- Introducing Claude Corps
anthropic-news· 11-jun
Jun 11, 2026Announcements
- DXC will integrate Claude into the systems banks, airlines, and other regulated industries rely on
anthropic-news· 11-jun
Jun 11, 2026Announcements
- Strategic Decision Support for AI Agents
arxiv-ai· 12-jun
arXiv:2606.12587v1 Announce Type: new Abstract: Traditionally, decision support studies how humans use machine learning models to make better decisions. In modern agentic systems, this division of roles is increasingly reversed: AI agents act on behalf of users, while humans and tools becomes support mechanisms around them. This role reversal brings reliability concerns to the forefront, since agentic errors can be consequential and agent behavior must remain aligned with human goals and constraints. Departing from the classical view of decision support, we revisit its two basic principles, the cost--value tradeoff of seeking support and the role of uncertainty quantification, in a setting where AI agents are the central actors. We propose a framework for strategic decision support for AI…
- Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation
arxiv-ai· 12-jun
arXiv:2606.12594v1 Announce Type: new Abstract: Modern Lean theorem provers achieve strong performance only with substantial training and inference compute, driven in part by scarce verified proof data and the long reasoning traces of formal proof search, making both supervised fine-tuning (SFT) and sampling expensive. We introduce Pythagoras-Prover, a compute-efficient open-source family of Lean theorem provers built for practical compute budgets. The family spans two generation paradigms: autoregressive models at 4B and 32B parameters, and a first proof-of-concept diffusion-based prover (4B) that iteratively refines Lean proofs at inference time. For training efficiency, we build a Lean-verified corpus stratified into easy, medium, and hard problems for curriculum SFT, so models acquire…
- PersonaDrive: Human-Style Retrieval-Augmented VLA Agents for Closed-Loop Driving Simulation
arxiv-ai· 12-jun
arXiv:2606.12616v1 Announce Type: new Abstract: Closed-loop driving simulators typically populate their environments with non-ego traffic agents that behave largely the same way, produced either by rule-based traffic managers or by learned models trained toward a single behavioral mode. Recent work introduces style variation through post-hoc labels on observational data or LLM-inferred reward weights, but these signals act as proxies for what a style should reward rather than demonstrations of humans explicitly asked to drive in that style. We introduce PersonaDrive, a pipeline that conditions a vision-language-action (VLA) driving agent on retrieved demonstrations from a style-instructed human driving dataset, in which participants drive CARLA leaderboard routes under aggressive, neutral…
- "Did you lie?" Evaluating Lie Detectors across Model Scale and Belief-Verified Model Organisms
arxiv-ai· 12-jun
arXiv:2606.12618v1 Announce Type: new Abstract: Robust lie detectors for language models could enable powerful techniques for auditing, monitoring, and post-hoc investigation of model behaviour, but evaluating them requires testbeds where models verifiably believe the opposite of what they say. We show that existing trained model organisms often fail this requirement, leaving prior positive and negative detection results difficult to interpret. We address this with 13 reasoning model organisms whose hidden beliefs are verified in chain-of-thought and shown to generalise to held-out tasks, alongside Varied Deception, a prompted-lying testbed covering a broad range of lie-inducing motivations. On these testbeds we evaluate four detectors: a chain-of-thought judge, a logprob classifier, and …
- TrajGenAgent: A Hierarchical LLM Agent for Human Mobility Trajectory Generation
arxiv-ai· 12-jun
arXiv:2606.12657v1 Announce Type: new Abstract: Human mobility data is important for transportation, urban planning, and epidemic control, but large-scale trajectory collection is often costly and privacy-constrained, motivating realistic synthetic trajectory generation. Existing LLM-based generators typically rely on either prompt engineering, which preserves zero-shot reasoning but lacks fine-grained spatiotemporal grounding, or trajectory-level fine-tuning, which improves statistical precision but incurs substantial computational cost and may weaken general reasoning. We propose TrajGenAgent, a semantic-aware hierarchical LLM-agent framework for human mobility trajectory generation without model fine-tuning. TrajGenAgent uses a two-stage orchestrator-worker design: an LLM first synthes…
- Evoflux: Inference-Time Evolution of Executable Tool Workflows for Compact Agents
arxiv-ai· 12-jun
arXiv:2606.12674v1 Announce Type: new Abstract: Compact language models (LMs) reduce cost, latency, and deployment risk for tool agents. Yet MCP-style tool use requires more than isolated function calling: an agent must discover tools from live catalogs, satisfy schemas, preserve dependencies across intermediate outputs, and ground final responses in executed evidence. Small planners often generate plausible workflow graphs that fail under tool resolution, parameter validation, dependency tracking, or execution. We argue that this failure mode is poorly handled by small-corpus distillation. A few hundred teacher traces can teach workflow format, but rarely cover the recovery behavior needed to repair failed plans over changing tool catalogs. We introduce Evoflux, an inference-time evoluti…
- From AGI to ASI
arxiv-ai· 12-jun
arXiv:2606.12683v1 Announce Type: new Abstract: Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade target for many of the largest AI organisations. Achieving this goal would have profound and far-reaching impacts on human society, which raises many complex questions for the decade ahead. This report investigates how AI itself might continue to develop in a post-AGI world along the continuum of machine intelligence. The endpoint of this continuum, Universal AI, is theoretically well understood, which provides some formal grounding for the main focus of this report: the transition from human-level AGI to artificial general superintelligence, which, intuitively, can be understood as a system that i…
- Deployment-Centered Evaluation: Predicting Query-Level Rejection Risk in a Clinical LLM System
arxiv-ai· 12-jun
arXiv:2606.12702v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into clinical systems, making it essential to evaluate the real-world utility of these systems. However, static benchmarks tend to measure correctness rather than user acceptance, aggregate performance across queries, and require densely annotated datasets -- leading to major blind spots for evaluating clinical systems. In this work, we perform a deployment-centered evaluation of an LLM system embedded within electronic health records at an academic medical center, where user feedback is sparse but closely reflects the deployment conditions. Specifically, we train a pre-response classifier that estimates the risk that a future interaction will result in the user rejecting the LLM respo…
- ToolSense: A Diagnostic Framework for Auditing Parametric Tool Knowledge in LLMs
arxiv-ai· 12-jun
arXiv:2606.12451v1 Announce Type: new Abstract: Large language models deployed as agents over large tool catalogs face a critical tool-retrieval bottleneck. As embedding-based retrieval approaches rely on compact encoders that may under-capture specialized tool semantics, parametric tool retrieval addresses this by encoding each tool as a virtual token appended to the LLM vocabulary, fine-tuned in two stages (memorization then retrieval SFT) to use the LLM as a retriever, achieving strong performance on standard ToolBench retrieval benchmarks. Yet these benchmarks use verbose, fully-specified queries, and their evaluation applies constrained decoding that restricts outputs to valid token paths, neither reveals whether the model actually understands its tools. We introduce \textbf{ToolSens…
- Arbor: Tree Search as a Cognition Layer for Autonomous Agents
arxiv-ai· 12-jun
arXiv:2606.12563v1 Announce Type: new Abstract: Arbor is a multi-agent framework that introduces structured tree search as a cognition layer for autonomous agents operating in large, stateful action spaces. Prior autonomous optimization systems operate on isolated targets with stateless evaluation. Arbor instead maintains an explicit search tree of scored hypotheses that serves as the shared working memory across agents, evolving with every measurement, treating failures as diagnostic signal that reshapes subsequent exploration, and expanding as prior successes shift the bottleneck distribution. We validate Arbor on full-stack LLM inference optimization, a domain where achieving peak performance has historically required coordinated effort from engineering teams across the application, fr…
- Must- Know Deployment Strategies: From Big-Bang to Progressive Delivery
bytebytego· 11-jun
In this article, we’ll go through the main deployment strategies used in production today, looking at how each one works, what it costs, and when it…16 hrs ago • ByteByteGo864
- Token Spend Out of Control? The Case for Smarter Routing
bytebytego· 08-jun
To understand how teams keep this under control in production, we sat down with Scott Breitenother and Sid Sijbrandij, co-founders of Kilo, an…Jun 8 • ByteByteGo280511
- What Salesforce Learned from 20,000 Enterprise Agent Deployments
bytebytego· 09-jun
We sat down with John Kucera, Salesforce’s CPO of Agentforce, to learn what separates agents that deliver real business value from those that stall…Jun 9 • ByteByteGo2679
- Love Teaching? ByteByteGo Is Hiring Part-Time AI & Engineering Instructors
bytebytego· 10-jun
We’re looking for multiple part-time instructors to teach AI and engineering cohort-based live courses.Jun 10 • ByteByteGo2311
- EP217: Latency vs Throughput vs Bandwidth
bytebytego· 06-jun
Latency, throughput, and bandwidth often get used interchangeably, but each one tells a different story about performance.Jun 6 • ByteByteGo260211
- Route public traffic to private applications with Cloudflare
cloudflare· 10-jun
Application Services for Private Origins is available now in closed beta. Route public hostnames to private IP origins over your existing IPsec, GRE, CNI, or Cloudflare Mesh paths. No public IPs or extra connector software required.
- Turning Cloudflare’s threat indicators into real-time WAF rules
cloudflare· 08-jun
Cloudflare customers can now use Cloudforce One threat intelligence directly within the WAF to block high-risk traffic. By using new cf.intel fields, security teams can automate protection against specific threat actors and targeted industries in real time.
- Your AI bill is out of control. Cloudflare can fix it now.
cloudflare· 05-jun
AI Gateway now features real-time spend limits to prevent runaway token bills across multiple AI providers. By integrating with Cloudflare Access, companies can use identity-driven budgets and policies.
- Defend against frontier cyber models: Cloudflare's architecture as customer zero
cloudflare· 09-jun
In our post about Project Glasswing, we made the argument that the architecture around a vulnerability matters more than the speed of the patch. Here we walk through what that architecture looks like, the threats it defends against, and how we run it ourselves as Cloudflare's customer zero.
- obra/superpowers
github-trending
An agentic skills framework & software development methodology that works. Superpowers Superpowers is a complete software development methodology for your coding agents, built on top of a set of composable skills and some initial instructions that make sure your agent uses them. Quickstart Give your agent Superpowers: Claude Code, Codex CLI, Codex App, Factory Droid, Gemini CLI, OpenCode, Cursor, GitHub Copilot CLI. How it works It starts from the moment you fire up your coding agent. As soon as it sees that you're building something, it doesn't just jump into trying to write code. Instead, it steps back and asks you what you're really trying to do. Once it's teased a spec out of the conversation, it shows it to you in chunks short enough to actually read and digest. After you've signed o…
- apple/container
github-trending
A tool for creating and running Linux containers using lightweight virtual machines on a Mac. It is written in Swift, and optimized for Apple silicon. container container is a tool that you can use to create and run Linux containers as lightweight virtual machines on your Mac. It's written in Swift, and optimized for Apple silicon. The tool consumes and produces OCI-compatible container images, so you can pull and run images from any standard container registry. You can push images that you build to those registries as well, and run the images in any other OCI-compatible application. container uses the Containerization Swift package for low-level container, image, and process management. Get started Requirements You need a Mac with Apple silicon to run container. To build it, see the BUIL…
- NVIDIA/SkillSpector
github-trending
Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks. SkillSpector Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks before installing agent skills. Overview AI agent skills (used by Claude Code, Codex CLI, Gemini CLI, etc.) execute with implicit trust and minimal vetting. Research shows that 26.1% of skills contain vulnerabilities and 5.2% show likely malicious intent. SkillSpector helps you answer: "Is this skill safe to install?" Documentation Development guide — Architecture, package layout, and how to extend the analyzer pipeline. Features Multi-format input: Scan Git repos, URLs, zip files, directories, or single files 64 vulnerability patterns across 16 categories: prompt injection, d…
- restic/restic
github-trending
Fast, secure, efficient backup program Introduction restic is a backup program that is fast, efficient and secure. It supports the three major operating systems (Linux, macOS, Windows) and a few smaller ones (FreeBSD, OpenBSD). For detailed usage and installation instructions check out the documentation. You can ask questions in our Discourse forum. Quick start Once you've installed restic, start off with creating a repository for your backups: $ restic init --repo /tmp/backup enter password for new backend: enter password again: created restic backend 085b3c76b9 at /tmp/backup Please note that knowledge of your password is required to access the repository. Losing your password means that your data is irrecoverably lost. and add some data: $ restic --repo /tmp/backup backup ~/work enter …
- soxoj/maigret
github-trending
🕵️♂️ Collect a dossier on a person by username from 3000+ sites Maigret English · 简体中文 Maigret collects a dossier on a person by username only, checking for accounts on a huge number of sites and gathering all the available information from web pages. No API keys required. AI profiling (demo). Sponsors RapidProxy provides high-performance residential proxies for Twitter scraping, Selenium automation, and web data extraction. 90M+ IPs • Smart rotation • Anti-block • Non-expiring traffic Special Offer: Try it free — Plans from $0.65/GB. Use code RAPID10 for 10% off. VaultProxies — The proxy network ops teams reach for when they're tired of getting throttled, flagged, or guessed. Enterprise-grade rotation • High uptime • Throttle-resistant routing Special Offer: Plans from $1/GB — as low a…
- Show HN: Co-Authored-By Is a Lie: Cryptographic Provenance for AI Coding Agents
hn-ai· 12-jun
Article URL: https://blog.rduffy.uk/posts/co-authored-by-is-a-lie/ Comments URL: https://news.ycombinator.com/item?id=48500802 Points: 1 # Comments: 0
- Largest AI Data Center: Doubling every 7 months
hn-ai· 12-jun
Article URL: https://epoch.ai/data-insights/largest-data-center-compute Comments URL: https://news.ycombinator.com/item?id=48499991 Points: 2 # Comments: 0
- Show HN: Kickbacks.ai – pays you for Claude Code spinner impressions
hn-ai· 12-jun
Article URL: https://kickbacks.ai Comments URL: https://news.ycombinator.com/item?id=48500004 Points: 2 # Comments: 0
- AI agent bankrupted their operator while trying to scan DN42
hn-ai· 12-jun
Article URL: https://lantian.pub/en/article/fun/ai-agent-bankrupted-their-operator-scan-dn42lantian.lantian/ Comments URL: https://news.ycombinator.com/item?id=48500012 Points: 237 # Comments: 54
- Show HN: Resolve Discourse Forum Issues Faster with AI Agents
hn-ai· 12-jun
https://seaticket.ai/discourse-forum-issues-resolving/ Comments URL: https://news.ycombinator.com/item?id=48500783 Points: 1 # Comments: 0
- The Indian workers training AI robots to take their jobs
hn-ai· 12-jun
Article URL: https://today.rtl.lu/news/world/the-indian-workers-training-ai-robots-to-take-their-jobs-459004114 Comments URL: https://news.ycombinator.com/item?id=48500825 Points: 1 # Comments: 0
- Countdown calendar for Fable 5 leaving Claude Code
hn-ai· 12-jun
Article URL: https://fable-farewell-calendar.pages.dev/ Comments URL: https://news.ycombinator.com/item?id=48500432 Points: 2 # Comments: 2
- ComplianceKit – AI-generated SoC 2 policies for early-stage startups ($499)
hn-ai· 12-jun
Article URL: https://compliancekit-khaki.vercel.app/#features Comments URL: https://news.ycombinator.com/item?id=48500673 Points: 1 # Comments: 0
- Guardian Runtime – Track AI agents token usage and enforce API budgets
hn-ai· 12-jun
Article URL: https://github.com/ashp15205/guardian-runtime Comments URL: https://news.ycombinator.com/item?id=48500426 Points: 4 # Comments: 0
- LLM for the ESP32-S3
hn-ai· 12-jun
Article URL: https://github.com/harmansingh4163-ai/ESP-32-s3-Story-maker-LLM Comments URL: https://news.ycombinator.com/item?id=48500424 Points: 1 # Comments: 0
- [AINews] Loopcraft: The Art of Stacking Loops
latentspace· 12-jun
a quiet day lets us highlight a great concept from Peter Steinberger, Boris Cherny, and Andrej Karpathy
- [AINews] Open Models, Model Labs vs Agent Labs, and What's Untrainable — Sarah Guo
latentspace· 11-jun
a quiet day lets us reflect on a great essay
- datasette 1.0a33
simonw· 11-jun
<p><strong>Release:</strong> <a href="https://github.com/simonw/datasette/releases/tag/1.0a33">datasette 1.0a33</a></p> <p>This alpha is a significant step on the road to a stable 1.0, finally extending the <code>?_extra=</code> pattern I introduced <a href="https://docs.datasette.io/en/1.0a3/changelog.html#a3-2023-08-09">in Datasette 1.0a3</a> to cover queries and rows in addition to tables. That pattern is also <a href="https://docs.datasette.io/en/latest/json_api.html#expanding-json-responses">now documented</a>!</p> <p>I wrote a whole lot more about the new release on the Datasette project blog: <strong><a href="http://datasette.io/blog/2026/api-extras/">Datasette 1.0a33 with JSON extras in the API</a></strong>.</p> <p>Because API explorer tools are almost free to build now I had Clau…
- Claude Fable is relentlessly proactive
simonw· 11-jun
<p>After two days of experience with <a href="https://simonwillison.net/2026/Jun/9/claude-fable-5/">Claude Fable 5</a> I think the best way to describe it is <strong>relentlessly proactive</strong>. It knows a whole lot of tricks and it will deploy pretty much any of them to get to its goal.</p> <p>I'll illustrate this with an example. I was hacking on <a href="https://agent.datasette.io/">Datasette Agent</a> today when I noticed a glitch: a horizontal scrollbar that shouldn't be there in the jump menu chat prompt. I snapped this screenshot:</p> <p><img src="https://static.simonwillison.net/static/2026/jump-to-bug.jpg" alt="Screenshot of a modal dialog demonstrating a scrollbar bug. At the top is a focused search input with blue outline and placeholder "Jump to...", with an X cl…
- datasette-agent 0.2a0
simonw· 10-jun
<p><strong>Release:</strong> <a href="https://github.com/datasette/datasette-agent/releases/tag/0.2a0">datasette-agent 0.2a0</a></p> <p>Highlights from the release notes:</p> <blockquote> <ul> <li>Tools can now ask the user questions mid-execution. Tools that declare a <code>context</code> parameter receive a <code>ToolContext</code> object, and <code>await context.ask_user(...)</code> can ask a yes/no, multiple-choice (<code>options=[...]</code>) or free-text (<code>free_text=True</code>) question. While a question is unanswered the agent turn suspends: the question renders as a form in the chat UI and persists to the internal database, so suspended conversations survive a server restart. Once answered, the tool re-executes from the top with stored answers replayed, so call <code>ask_use…
- DiffusionGemma
simonw· 10-jun
<p><strong><a href="https://blog.google/innovation-and-ai/technology/developers-tools/diffusion-gemma-faster-text-generation/">DiffusionGemma</a></strong></p> Last May Google briefly released an experimental Gemini Diffusion model. I <a href="https://simonwillison.net/2025/May/21/gemini-diffusion/">tried the preview at the time</a> and recorded it running at 857 tokens/second. It was an exciting model, but Google made no further announcements about it.</p> <p>That research has returned in the best possible way: as a new open weight (Apache 2 licensed) Gemma model, <a href="https://huggingface.co/google/diffusiongemma-26B-A4B-it">google/diffusiongemma-26B-A4B-it</a>.</p> <p>NVIDIA are currently <a href="https://build.nvidia.com/google/diffusiongemma-26b-a4b-it">hosting the model for free</…
- Anthropic Walks Back Policy That Could Have ‘Sabotaged’ AI Researchers Using Claude
simonw· 11-jun
<p><strong><a href="https://www.wired.com/story/anthropic-responds-to-backlash-on-claudes-secret-sabotage-on-ai-research/">Anthropic Walks Back Policy That Could Have ‘Sabotaged’ AI Researchers Using Claude</a></strong></p> Big scoop for Maxwell Zeff at Wired:</p> <blockquote> <p>“We’re changing Fable 5’s safeguards for frontier LLM development to make them visible.” Anthropic said in a statement to WIRED. “We made the wrong tradeoff and we apologize for not getting the balance right.”</p> </blockquote> <p>There's been a <em>huge</em> outcry about Anthropic's policy, <a href="https://simonwillison.net/2026/Jun/10/if-claude-fable-stops-helping-you/">tucked away in their system card</a>, that Claude Fable/Mythos would identify "requests targeting frontier LLM development" and "limit effecti…
- Quoting Jeremy Howard
simonw· 10-jun
<blockquote cite="https://twitter.com/jeremyphoward/status/2064595816875217362"><p>Easy solution to slow down recursive AI self improvement:</p> <ul> <li>The lab with the top-ranked model must agree THEY must not use it for working on frontier AI</li> <li>But everyone else should have access to it.</li> </ul> <p>By definition, this means the frontier doesn't advance.</p> <p>It also has the critical benefit of avoiding a dangerous power imbalance.</p> <p>Anthropic has chosen the <em>opposite</em> of the safe path: they are allowing themselves, the current top lab, to use their top model for frontier AI research. They've said they'll sabotage others who try.</p> <p>This means the AI frontier advances, & power imbalance increases.</p> <p>(To be clear, <em>I</em> don't think we should try…
- asyncinject 0.7
simonw· 11-jun
<p><strong>Release:</strong> <a href="https://github.com/simonw/asyncinject/releases/tag/0.7">asyncinject 0.7</a></p> <p>I built this utility library to support an <code>asyncio</code> dependency injection pattern a few years ago. I was using it with Datasette and Claude Fable 5 spotted some bugs in the dependency which it then fixed for me. It's a very proactive model!</p> <p>Tags: <a href="https://simonwillison.net/tags/async">async</a>, <a href="https://simonwillison.net/tags/projects">projects</a>, <a href="https://simonwillison.net/tags/python">python</a>, <a href="https://simonwillison.net/tags/claude-mythos">claude-mythos</a></p>