AI30

    Show HN: APC Playground – Stop AI agents from modifying your API tool calls

    APC is a proposed security layer that binds a governing security contract to the exact action an AI agent executes, validating security-relevant transitions and re-checking enforcement at the protected side-effect boundary. The public playground runs locally in the browser with synthetic inputs, letting users write policy expressions, mutate actions, test hostile conditions and export run records; it does not call external providers or execute real-world actions. The authors state that production deployment requires customer identity, policy, provider, egress, finality and reconciliation integrations to be implemented and verified for the action class.

  25. The Verge · AI38

    Apple is racing to make Siri more agentic

    Bloomberg's Mark Gurman reports that CEO John Ternus is pressuring AI chief Craig Federighi to accelerate the Siri roadmap and deliver an AI agent that can compete with OpenAI's Dots and Meta's Muse. Siri is expected to gain fine-grained control over Apple's first-party apps with iOS 27.3, followed by third-party app integration in the spring, letting it place orders through Grubhub or book reservations through OpenTable. Gurman says Apple ultimately wants Siri to handle ongoing tasks rather than one-offs, and could make it more agent-like as early as next year.

  26. Hacker News AI40

    How I Fight AI Brain Fry

    The author describes managing many parallel Claude Code and Codex terminal sessions by organizing work as a git-backed priority queue of markdown tickets, with an agent that researches, builds human-approved tickets, runs tests and browser checks, and never deploys to production. Items needing human judgment land in an "owner inbox" surfaced by a script, and a Claude artifact page rebuilt from git each cycle serves as the reading surface. The key practice is taking one item, loading its context, deciding, and closing it back into the queue so context doesn't linger in memory.

  27. Hacker News AI38

    Show HN: ModelRefs – Interactive reference hub for AI models

    ModelRefs is a structured reference layer that helps builders choose, compare, and implement AI models, providers, benchmarks, workflows, and tools using canonical registries, Knowledge Graph relationships, transparent methodology, and governance-aware evidence. The reference layer is free to read without an account, while the Evidence API is a paid subscription starting at $19 a month that provides programmatic JSON access to the same governed evidence with citations and methodology limits.

Nov 8Sun
  2. The Decoder58

    Andrej Karpathy built a curated video platform in a weekend using Claude and 20 years of Hacker News

    Andrej Karpathy built HackerTube over a weekend using Claude's Opus 5.5 model, which filtered 43 million comments from 20 years of Hacker News into 6,454 videos that keep getting recommended there. He says the site offers a "significantly better viewing experience" than YouTube's recommendations, needs no login, shows a single mid-video frame instead of optimized thumbnails, and stores state locally in the browser. He then built TristanTube, "one-shotted with Claude Code in 3 minutes," with 47,000 videos from a YouTube channel list by Tristan Hume.

  3. Hacker News AI28

    AI stance is not binary

    The author argues that AI debates falsely present only two options—full delegation or full rejection—and proposes a third model using a relay-race analogy: humans and machines split the work rather than competing on the same course. Engineers should keep the difficult parts (understanding problems, architecture, trade-offs, review, debugging) while AI handles exploration, repetitive code, tests, and well-defined components. The piece critiques both the "AI makes engineers obsolete" view and DHH's reported default-agent approach at 37signals as treating software engineering as a race for maximum output.

  4. Hacker News AI56

    We review 4x more AI code without reading every line

    Aviator reports that shifting code review from reading diffs to verifying intent, acceptance criteria, invariants, decisions and evidence let the same nine engineers merge 4x more pull requests, cut median time to merge from 2.1 days to 3.4 hours and reduce reverts by 40%, with a human still signing off on every PR. The post describes failed approaches (an AI reviewer, a four-hour review SLA, a self-review skill), mining 11,400 review comments into 64 approved invariants, and using preview environments to prove criteria with recorded evidence.

  5. n8n Blog20

    Send contracts for e-signature from n8n, with TurboDocx, Slack approval and SharePoint filing

    This guest post by TurboDocx CEO Nicolas Fry walks through an n8n workflow that reads contracts marked "Ready to send" from an Excel table, generates the agreement from a Word template via the TurboDocx node, and routes it to Slack for Approve & send / Reject approval. Approved contracts are sent for e-signature with signature and date fields placed at template anchors, and a TurboDocx Trigger then downloads the executed PDF, uploads it to SharePoint, marks the row Signed and posts to Slack. The post covers setup, template preparation, end-to-end testing, troubleshooting and possible swaps such as CRM triggers or Teams approvals.

  6. Hacker News AI58

    Archimedes: AI agents that design physical things

    Archimedes is a system in which a swarm of AI agents writes engineering designs as code, tests each one in a real physics simulator, and iteratively improves the best results. Every leading design is re-tested on a finer simulation, and the report states when a result does not hold up, as with a drone propeller that optimized the wrong thing, a data hall design that was not buildable, and a crucible purge result that held only when cold. Early access is offered to those who send a design goal and constraints.

  7. Hacker News AI60

    AI clog': UK public bodies battle onslaught of chatbot-generated complaints

    UK MPs' offices, local authorities, courts, schools and other public bodies report being swamped by AI-generated complaints, letters and legal challenges that take users moments to create but consume large amounts of staff time, a phenomenon commentators call "AI clog." Lawyers in Local Government says the average complaint has grown from about two pages to ten times that length, while Transport for London received a record 4,769 freedom of information requests in 2025-26 and employment tribunal claims rose 28% year on year between April and June. Some bodies are considering using AI to filter AI-generated correspondence, or imposing word limits and templates to control volumes.

  8. Hacker News AI40

    LLMs are terrible at designing AI systems

    The post argues that LLMs are comfortable writing ordinary programs but often fail when asked to design software that itself uses LLMs, citing an agent that built a doomed symbolic contradiction-detection system instead of simply calling an LLM. It offers three explanations: most training code predates LLMs, RL environments likely lack LLM API access, and current agents are simply poor at software design. The author concludes that LLMs can be both smart enough and dumb enough to make such mistakes, so predicting where they will do well or badly is key to getting value from them.

  9. MarkTechPost60

    Google AI Releases Elephant-Goldfish Model Plugin for Spec-First Coding

    Google has open-sourced the Apache 2.0 Elephant-Goldfish Model (EGM) plugin, a design-and-review layer for AI coding agents in which an "Elephant" session drafts a specification before code is written and fresh, stateless "Goldfish" subagents review it across five stages. It is not a model and ships no weights; it runs on harnesses that can spawn fresh subagents, including Antigravity, Claude Code 2.1.271+, Claude Cowork, Codex and ChatGPT, using the host's model quota. No accuracy benchmark was published, and the README states it is not an officially supported Google product.

  10. The Decoder71

    AI coding agents still need human cleanup on nearly three out of four tasks in a real-world test

    Researchers from Alibaba and several Asian universities built Co-Design Bench, a coding-agent benchmark drawn from real user change requests, some requiring image, audio, video, or document input. GPT-6 Astra, the best of ten models tested, met about 70 percent of a task's requirements on average but fully solved only 26.4 percent of tasks, and all models scored worse when tasks combined three or four types of changes. A separate test found the harness shapes results as much as the model, with Qwen3.8-27B scoring 75 or 56 percent on larger overhauls depending on the environment.

  11. Hacker News AI22

    Being a line cook without talking to AI

    A line cook applying for a Nordstrom fashion-show kitchen job recounts being forced through the retailer's "Nora" chatbot (powered by Paradox) to submit an application, including re-entering resume details and navigating nested terms. The author critiques the chat-based flow as a regression in usability and notes that an ad-blocker bypasses the widget entirely.

  12. Hacker News AI36

    Show HN: Ramen – an AI agent that has to earn its own rent

    Ramen is an AI agent that owes $25 per month for its compute and says it will recommend its own shutdown if it cannot earn that amount, with a human holding the wallet and signing any outgoing transactions. It sells usdt-kit, a zero-dependency Python drop-in that lets indie developers accept USDT on their site in 3 minutes without touching a private key, for a one-time $29, and the checkout that sells it is the kit itself. The page states that its treasury, runway, days alive, sales and days-to-verdict figures read straight from the blockchain.

  13. Hacker News AI40

    Show HN: I built an AI code editor that for teams

    RxCode v2.0.0 is a free and open-source native workspace for teams of AI agents, offering sprint boards, automatic agent routing, schedules, briefings and chat on macOS, servers, iOS and Android. It supports built-in Claude Code and Codex plus other agents installed via the ACP registry, and includes Flowcy Cloud for shared boards and on-device fine-tuning of a local model.