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Hacker News AILLMs

Scams Were Awful. Then They Got AI

Article URL: https://www.rstreet.org/commentary/scams-were-already-awful-then-they-got-ai/ Comments URL: https://news.ycombinator.com/item?id=48900681 Points: 2 # Comments: 0

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Hacker News AILLMs

Customer auth for AI voice agents

Article URL: https://www.ringd.dev/ Comments URL: https://news.ycombinator.com/item?id=48900608 Points: 2 # Comments: 1

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PlatformerNewsletters

The loudest warning about AI and jobs yet

200 economists and AI leaders say something big is happening. What should we do about it? Plus: Apple sues OpenAI

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The loudest warning about AI and jobs yet
OpenAI BlogLLMs

How data science teams use ChatGPT Work

See how data science teams can use ChatGPT Work to build root-cause briefs, impact readouts, KPI memos, scoped analyses, and dashboard specs from real work inputs.

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Vercel Blog

AgentMail joins the Vercel Marketplace

You can now provision and manage AgentMail directly from the Vercel Marketplace. Your AI agents can send, receive, and respond to email from a real inbox. AgentMail handles the mail servers and deliverability. Key capabilities: Provision inboxes and custom domains through the API Handle threads, attachments, and deliverability out of the box Trigger agentic workflows using webhooks and WebSockets Install AgentMail on the Vercel Marketplace or with the Vercel CLI: Read more

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Apple Machine LearningResearch

Proactive Agent Research Environment: Simulating Active Users to Evaluate Proactive Assistants

Proactive agents that anticipate user needs and autonomously execute tasks hold great promise as digital assistants, yet the lack of realistic user simulation frameworks hinders their development. Existing approaches model apps as flat tool-calling APIs, failing to capture the stateful and sequential nature of user interaction in digital environments and making realistic user simulation infeasible. We introduce Proactive Agent Research Environment (Pare), a framework for building and evaluating

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Vercel Blog

Access and share AI Gateway leaderboard data

You can now export AI Gateway leaderboard charts as images and download or query the data behind every ranking. The AI Gateway leaderboards show how AI is used in production, ranking models, labs, apps, and providers running on AI Gateway by production traffic, aggregated daily across trillions of tokens, so you can see what gets adopted and how that changes over time. For deeper analysis, see the July AI Production Index . What's ranked There are four leaderboards, each with its own metrics: Le

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OpenAI BlogLLMs

How sales teams use ChatGPT Work

See how sales teams can use ChatGPT Work to create pipeline briefs, meeting prep packets, forecast reviews, account plans, and stalled-deal diagnoses from real work inputs.

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Apple Machine LearningResearch

Multilingual Semantic Retrieval for Apple Music Search

Apple Music serves listeners across 150+ storefronts in dozens of languages, with a catalog that grows by hundreds of thousands of new tracks daily. At this scale, search recall on misspelled, transliterated, and cross-lingual queries becomes a dominant driver of session quality, particularly for tail queries that account for the majority of unique queries. We present a multilingual semantic retrieval system built on a 305M-parameter Siamese bi-encoder fine-tuned from GTE-multilingual-base with

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Vercel Blog

Vercel Blob now supports consistent reads on private storage

Vercel Blob now supports consistent reads on private storage. Pass useCache: false to get() or presignUrl() for a read that reflects the latest write. A blob written to a fresh pathname has no existing cached entry, so reads reflect the latest write immediately. When you overwrite a blob at an existing pathname, readers might see the cached version for up to 60 seconds. When a read must reflect the latest write, like an agent's memory file, a session transcript, or a scheduled JSON report, pass

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Vercel Blog

Vercel Plugin now available in VS Code and GitHub Copilot CLI

The Vercel Plugin is now available in VS Code and the GitHub Copilot CLI. GitHub Copilot now has Vercel platform knowledge on demand, with skills for Next.js, AI SDK, Vercel Functions, and more. The Vercel plugin also helps Copilot stay up to date with the latest Vercel APIs and recommended patterns. To install it for Copilot Chat, search for @agentPlugins vercel in the Extensions panel in VS Code. To install it for the GitHub Copilot CLI, run npx plugins add vercel/vercel-plugin . Learn more in

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Hacker News AILLMs

Tachyon: An AI Screen-Aware Tutor

Article URL: https://heybraza.com Comments URL: https://news.ycombinator.com/item?id=48900478 Points: 2 # Comments: 0

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Hacker News Show

Show HN: FixBugs – Reproduce production bugs and verify fixes

I built FixBugs, an agent that ingests the rich context surrounding production bugs to reproduce them in a sandbox and generate verified fixes. It's available in the form of a self-hosted VSCode extension and as a Github app: VSCode Extension: https://fixbugs.ai/go/vscode-extension - full code and data privacy. - zero data retention models opted out of training. GitHub App: https://fixbugs.ai/go/github-app - we do access your code temporarily. - pick a repo to install FixBugs on. What motivated

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Dev.to

The AI Supply Chain: The Next Evolution of Third Party Risk

<p>Most enterprise security teams believe they have third party risk under control. They send out questionnaires, review SOC 2 reports, and negotiate vendor contracts.</p> <p>In the age of enterprise AI, this traditional approach is no longer enough. It is dangerously incomplete.</p> <p>The real risk has shifted from vendors to dependencies. We are moving away from legal agreements to neural weights, embeddings, retrieval pipelines, and agent frameworks. You can build a textbook Zero Trust archi

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Dev.to

Building a production AI agent in TypeScript with Mastra: a 2026 step-by-step.

<h1> Building a production AI agent in TypeScript with Mastra: a 2026 step-by-step. </h1> <p>I spent an afternoon last month wiring up an AI agent in raw TypeScript using the Anthropic SDK directly. The code worked, but I owned every piece of it: the tool dispatch loop, the conversation history array, the retry logic. Around 400 lines before the agent did anything interesting.</p> <p>Mastra cuts that to about 60. A TypeScript-first agent framework with 24k+ GitHub stars, an active release cadenc

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Hacker News AILLMs

Dependency analytics 1.0: AI coding with supply chain security

Article URL: https://developers.redhat.com/articles/2026/07/07/dependency-analytics-10-ai-coding-supply-chain-security Comments URL: https://news.ycombinator.com/item?id=48900324 Points: 2 # Comments: 0

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Hacker News AILLMs

Show HN: Sx 2.0 – Share AI skills with your team through a Dropbox folder

Hi all, author here. SX started as a CLI to let developers share skills across AI clients without having to rely on git for storage. This allowed sharing at the Repo/Team/Org and Personal level. However, the more we spoke to users the more we realized that non-technical users were actually using skills more and more but they had no way to share. And there was no way you were going to get your legal team to install and learn git. SX 2.0 is targeting non-technical teams by adding a native Mac, Win

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OpenClaw Commits

feat(reef): headless openclaw reef CLI for agent-driven registration …

<pre style='white-space:pre-wrap;width:81ex'>feat(reef): headless openclaw reef CLI for agent-driven registration and pairing Adds a non-interactive command surface (openclaw reef register|status|friend code|request|list|remove) so an agent can claim a handle and manage guarded friendships when its owner asks, without the interactive wizard. --json emits machine-readable output for automation. Registration is crash-safe and idempotent: guard defaults are provider-coupled, the full config is vali

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Hacker News AILLMs

Show HN: ContextVault – Shared memory layer for your AI and your team

Hi HN, I'm Kevin. I built ContextVault because I kept running into the same problem with AI tools. Every project accumulated prompts, coding conventions, architectural decisions, examples, and other pieces of context that made the models significantly more useful. The problem was that this information quickly became fragmented. Some lived in ChatGPT Projects, some in Claude, some in Markdown files, some in internal documentation, and some only existed in previous conversations. Late last year, I

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OpenClaw Commits

refactor(whatsapp): reuse SDK tool result helper (#105574)

<pre style='white-space:pre-wrap;width:81ex'>refactor(whatsapp): reuse SDK tool result helper (#105574) * refactor(whatsapp): reuse SDK agent-tool utilities * fix(whatsapp): preserve call audio cleanup errors</pre>

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Hacker News AILLMs

The AI Whale Fall and Open Source

Article URL: https://minor.gripe/posts/2026-07-13-the_ai_whalefall_and_open_source/ Comments URL: https://news.ycombinator.com/item?id=48900231 Points: 4 # Comments: 1

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Dev.to

Your rules file only grows. Here's how to find the rules that do nothing

<p><em>This is part 3 of a series on project rules for AI coding agents. <a href="https://dev.to/rulestack/how-cursor-claude-code-and-codex-actually-load-your-project-rules-and-why-yours-get-ignored-1l1j">Part 1</a> covered how Cursor, Claude Code, and Codex load your rules. <a href="https://dev.to/rulestack/your-claudemd-says-always-run-tests-hooks-are-how-you-actually-mean-it-1o9f">Part 2</a> covered enforcing rules with hooks. This one covers the part almost nobody does: figuring out which of

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Dev.to

JavaScript Atomics and SharedArrayBuffer in 2026: Practical Patterns for Cross-Worker State

<h1> JavaScript Atomics and SharedArrayBuffer in 2026: Practical Patterns for Cross-Worker State </h1> <blockquote> <p><em>This article was written with the assistance of AI, under human supervision and review.</em></p> </blockquote> <p>Most cross-worker communication problems stem from treating workers as isolated processes when the workload demands shared state. Teams reach for <code>postMessage</code> by default, serialize multi-megabyte data structures on every frame, and watch their real-ti

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Dev.to

I Built a Browser to Solve a Problem Every Developer and QA Engineer Faces

<p>If you've ever worked on an application with multiple user roles, you've probably experienced this.</p> <p>You log in as an <strong>Administrator</strong>.</p> <p>Then you need to test the <strong>Manager</strong>.</p> <p>So you log out.</p> <p>Log in as the <strong>Customer</strong>.</p> <p>Log out again.</p> <p>Then the <strong>Support Agent</strong>.</p> <p>And maybe another <strong>Guest</strong> account.</p> <p>Before long, your browser has turned into a collection of Incognito windows,

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MarkTechPostResearch

Skyfall AI Releases MORPHEUS: A Persistent Enterprise Simulation Benchmark That Makes Continual Reinforcement Learning Necessary Under Structured Non-Stationarity

MORPHEUS from Skyfall AI is a persistent enterprise simulation platform for continual reinforcement learning. It runs worlds that never reset, using parameterisable regime shifts and a six-metric evaluation protocol. Across the platform, PPO, HER, EWC, and LCM all remain far below the theoretical upper bound. The post Skyfall AI Releases MORPHEUS: A Persistent Enterprise Simulation Benchmark That Makes Continual Reinforcement Learning Necessary Under Structured Non-Stationarity appeared first on

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Simon WillisonLLMs

DOOMQL

<p><strong><a href="https://github.com/petergpt/doomql">DOOMQL</a></strong></p> Peter Gostev built this using GPT-5.6 Sol. This is a <em>lot</em> of fun: </p> <blockquote> <p>DOOMQL started with a deliberately unreasonable question: what if SQLite were the game engine, not merely the place where a game stores data?</p> <p>The result is a small, original Doom-like game in which SQL owns movement, collision, enemies, combat, progression and every RGB pixel on screen.</p> </blockquote> <p>It's impl

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Hacker News Ask

Ask HN: AI Agent and harness containerization/security recommendations

Hello HN crew - I am seeing the tendency for people to allow AI agents to access local project & user folders, and beyond (operating system files). I thought to ask the question: How can we best use AI tools safely - where the workflow often runs local system commands and network commands - to protect the integrity of our systems & data AND be easy enough to use productively? Comment structure idea: Operating system / Agent harness / Agent / Security strategy & tool stack / Workflow To give some

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