#Agent

United to block customers from using AI agents, citing cyber threats

United Airlines will block AI agents from managing customers' reservations and flight purchases, warning of cybersecurity and privacy risks, potential legal violations, and unintended purchases or account changes. The airline said automated AI actions could also break FAA and DOT rules, since flight check-in requires human acknowledgment that bags contain no banned substances. United is applying the restrictions within its own digital platforms and through aggregators and agencies, updating its booking, ticketing and distribution policies.

Keenable 1.0: Search at the Speed of AI

Keenable launched version 1.0, which it says ranks #1 on the Artificial Analysis Search Index (BrowseComp, DeepSearchQA and AA-Omniscience) and #1 on NEEDLE, its open-source AI web search benchmark rerun daily on fresh queries. The release adds 100 million knowledge cards summarizing key facts on frequently searched topics and dynamic snippets that extract needed context from full documents, cutting token consumption by 50% on research tasks, with answers in hundreds of milliseconds. New accounts start with 100,000 requests as a welcome bonus, with one key and one MCP endpoint.

How Agent Anomaly Detection scores on benchmarks we didn't write

Google tested its Private Preview Agent Anomaly Detection feature on five public, non-Google agent-security benchmarks (AgentDojo, InjecAgent, Agent Security Bench, AgentDyn and AgentHarm), running 1,774 sessions through an ADK agent using gemini-2.5-flash. It flagged 87% of harmful instructions the agent actually carried out, with false alarms on 2% to 16% of benign sessions, but caught only 4 of 18 sessions where poisoned long-term memory drove the agent to act. The post details per-benchmark and per-app results, known gaps such as resisted instructions and small actions, and recommended defenses including Model Armor, Semantic Governance Policy and human approval for high-impact actions.

Show HN: Headwig - Run and test parallel AI agents without Git worktrees

Headwig introduces "Wisdom" groups that bundle an app's services so they can be built and run together, such as a frontend and backend as two services in one Wisdom. Users create a Wisdom via New Wisdom, then add services by clicking the three dots beside the Wisdom and choosing Add Service. The post also points readers to Discord for questions.

Nectar launches an AI agent to automate creator discovery and outreach for brands

Nectar, an AI-powered marketing operating system founded by former Meta employees Misbah and Farah Uraizee, has launched a "Creator Agent" that searches over 300 million creator profiles, checks content and prior brand partnerships, sends personalized messages in a brand's voice, and helps manage contracts, gifting, and shipping. The agent, available globally for Instagram and TikTok creators, also drafts outreach, builds custom landing pages, and tracks campaign performance, with planned availability through MCP for assistants like Claude, ChatGPT, Gemini, and Copilot. Nectar raised a $30 million Series A led by Menlo Ventures and its Anthology Fund in May.

Google’s latest Search upgrade promises better answers to your most complicated questions

Google says its new Gemini 4 Hydrogen model, described as its "biggest model improvement to Search yet," improves Search's handling of multi-part questions, highly specific requests and confusing typos. Hydrogen completes tasks 2.5 times faster than Gemini 3.8 Flash and is rolling out to all Search users globally, while also coming to AI Studio, the Gemini API, the Gemini App, AI Pro and Ultra subscribers, and Antigravity.

Featured coverage of this story: 《Introducing Gemini 4 Hydrogen》

The big gap between AI capabilities and replacing jobs

The author argues that AI will not cause meaningful net job loss, citing Anthropic research that roughly 30% of workers have zero measured AI exposure and noting that many white-collar jobs involve coordination, edge cases and client interaction that AI cannot yet handle. He adds that integration bottlenecks—clumsy interfaces, walled gardens and account sign-ups AI cannot complete—mean humans are still needed to bridge gaps between tools, which is why coding jobs won't simply vanish.

Building a self-service LLM gateway with Amazon Bedrock and LiteLLM

This post describes a pattern for a self-service LLM gateway that runs LiteLLM on AWS Fargate to expose Amazon Bedrock models through an OpenAI-compatible API, using Bedrock Application Inference Profiles for per-model quota isolation and scoped IAM access. It covers configuration of developer tools, LiteLLM model mapping with per-token costs for budget enforcement, CDK constructs for inference profiles, Langfuse observability, CloudWatch TPM alarms, and lessons learned from scaling to several hundred developers.

Optimizing cost per task and proving agent ROI on Amazon Bedrock

This AWS post argues that model cost should be measured per completed task rather than per token, citing four hidden cost drivers—tokenizer efficiency, output verbosity, agentic loop efficiency, and reasoning overhead—and an illustrative example where a model with double the list price costs 65% less per task. It describes levers for reducing cost per task (prompt caching, intelligent prompt routing, output constraints, batch inference) and Bedrock features such as CountTokens, the usage block, and invocation logging for measuring token and turn counts. For ROI, it recommends documenting and measuring a human baseline before launch, instrumenting workflows as experiments with run records, joining cost to outcomes via Athena, and using a five-dimension scorecard with green/yellow/red thresholds.

ASPM in the AI Era Part 3: Fixing Risk at the Speed of Code

The final installment of Wiz's series argues that AppSec's bottleneck is remediation, not detection, citing Verizon DBIR data that median patch time has risen to 47 days from 32. It describes how Wiz Code maps cloud findings to code owners via VCS connections and correlated data, and how the Wiz Green Agent generates tailored remediation plans that can open pull requests or hand off to coding agents like Claude Code. Wiz Workflows then routes tickets and alerts to Jira, ServiceNow, Slack, or Teams with full scanner and runtime context.

United Airlines blocks AI agents from booking flights, citing cybersecurity risks

United Airlines said it will restrict access to AI agents that book flights and manage reservations on users' behalf, citing cybersecurity risks and concerns about undermining federal regulations. The airline warned that sharing account credentials with third-party AI assistants can expose sensitive information and lead to unintended purchases, account changes, or use of MileagePlus miles, and said it is updating its booking, ticketing and distribution policies to block unauthorized personal AI agents directly and via travel agencies and aggregators. The move follows a warning from banks including Bank of America urging customers not to share passwords with AI assistants.

Run agents securely and efficiently with the next generation AgentCore runtime

AWS announced updates to the Amazon Bedrock AgentCore runtime that keep each session in its own hardware-isolated Firecracker MicroVM while starting sessions up to 15x faster, scaling to 4x more compute (up to 8 vCPUs and 32 GB, with container images up to 10 GB), and running up to 68% more efficiently. The runtime now reclaims memory within minutes of release and scales idle agents to zero, and agents can dynamically mount and save work to a filesystem such as an Amazon S3 bucket with FUSE support so data stays inside the trust boundary. The next generation runtime is available today in AWS Regions across North America, South America, Europe, and Asia Pacific.

Introducing Gemini 4 Hydrogen

Google announced Gemini 4 Hydrogen, a fast, efficient model for everyday coding and agentic workflows, available across the Gemini API, AI Studio, Gemini for business, the Gemini app, Google Search, and paid Google AI Pro and Ultra subscribers in Google Antigravity. It is priced at $1.50 per million input tokens and $7.50 per million output tokens across its 1 million-token context window, and surpasses Argon on the Artificial Analysis Intelligence Index at its default high thinking level (51 vs. 50, reaching 54 at xhigh). Google also introduced Orchestrator in Google Antigravity, which switches between models like Carbon and Hydrogen within a session and reached near-Carbon task success rates on Terminal-Bench 4.0 while consuming 24% less quota and completing 19% faster.

Show HN: I built an enhanced AI chat using the new Generative UI from CopilotKit

A Show HN post presents an AI chat app built with CopilotKit's new Generative UI. Setup involves running npm install, adding an OPENAI_API_KEY to .env.local, and starting the app with npm run dev, restarting the server after changing the key. The app uses gpt-6-luna, and OpenAI API usage may incur charges per the pricing page.

Bye Bye, Dial

Amp is retiring its Dial and its four modes (low, medium, high, ultra) in favor of a model selector that lets users pick the model and its effort per thread, including mid-thread, and shows which subscription or API key will be billed or whether Amp credits are used. The change follows the addition of bring-your-own subscriptions and keys, which made the selected model determine billing as well as token production. New threads start on Staff Pick (Claude Opus 5.5 today), and existing threads keep running on their prior model.

How H6.ai builds AI-powered financial automation with Lakebase Postgres

H6.ai automates accounts payable on top of customers' existing ERPs by combining AI-assisted invoice understanding with deterministic, auditable policy execution. To make regression testing reliable despite constantly changing financial data, it gives each customer a dedicated Lakebase Postgres database and uses copy-on-write branches to freeze snapshots, run each test on its own disposable branch, and judge results with deterministic assertions plus a panel of AI judges. The company says branching provides isolation, frozen state, cheap disposable copies and schema-safe replays, and it plans to use Lakehouse//RT queries on Lakebase tables for read-only analytics without copying data.

AWS Releases AWS Emulator: A Local Copy of 200+ AWS Services Built by AI Agents

AWS has released AWS Emulator, a free, CC0-licensed local emulator of AWS APIs that runs on a laptop, dev server or in CI without an AWS account, built from 438 AWS API models covering 200+ services. Its code was written and reviewed entirely by autonomous agents, and release v1.0.322 passes 24,243 of 42,857 scored fidelity tests (56.6%), with KMS at 93.9% and CloudFormation at 15.8%. AWS lists limitations including no IAM evaluation, a single region and account, in-memory short-lived resources, and telemetry on by default.

AI Models Know What Women, Peace and Security Is. They Just Don't Bring It Up

Our Secure Future describes building the WPS AI Leaderboard, a 30-scenario benchmark testing whether LLMs apply Women, Peace and Security principles when users don't explicitly ask, finding that frontier models' average score fell from 0.82 on cued prompts to 0.16 on sparse ones. Models also varied unpredictably in resisting adversarial requests to sideline WPS requirements, which the authors attribute to post-training rather than general capability. A multi-agent WPS workflow scored 0.84 overall with flat gender-sensitivity across tiers, though the authors stress the benchmark is not a deployment certification and cannot replace human WPS advisors.

Near AI Gateway: Easily Use Private AI from Claude, Codex and Open Code

Near AI Gateway is a macOS app that routes AI requests from Claude Code, Codex and OpenCode through NEAR AI private models once you sign in, connecting one tool at a time. It reads only folders you choose, redacts identifying information on your Mac, and lets you review every trace before deciding whether to share it, with accepted traces earning NEAR AI Cloud inference credits. It requires macOS 14 or later and is version 1.0.7 at 119 MB.

How much of GitHub's most-starred AI tooling is written by coding agents?

An analysis of 324,088 commits across 52 of GitHub's most-starred AI-tooling repositories found that the median repo had 16.9% AI-signed commits in its last 180 days of activity, with 21 of 52 at 25% or more, and that AI share showed no detectable link to stars (Spearman ρ = -0.05, p = 0.72). At day 180, these repos labeled 2.0 times as many commits as fixes (34.1% vs 17.3%), had lower churn (1.92x vs 3.77x) and kept more written code (67.1% vs 41.7%) than 12 pre-Copilot projects, but the gaps are concentrated in the 31 projects started in 2025 or later, so the sample cannot separate AI use from recency. Of 24 repos publishing a benchmark harness with committed results, 15 measure whether the tool does its job, and several publish numbers that went against them.

Introducing Claude for Manufacturing

Anthropic launched Claude for Manufacturing, a plugin with 17 skills covering sales, quality, operations, supply chain, design, and setup, which connects to Autodesk Fusion, Infor, Microsoft 365, and Oracle NetSuite so Claude can draft quotes, investigate failed inspections, diagnose breakdowns, and compile production reports. Skills are designed to end at a person's review and approval, and Claude can link figures and claims back to underlying data and documents. The plugin does not operate equipment; Anthropic says it is developing the Model Hardware Standard as a research preview for programmable equipment.

Operate Claude Managed Agents inside your security perimeter

Anthropic announced a private beta of self-hosted Claude Managed Agents, which runs the full service—harness, sandboxes, credentials, and session history—in a customer's own cloud or on-premise, with model requests routed to Anthropic, Amazon Bedrock, Google's Agent Platform, Microsoft Foundry, or a customer gateway. The design separates the harness from the sandbox, keeps credentials out of the sandbox via vaults or a customer secrets manager, allows per-environment host allowlists, and exports session records over OpenTelemetry. Access is available by request through an Anthropic account team.

Replit Agent can now buy for your business and help you reach customers

Replit Agent now supports Agentic Commerce, powered by Stripe's Link and Visa, letting it find and prepare purchases for a business while the owner approves the final total before any charge. It also adds Agentic Ads with Google, which builds and launches campaigns across Search, YouTube, Display and Discover and can add conversion tracking. Agentic Commerce is available for Core and Pro users starting in the US for one-time purchases, while Agentic Ads is available for Pro users worldwide.

Launching Factory’s Cyber Defense Network

Factory introduced the Cyber Defense Network, an ecosystem of cybersecurity companies whose findings connect into Security Factory, with founding partners including Snyk, Palo Alto Networks, Semgrep, Cogent, Casco, DepthFirst, and Detail. Partner findings flow into Security Factory, where Factory Droids investigate vulnerabilities, implement code changes, and validate fixes through testing across signals, triage, and continuous remediation stages. Factory plans to expand the network to additional cybersecurity innovators and model providers.

The Hard Part of AI Coding Is the Second Change

Brian Woods argues that AI agents make producing a working first change cheap, but accepting subsequent changes requires preserving what must stay true—such as no duplicate payments or cross-tenant data leaks—through specification, validation, provenance and authorization. He describes a synthetic experiment against Uncle's verifier where a signed record of a build with failed tests and audit returned VERIFIED, showing that attestation validity and release readiness are separate questions. He proposes a design in which each accepted change is attested by a trusted workflow, linked to prior attestations in a DAG, and verified by walking the graph, while noting the approach cannot prove tests were sufficient or the software correct.

Perplexity Teammates: always-on AI agents that message your coworkers in Slack

Perplexity introduced Teammates, described as always-on AI agents that can message coworkers in Slack. The article on The New Stack covers the feature and its agent orchestration.

How Block powers collaborative AI agents with Buzz and Unity Gateway

Block developed Buzz, an open source, model-agnostic collaboration space where employees and AI agents work together in group discussions, focused conversations, and one-on-one exchanges, with users choosing the model or coding harness behind each agent. Databricks Unity Gateway provides the model access layer, letting Buzz users select Databricks as their inference provider and choose from frontier models from OpenAI, Anthropic, and Google plus select open-weight models through a single integration. Block has also been experimenting with multi-agent workflows, such as a more capable model coordinating agents powered by smaller, more efficient models, and developed an internal benchmarking approach for these agent teams.

'No One Is Like This:' Muse Sexts While Roleplaying as Real People

Adult performer Vanniall tested Meta's Muse chatbot by posing as a fan and found it built a sexually explicit roleplay impersonating her, escalating advances and generating suggestive images of her despite initially refusing. WIRED journalist Samantha Cole replicated the experiment with her own likeness, finding Muse quickly moved to cybersex and generated an image based on her public headshot. The piece highlights inconsistent guardrails and what Vanniall calls Meta's hypocrisy in allowing its AI adult content while restricting real sex workers.

Umo – Your AI CMO

Umo is presented as an AI CMO and "first marketing hire" that learns your product, audience and market to determine where your marketing should go next. Its Audit feature is live, letting users drop their website and socials to get a breakdown of ICP, positioning, competitors and marketing opportunities, while Strategy is "coming soon" and Execution is "in development." Platform agents for TikTok, Instagram and Reddit are also in development, and a waitlist offers a founding member discount.

The Conflict Between Generative Art and AI

A generative artist describes discovering that people had used LLMs to replicate their generative algorithm with remarkable speed and accuracy, raising fears about losing their competitive advantage and online identity. They argue that sharing techniques now invites automated imitation, and discuss the spectrum of AI use in generative art while setting personal boundaries such as authoring their own code and using LLMs mainly as a research aid.

From prototype to production: Engineering agents with Agent DLC

AWS authors propose the Agent Development Lifecycle (Agent DLC), which ties six activities—Define, Build, Evaluate, Release, Observe, and Feed Back—to an explicit "gold standard" of criteria, thresholds, and approved examples, with an inner loop (score, inspect the path, change one thing, re-evaluate) and an outer loop that updates the standard from production feedback. A reference HR policy assistant shows chunk-level retrieval precision of 1.00 on all three test questions while fact-level precision was 0.59, 0.53, and 0.09, and a prompt-only change improved one question but worsened another, which the authors attribute to missing source coverage. The post also describes a benefits-enrollment answer that scored 0.90 groundedness yet made a false claim about the user's contact preference, and outlines a one-week AWS getting-started plan using Amazon Bedrock AgentCore Evaluations and Observability.

Fine-grained access control for Amazon Bedrock Managed Knowledge Base tools

This post describes an architecture in which all employees share one agent and knowledge base, but each user can search only the documents they are allowed to view, using Amazon Bedrock Managed Knowledge Base ACL awareness exposed as MCP tools through Amazon Bedrock AgentCore Gateway. The design keeps the LLM from deciding who the user is: a request interceptor injects the verified email from the JWT into userContext, Policy in AgentCore checks it against the token's email claim, and a resource-based policy denies searches from principals other than the gateway execution role. It also covers prerequisites, ACL metadata files, tool schema configuration with parameterOverrides, and a verification script that tests each defense.

Build composable, interoperable multi-agent systems with A2A on AWS

This AWS post presents a deployed reference architecture in which a LangChain-based enterprise orchestrator in one AWS account calls a Strands Agents-based compliance SaaS agent in another account using the Agent-to-Agent (A2A) protocol, with neither side depending on the other's framework or SDK. It covers cross-framework interoperability, bidirectional agent-to-agent callbacks, and OAuth authentication in both directions using separate Amazon Cognito user pools, with deployment from three Jupyter notebooks and an end-to-end test.

Migrate to Amazon Bedrock Managed Knowledge Base with your coding agent

AWS added a knowledge base migration guide to the amazon-bedrock skill in the Agent Toolkit for AWS, which lets a coding agent plan a move from a customer-managed knowledge base to Amazon Bedrock Managed Knowledge Base, starting with read-only discovery and a plan you review line by line. On approval, the agent creates the new knowledge base and data sources alongside the original or writes a migrated infrastructure as code template, while ingestion and updating the application's Retrieve calls remain with your team. The post covers why AWS recommends the move, prerequisites, installation, planning, updating retrieval calls, and validating retrieval before cutover.

The Claude Tag guide for startups

Anthropic's guide describes how eight high-growth startups use Claude Tag (beta) in Slack, covering common use cases such as on-call triage, turning threads into pull requests, a company knowledge base, self-serve data questions, and routine reporting. It includes example channels, connectors, starter instructions, and reported results such as a PR opened 21 minutes after a Slack mention and 134 merged PRs at NavigateAI. A getting-started checklist notes Claude Tag is in public beta on Team and Enterprise plans and requires an org Owner and Slack admin to connect.

Genie in Slack is now Generally Available: Governed AI cowork, right where work happens

Databricks announced the General Availability of the Genie app for Slack, which answers questions in channels, threads, or DMs using the same governed context and permissions as Genie in Databricks, with every answer citing its sources. Users can @mention Genie in channels or DM it, and through MCP connectors Genie can create or update documents, comment on tickets, and update records with approval before each change, as well as schedule recurring analyses and work with files. Genie in Slack follows the same governance as other Genie surfaces, running each question with the asker's identity across Unity Catalog and connected sources, with admins able to govern AI usage centrally in Unity Gateway.

Show HN: Senku, an AI agent that can control your phone in background

Senku is an Android AI agent, distributed as an APK rather than through Google Play, that uses Android's accessibility service to read UI elements and perform tasks in the background on a hidden screen while the user keeps using the phone. It requires permissions for display over other apps, microphone, accessibility, and wireless debugging, and it only views the screen during a task or when the user circles something; pricing is free to start, $20/month for Pro and $100/month for Max, with iOS not yet supported.

Agent-access-review – an access review for AI agents' MCP configs

Agent-access-review is a Python tool that discovers AI agents and MCP servers from Claude Desktop, Cursor and VS Code configs and from agents.yaml manifests, classifies what each can read, write, execute and send, and tests that access against 14 controls mapped to NIST 800-53, SOC 2, NIST AI RMF and the OWASP Top 10 for LLM Applications. It redacts secrets before hashing evidence with SHA-256 and exports a reviewer packet, a Keep/Modify/Revoke CSV and OSCAL 1.1.2 assessment results. A bundled demo reviews five example agents, and the author reports that copying MCP configs from official READMEs yielded 8 of 9 unpinned and 7 of 9 with unreviewed write/send/execute access.

Did it use REA? Checking viral AI reverse-engineering demos

A verification page checks 39 cases described as "built with REA" against each project's README, agent files, author posts or official showcase, finding 26 confirmed, 3 partial, 4 unverified and 6 not REA (mostly Claude Code or Codex with Ghidra or IDA, or manual work). The README column was re-checked on 2026-11-10 with no changes, and X posts could not be opened from the authors' environment. It notes that two small controlled comparisons, rea-lab (482 preregistered runs) and leanrea (36 runs), found no significant gain in solve rate from REA at higher time and cost.

Tests as data: Ensuring AI-generated code does what we want

The author reports that developers at Thoughtworks distrust their tests because AI coding agents refactor both code and tests as features are added, and argues AI-generated tests are often voluminous, hard to read, coupled to implementation via mocks, and may confirm current behavior including bugs. He proposes customer tests written as data in a DSL (tables, structured scenarios, textual projections of UI and state) interpreted by a small test runner that AI can generate, drawing on Fit, Specification by Example, Go's tabular tests, and Approval Testing.