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#Deployment
Oct 30Fri
  1. AWS Machine Learning Blog38

    Building intent-driven UI testing with Amazon Nova Act

    Epsilon's Agentic Platform team built a multi-tenant UI testing service on Amazon Nova Act and Amazon Bedrock AgentCore Browser Tool, layering natural-language, intent-based tests on top of its existing Playwright regression suite. The service runs each workflow's plain-English steps through Nova Act over a CDP WebSocket in managed, ephemeral browser sessions, capturing per-step screenshots and pass/fail results. Epsilon reports 4-6x faster test authoring (an 18-step workflow took 5-10 minutes versus 30-90 minutes for an equivalent 80-150-line Playwright script) and a 100 percent pass rate on saved trajectory replays.

  2. Prime Intellect Blog34

    ResearchOCT 29TH, 2026Prime Mega MoE: Fast Fused MoE Kernels for Training

    Prime Mega MoE extends DeepSeek's Mega MoE kernel, which previously had only a forward implementation, with a fast overlapping backward pass so it can be used for training. It reports up to 3.11× faster MoE kernels than the default PyTorch-based implementation and up to 1.34× faster end-to-end training than the Prime-RL baseline (34% higher throughput). Supported data types are bfloat16, MXFP8 (Blackwell only) and blockwise FP8 (Hopper only).

  3. Hacker News AI58

    Show HN: Kinoloom – A local AI film studio for an 8 GB GPU

    Kinoloom is a one-person Windows project that runs large open video models (LTX-2.5 at 22B parameters and MiniMax H3 at about 20B) on a single 8 GB RTX 3070 by giving the card one model at a time and streaming the rest from 64 GB of system RAM. It wraps the models in a local web app with an LLM story writer, a story bible, Qwen-Image 2.1 cast portraits and opening frames, a seamless-chain engine that joins short clips in latent space before decoding, face-identity QA via InsightFace, and an assembler that cuts the film. The author reports about 6 minutes for a warm 5-second 1080p LTX-2.5 clip and 20-22 minutes for MiniMax H3, notes the project has been tested on only one machine, and does not publish H3 renders because the H3 Community License restricts use and output display in the EU, UK, South Korea and the US.

  4. Hacker News AI38

    Teaching a 1999 VB6 app to talk to AI agents

    The author added a headless mode to the VB6-based SQL Server Comparison Tool (SCT) that runs saved comparisons and emits versioned JSON, plus a small C# MCP server (SctMcpServer.exe, .NET Framework 4.8) that lets Claude Desktop list and run those comparisons. A key bug was that Claude Desktop starts MCP servers with a stripped-down environment missing %CommonProgramFiles%, causing ADO error 3706 until the server restored standard Windows variables. The design restricts the AI to saved comparisons with no server choice, credentials, writes or row data, and shipped in SCT version 6.0.

  6. Simon Willison58

    Building a multiplayer game world with autonomous Fable-class models

    This piece by Jacob Sansbury describes Spawn, a massively multiplayer gaming environment where players prompt an in-game agent, Savi, to modify the game world, and which is now developed autonomously by a swarm of Fable-powered agents costing over $3 million in tokens per month. Agents change live code directly and ship to production hourly, with about 60% of work starting from production errors, Savi bug reports, log anomalies or feature requests, and an hour without a ship treated as a SEV-0 incident. Sansbury says Fable 5 (and then 5.1) made this level of autonomy possible, while a GPT-6 Astra attempt to apply security-review fixes disabled every feature instead.

  7. AWS Machine Learning Blog55

    Build a repeatable PHP-to-Java migration engine with Kiro

    This AWS post describes a PHP-to-Java migration engine packaged as versioned Kiro skill files (php-model-discovery and php-to-java-migration) that can be run either interactively in Kiro or agentically at portfolio scale via AWS Transform. The engine uses a dependency-free PHP scanner to emit a JSON manifest of models, fields, relationships and review flags, then follows an eight-phase, parity-first workflow in which a parity harness is built before any Java is written and the PHP code serves as the specification. A sample project migrates four Laravel Eloquent models to Spring Boot 3.4.1 on Java 21 with Maven and H2, and the post notes the parity harness was not built for that slice, calling it "the single biggest gap."

  8. Hacker News AI58

    Show HN: Sheetgraph, AI agents can understand complex spreadsheets

    Sheetgraph is a Rust-built local binary that extracts Excel and Google Sheets files into a short REPORT.md plus a formula dependency graph, keeping every cell for exact lookups; a 120k-cell invoice ledger compresses to about 7k tokens instead of roughly 1.3M. It ships as an agent skill for Claude Code, Codex and Cursor, and supports drill-down commands (cells, trace, find) for querying specific values. It is in beta (0.1), and the report format and library API may change between releases.

  9. Hacker News AI58

    Show HN: phpClaw – AI agent runtime for PHP with tools, memory and guards

    phpClaw is an MIT-licensed AI agent runtime for PHP that provides a built-in ReAct loop, pluggable tools, memory, and eight default security guards, with zero framework dependencies in core. It auto-detects seven LLM providers from environment variables, ships eight framework and CMS adapters (Laravel, Symfony, Drupal, Magento, WordPress, Joomla, OpenCart, PrestaShop), and includes an MCP server for exposing tools to Claude Desktop and Claude Code. It also offers pipelines and graphs with human pause/resume and fan-out, and requires PHP 8.1–8.4 with ext-curl, ext-json, and ext-mbstring.

  10. Baseten Blog30

    Baseten and Postman: Building reliable, cost-efficient agents for the enterprise

    Postman's Agent Stack (Passport, Fabric, Astropods, Fern) provides tools to build, secure, and govern enterprise agents, while Baseten serves as its recommended inference partner, offering fast model APIs, multi-cloud capacity management with zero data retention by default, and post-training infrastructure. Baseten cites seven 2026 model launches ranking in the top two on Artificial Analysis for throughput and latency, and notes Harvey post-trained a 27B open model to match closed-source frontier performance on its legal agent benchmark. The post describes post-training via supervised fine-tuning and reinforcement learning, with customers retaining model weights, evaluations, and training scripts.

  11. Claude Platform Release Notes22

    Claude Platform release notes — November 12, 2026

    The Claude Platform release notes list changes to the Claude API, client SDKs, and Claude Console, newest first, with entries from September 1 through October 29, 2026. Recent items include the beta Usage and Cost Analytics API, a raised 128 MB maximum request size for the Messages and Token Counting APIs, the beta Claude Tag API for Claude Enterprise, Claude Models on Google Cloud (Anthropic managed), and API version 2026-10-21 with new SDK and CLI releases. Earlier entries cover the launches of Claude Opus 5.5, Claude Sonnet 5.5, Claude Haiku 5.5, and Claude Fable 5.1, along with user profiles, organization webhooks, and OpenTelemetry export.

  12. Amazon Science38

    Speeding up language models for travel applications

    Researchers combined knowledge distillation, which trains a compact student model on a large teacher's outputs, with Medusa, a framework that predicts multiple tokens in parallel, and applied the pipeline with Booking.com to three travel features. The final model matched the quality of a 70-billion-parameter teacher while running 10 to 20 times as fast, with reported gains including 2.9% higher engagement versus GPT-3.5 for AI Trip Planner and 15-times-faster Smart Filters responses for 99% of queries. The work received the Industry Track best-paper award at ACL.

  13. AWS Machine Learning Blog58

    How MoEngage turned over 400 APIs into agent tools with AgentCore Gateway

    MoEngage used Amazon Bedrock AgentCore Gateway to expose roughly 400 internal REST APIs across seven AWS Regions as permission-scoped agent tools, avoiding over 20 separate MCP servers and per-API networking. Cedar policies filter tools server-side per agent identity, managed egress over Amazon VPC Lattice keeps APIs private, and teams expose operations by annotating OpenAPI specs rather than writing MCP code. MoEngage estimates the approach saved about six months of platform engineering effort, with new API onboarding now taking hours instead of days.

  14. AWS Machine Learning Blog36

    Lend and borrow resources across teams with AWS Batch’s quota management for SageMaker Training jobs

    AWS Batch now offers quota management, letting administrators divide compute capacity into quota shares per team or project with RESERVE, LEND, or LEND_AND_BORROW sharing strategies, plus cross-share and optional in-share preemption. The post walks through configuring a Scheduling Policy, Service Environment, and job queue, then submitting SageMaker Training jobs to quota shares via the SageMaker Python SDK v3 aws_batch module.

  15. Hacker News AI55

    Dive Apps: Superpowers for AI Builders by MotherDuck

    MotherDuck launched Dive Apps, fully custom data apps built with an agent that run on the MotherDuck data warehouse and can write back to source systems via Flights, its serverless Python runtime. Dive visualizations can trigger Flights to update MotherDuck data, write to source systems, send emails, post in Slack, rerun machine learning models, or launch an agent harness. MotherDuck positions Dive Apps for replacing SaaS apps, automating operations, and keeping humans in the loop to steer agents, citing SSO, RBAC, and table, row, or column level security.

  16. Meta Engineering58

    Catching Bugs Before They Land: JiTTesting’s Human-on-the-Loop Approach at Full Scale

    Meta reports that its Catching JiTTests system, which uses LLMs to generate executable tests that fail on risky code diffs before they land, is now part of its production infrastructure rather than a research prototype. The system combines intent-aware and "dodgy diff" test-generation workflows with an LLM-as-Judge ensemble and a rule-based assessor, and uses a human-on-the-loop model where engineers review outcomes at an aggregate level. Meta says 589 engineers (64% of outreach) engaged with the system, which showed a 60% true-positive rate and helped catch 74 serious privacy bugs at the diff stage in the first half of 2026, lowering privacy SEVs by 20%.

  17. Hacker News AI47

    Luma – smart launcher for you, and your AI agent

    Luma is a Linux launcher that fuzzy-searches apps and files, offers opt-in CLIP semantic photo search and OCR text-in-image search, a calculator and currency conversion, and exposes the same photo and screenshot index to AI agents via an MCP server (luma mcp) and CLI (luma query). It runs locally by default, with only model downloads and exchange rates leaving the machine, and supports Hyprland, niri, GNOME and KDE. The page reports one agent prompt taking 11 s with Luma versus 1 min 26 s without.

  18. TechCrunch · AI40

    Ex-Palantir execs launch Dream with $17M from a16z to build AI world models for construction

    Andy Alder and Arjun Mather, former Palantir colleagues, launched Dream, a startup building world models that automate building design and engineering for the architecture, engineering, and construction industry. Dream emerged from stealth with $17 million in seed funding led by Andreessen Horowitz, with SV Angel, XYZ, and Zigg Capital also participating, aiming to replace legacy tools like Autodesk's AutoCAD and Revit. Its model is trained on more than 100 million square feet of building data from U.S. permit archives and is already deployed across 10 active projects in Texas and California.

  19. AWS Machine Learning Blog41

    Accelerate agentic AI with NVIDIA Nemotron models on Amazon EKS and SageMaker HyperPod EKS

    NVIDIA Nemotron 3.5 Super VL is a 120B-parameter mixture-of-experts model activating 12B parameters per token that handles text, image, document, and video input, joining other Nemotron models already on AWS. The post describes its hybrid Mamba-2, MoE, and attention architecture with a RADIO vision encoder and up to 1M-token context, then shows deployment on Amazon EKS, EKS Auto Mode, and SageMaker HyperPod EKS using NVIDIA Dynamo and vLLM, with validation and performance results on B200 and H200 instances.

  20. NVIDIA Blog40

    Into the Omniverse: How Developers Turn Ideas Into Simulations With Frontier AI Agents

    NVIDIA describes a series of developer projects in which frontier AI models such as GPT-6 Astra are directed through natural-language instructions to build simulations using Omniverse libraries for GPU-accelerated physics, rendering and sensor simulation. Examples include recreating an OP-1 synthesizer in Houdini, testing robotic disassembly in Isaac Sim, reconstructing buildings from site scans, and a gas-turbine what-if application. Other projects cover SimReady asset scene assembly, warehouse performance scaling, cable routing, CAD-to-SimReady conversion, humanoid simulation, autonomous-driving testing, sensor-based digital twins, Robo Olympics, an ISS browser model and room reconstruction.

  21. Hacker News AI34

    Running Self-Hosted AI Agents on Oxide

    Oxide explains that AI agents should run in virtual machines rather than containers for stronger isolation, with an orchestrator VM provisioning ephemeral VMs for each agent session and cleaning them up afterward. The post walks through Claude Code self-hosted environments, where a spawn-runner hook creates ephemeral VMs and a separate reaper deletes stopped ones, and Amp self-hosted orbs, where a dispatch script handles spawn, pause, and delete operations. It also outlines future work on security, multi-rack scale, cold-start latency, and a possible microVM primitive.

  22. Hacker News AI22

    Serving Prefill and Decode for Agentic AI (On Tenstorrent Blackhole)

    Tenstorrent describes how its Galaxy systems, built on Blackhole chips, serve both prefill and decode phases on the same hardware so operators can shift capacity between them as agentic workloads change. The post explains how agent loops produce growing, largely cacheable context, models how faster decode only partly shortens dependent-call latency, and contrasts prefill's compute-bound long prompts with decode's memory-bound small batches. It cites a Wormhole FlashAttention kernel comparison (9 to 44 times faster than a basic implementation) as a measured example of data-placement control.

  23. Hacker News AI40

    Launch HN: Simantic (YC F26) – Firmware Simulation for AI Agents

    Simantic, founded by former firmware engineers from Neuralink and Tesla, is building a simulation layer that lets engineers and AI agents test and validate firmware without physical hardware. The offering includes virtual devboards programmable via a single API call, an AI code reviewer that uses the simulation as a verification engine, and a CI/CD pipeline that validates firmware against a simulated microcontroller on every commit. Users apply it to bare-metal and RTOS development for flight controllers, electric vehicles, robotics, and satellites.

Oct 29Thu
  1. Hacker News AI18

    Systems Thinking Is Vital in the Age of AI

    The article argues that as AI helps engineers handle early project steps once requiring several specialists, the engineer's role expands from performing each technical step to coordinating people, machines, and specialist knowledge. It stresses systems thinking and human judgment, since AI can produce convincing answers with weak assumptions, and calls on IEEE to build cross-field communities and practical standards for human-machine collaboration.

  2. Hacker News AI62

    Show HN: I built a tamper-evident flight recorder for AI agents

    Mnestiq is a flight recorder for AI agents that records what an agent read, decided and did, tags each piece of model context by provenance, and hash-chains records sealed by Ed25519-signed Merkle checkpoints so edits, deletions and reordering fail verification. It can be used without code changes via a proxy between the agent and model APIs, or through Python SDK wrappers for Anthropic and OpenAI clients, and includes a local dashboard with detection rules such as MNQ-001 for untrusted arguments in tool calls. The project is at version 1.0 under Apache-2.0, with a documented evidence format and a stated security model noting that evidence is tamper-evident after writing but a compromised host is not made truthful at write time.

  3. Hacker News AI38

    Least privilege for your customers' AI agents

    FusionAuth 1.70 introduces Client ID Metadata Document (CIMD) registration and RFC 8693 OAuth token exchange to give AI agents, including MCP servers, narrowly scoped delegation tokens with actor attribution rather than broad user credentials. The release also adds a Recorded Intent extension that logs an agent's stated objective for audit review, and offers entity-based or lambda-based policy engines for deterministic, testable authorization.

  4. vLLM Blog62

    Day 0 support for Mistral Large 4 on vLLM

    vLLM announces day-0 support for Mistral Large 4, a 1T-parameter MoE multimodal model with 49B active parameters per token, running on the V2 model runner with breakable CUDA graphs and a new vllm/models/mistral/ package. The work adds cross-layer KV sharing, DCP/PCP context parallelism, DSpark speculative decoding, NIXL-based disaggregated serving and HiSparse KV offload, plus day-0 ROCm support on AMD Instinct MI350 Series GPUs with MXFP4 experts. Support ships in the vllm/vllm-openai:mistral-large-4 Docker image, with FP8 and NVFP4 checkpoints and serving commands documented.

    Why it matters: A detailed engineering account of what it takes to land a frontier model on an inference engine, useful for teams planning long-context or disaggregated deployments.

  5. Hacker News AI62

    Show HN: SpaceApp – Self-hosted workspace running AI coding CLIs in parallel

    SpaceApp is an MIT-licensed, self-hosted workspace that runs up to 16 AI coding CLIs (including OpenCode, OpenAI Codex, Claude Code, Gemini, Qwen, Kimi, Grok and DeepSeek) side by side in persistent rooms on your own machine, installed with a single npx command on Linux, macOS or Windows 11. It adds a coordinating agent called Nous, optional copilots and studios, a Vault for logins, and a Space Gateway that uses your subscriptions before API keys. The post notes that rooms are not a security boundary between mutually untrusted users and links to a Known Limitations page.

  6. Hacker News AI58

    Sorry Harvey! I Made a Free Open-Source Alternative to Your Overpriced Legal AI

    The post introduces CaseCite, a free, open-source legal AI platform released under the Apache 2.0 license that handles cited legal research, document analysis, contract review and redlining, legal drafting, citation checks, and judge intelligence. It is self-hosted, runs on the user's own infrastructure, and supports the user's own AI models and API keys, with users paying only their own infrastructure and AI usage costs. The author acknowledges it is not yet as polished as Harvey's enterprise platform but says it covers a substantial portion of everyday legal workflows.

  7. Hacker News AI34

    Most AI pipelines are graphs. Graph engineering treats them that way

    The article argues that while prompt engineering and loop engineering treat the model call as the unit of work, most production AI pipelines are really graphs of steps whose dependencies, parallelism, duration and cost can be derived before running. It describes deriving edges from prompt references to other steps' outputs, using structured output as the graph's type system, and lessons from building a compiler and scheduler for such pipelines.

  8. Hacker News AI58

    You can just ask AI to do things

    The author argues that a key skill for working with AI is agency—being willing to try ambitious things—and lists everyday examples from his work: having agents start his dev server, run curl requests against it, poll metrics and logs during production changes, get second opinions from other models, do a 6am pass over unread messages and logs, improve their own setup, and manage their own sessions. He notes he still writes his own messages and reports, makes his own design decisions, and reviews code himself, and is often ruthless with agent suggestions.

  9. Hugging Face Blog36

    Granite Switch 4.1.1 — Update models like you update software

    Granite Switch 4.1.1 is a backwards-compatible patch release to Granite Switch 4.1 that adds an updated Granite Speech ASR model covering multilingual speech-to-text across 10 languages with native punctuation and capitalization, plus an updated Decision adapter in granitelib-core with improved performance on the Jev Decision Index test set. Apart from training the new ASR model and Decision adapter, nothing was recomputed and the base model is untouched. The team says it is working on tutorials and an Adapter SDK so developers and third-party providers can build their own adapters.

  10. Hacker News AI60

    Show HN: Vibecheck – a pre-launch security audit for AI-built apps

    Vibecheck is a zero-dependency scanner with 60+ checks plus AI-agent skills that audit AI-built apps for exposed secrets, missing Supabase RLS, auth gaps, and deploy misconfigurations, producing a 0–100 Launch Score with a GO/NO-GO verdict and copy-paste fix prompts. It includes an always-on guard hook that blocks agents from hardcoding API keys or committing .env files, and can run in CI via a single Node script with --fail-on critical. The audit is read-only, makes no network calls, and never runs the project's code.

  11. Hacker News AI22

    Project Baobab – Off-grid solar AI edge nodes with micro-payout incentives

    Project Baobab is a lightweight, decentralized edge-computing orchestrator that shards AI tasks across distributed low-power edge nodes such as Raspberry Pi 5 and off-grid hardware, settling compute rewards via automated micro-payments. It uses Python's concurrent.futures for task sharding and the PayPal REST API v2 (OAuth 2.0) to trigger payment orders upon verified task completion, targeting solar/battery-powered nodes. The project is built in Python 3.10+ and runs cross-platform on Linux, Debian, Ubuntu, and Raspberry Pi OS.

  12. ElevenLabs Blog25

    How we use ElevenAgents to save 1,200 hours a month in daily operations

    ElevenLabs says its internal agents save teams over 1,200 hours a month, answering more than 5,000 questions monthly and taking actions such as building customer demos and opening over 150 tickets in the last month. The agents span sales (GTM and FDE bots), support and engineering triage, and product data analysis, with lessons including schema curation over prompt engineering, injecting Salesforce picklist values into tool type definitions, pruning overlapping procedures, and verifying tickets after creation.

  13. Hacker News AI71

    Open-sourcing Deriv One: the self-hosted AI platform we run in production

    Deriv has open-sourced Deriv One, an MIT-licensed, self-hosted AI platform combining a reviewed skills catalogue, registered Slack agents, a multi-pane workspace, sandboxed code execution, and a no-code app builder, all running on one identity directory and secrets vault with usage tracked against the company's own model gateway. The team says the real problem was never discovery but control—deciding who can run which skill—and that 221 skills came from 54 people across the company. The repository includes provider interfaces, Docker images, Kubernetes starter manifests, and adopter documentation, but excludes Deriv's production cloud plugins, internal integrations, Terraform and Helm configuration, and Slack DMZ relay implementation.

  14. Hacker News AI58

    AWF – AI Workflow Framework

    AWF is an open-source ecosystem of three binaries: the Go-based AWF CLI for provider-agnostic YAML workflows, ZPM (Zig + Prolog) for deterministic logical reasoning via 22 MCP tools, and ztick, a push-driven Zig scheduler that can dispatch into AWF workflows. The project emphasizes deterministic replays, per-step token tracking, provider swapping via YAML, and static binaries with zero runtime dependencies.

  15. Hacker News AI35

    Open Source or Custom in Enterprise AI Systems?

    This article argues that as AI makes code generation cheaper, engineering judgment becomes more valuable, and that velocity metrics like PR volume or lines changed are weak signals of progress. It explains where quality breaks in AI-assisted systems—at integration boundaries, retries, observability, and governance—and recommends building on proven open-source components, applying Twelve-Factor and annotation discipline, then adding AI-assisted implementation with strict review, testing, and monitoring. It cites an advisory project for a U.S. industrial manufacturer where an internally built agentic system was rebuilt on the OpenAI Agents SDK for greater robustness and maintainability.

  16. Hacker News AI38

    AI infra financials leading/lagging indicators data vis and analysis page

    This page tracks early warning signs of an AI infrastructure build-out, linking every figure to a public source: borrowing costs for the riskiest junk-rated companies reached 13.21% as of Oct 27, 2026, big tech capex hit $566B in the 12 months to Jun 30, 2026, and AWS's H100 list price fell to $6.88 per GPU-hour. It also covers CoreWeave's $21B in capital spending against $7B in operating cash, a used-GPU resale index at 75 versus 100 in early 2025, and 1.4% data-center vacancy in main North American markets. The page pairs indicators in charts to flag divergences, such as spending rising while prices fall, and states it is research, not investment advice.

  17. Hacker News AI47

    Control Planes of Agentic AI Infrastructure for Reliable Software Delivery

    The article proposes five control planes—Context, Containment, Validation, Rollout, and Accountability—for safely scaling agentic software engineering, and argues that AI-generated code changes should be classified by production risk, with high-risk areas such as authentication, billing, permissions, and data migrations requiring more context, guardrails, and human judgment. It describes practices including architecture-focused context documents and specialist agents, feature flags and scoped cluster roles for containment, behavioral and feature-flag testing, rollback plans designed before deployment, and retained human ownership of high-risk decisions. A running example applies the workflow to modifying authentication systems across multiple deployment types.