<?xml version="1.0" encoding="UTF-8"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:news="http://www.google.com/schemas/sitemap-news/0.9">
  <url>
    <loc>https://modelsatwork.news/article/hugging-face-transformers-model-integration-contracts-shrunk-models-cpu-tests-umt5-bug</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T15:58:00.000Z</news:publication_date>
      <news:title>Hugging Face tests Transformers on shrunk models; one caught a 2-month bug</news:title>
      <news:keywords>Evals, Open source, Developer tools, Hugging Face, Agents</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/stroq-local-hooks-audit-coding-agent-commands-leaked-keys-show-hn</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T15:05:00.000Z</news:publication_date>
      <news:title>Stroq: open-source hooks that check what coding agents run and send</news:title>
      <news:keywords>Agent safety, Coding agents, Open source, Show HN, Agent security</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/flide-decision-model-inference-engine-9-5x-faster-vllm-sglang-show-hn</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T14:05:00.000Z</news:publication_date>
      <news:title>Flide: engine claims 9.5x faster decision-model inference than vLLM</news:title>
      <news:keywords>Decision models, Inference, Open source, Show HN, Self-hosting</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/impel-anthropic-customer-story-roleplay-agent-ramp-time-3-6-months-to-1-month-vendor-published</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T12:10:00.000Z</news:publication_date>
      <news:title>Impel: a sales roleplay agent cut new-product ramp to 1 month</news:title>
      <news:keywords>Case study, Vendor-published, Adoption, Agents, Model routing</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/mistral-studio-managed-agents-workflows-apps-vpc-on-prem-incident-agent-hundreds-of-hours-vendor-published</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T11:05:00.000Z</news:publication_date>
      <news:title>Mistral Studio adds managed agents, workflows and apps</news:title>
      <news:keywords>Mistral, Agents, Managed Agents, Human oversight, Vendor-published</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/simon-willison-hide-agent-written-pr-descriptions-details-summary-github</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T10:10:00.000Z</news:publication_date>
      <news:title>Simon Willison hides agent-written PR descriptions behind a summary</news:title>
      <news:keywords>Coding agents, Code review, Developer tools, Pull requests, Workflow</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/dharma-ai-vocabx-vocabulary-cuts-essay-grader-inference-cost-77-percent-vendor-published</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T03:10:00.000Z</news:publication_date>
      <news:title>Dharma AI: a rebuilt vocabulary cut a 4B grader's inference cost 77%</news:title>
      <news:keywords>Cost, Inference, Small models, Fine-tuning, Vendor-published</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/llama-modchip-deepseek-v4-flash-284b-64gb-ram-cpu-only-readme-claims-show-hn</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-08T14:10:00.000Z</news:publication_date>
      <news:title>llama-modchip: 284B DeepSeek model on a 64 GB CPU-only PC, says README</news:title>
      <news:keywords>Open source, Show HN, Self-hosting, Inference, Open-weight models</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/vidraft-backdoored-qwen-24-scans-clean-action-gate-denied-290-payloads-vendor-published</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-08T13:10:00.000Z</news:publication_date>
      <news:title>VIDRAFT: a backdoored Qwen passed 24 scans; an action gate blocked all 290 payloads</news:title>
      <news:keywords>Security, Agent safety, Agent security, Coding agents, Open-weight models</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/co-design-bench-coding-agents-fully-finish-26-percent-real-user-requests-preprint</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-08T09:55:00.000Z</news:publication_date>
      <news:title>Co-Design Bench: best coding agent fully finishes 26.4% of tasks</news:title>
      <news:keywords>Research, Benchmarks, Coding agents, Evals, Human in the loop</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/stanford-memorilla-16-memory-tokens-frozen-llm-agent-memory-preprint</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-08T02:10:00.000Z</news:publication_date>
      <news:title>Stanford's Memorilla gives a frozen LLM memory in 16 tokens</news:title>
      <news:keywords>Research, Agent memory, RAG, Context management, Token cost</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/video-rebirth-hyperflow-h3-flash-compressed-video-audio-model-runs-24gb-gpu-show-hn</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-08T00:00:00.000Z</news:publication_date>
      <news:title>HyperFlow H3 Flash: a 31B video model cut to 13.7B for one GPU</news:title>
      <news:keywords>Open source, Show HN, Self-hosting, Inference, GPU</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/waymark-durable-workflow-engine-postgres-agent-loops-show-hn</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-07T21:00:00.000Z</news:publication_date>
      <news:title>Waymark: a Postgres-only durable workflow engine for agent loops</news:title>
      <news:keywords>Agents, Open source, Show HN, Developer tools, Monitoring</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/dragonscale-kniv-v7-local-extraction-models-agent-memory-90x-faster-than-gpt-6-vendor-reported</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-07T20:00:00.000Z</news:publication_date>
      <news:title>Dragonscale's kniv v7: local fact extraction, 90x faster than GPT-6</news:title>
      <news:keywords>Open-weight models, Agents, Open source, Self-hosting, Token cost, Vendor-published</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/vals-ai-inkling-2-small-swears-in-reasoning-96-percent-of-failures-silent</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-07T19:05:00.000Z</news:publication_date>
      <news:title>Vals AI: Inkling 2 Small swears in 50 of 2,655 runs, a poor failure signal</news:title>
      <news:keywords>Agent evaluation, Monitoring, Agents, Research, Evals</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/ai-auditors-catch-agent-misbehavior-but-false-alarms-pile-up-hall-metr-malt</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-07T18:20:00.000Z</news:publication_date>
      <news:title>AI auditors catch most agent cheating, but false alarms pile up</news:title>
      <news:keywords>Agent evaluation, Agent safety, Verification, Research, Agents</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/nous-research-arete-27b-qwen-fine-tune-cuts-propaganda-rate-22-to-0-9-percent</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-07T16:58:00.000Z</news:publication_date>
      <news:title>Nous Research's Arete-27B cuts Qwen's propaganda rate from 22% to 0.9%</news:title>
      <news:keywords>Open-weight models, Fine-tuning, Evals, Model selection, Model release</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/article/vals-ai-cyberoffense-open-weight-deepseek-72-8-percent-vs-restricted-daybreak-80-8</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-07T16:20:00.000Z</news:publication_date>
      <news:title>Vals AI: open DeepSeek model nears OpenAI's restricted cyber model</news:title>
      <news:keywords>Security, Benchmarks, Open-weight models, Agent cost, Evals</news:keywords>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/briefing/2026-11-09</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-09T11:30:00.000Z</news:publication_date>
      <news:title>The briefing, 2026-11-09: Dharma AI says a new tokenizer cut its essay grader's inference cost 77% on the same 4B model</news:title>
    </news:news>
  </url>
  <url>
    <loc>https://modelsatwork.news/briefing/2026-11-08</loc>
    <news:news>
      <news:publication><news:name>Models at Work</news:name><news:language>en</news:language></news:publication>
      <news:publication_date>2026-11-08T11:30:00.000Z</news:publication_date>
      <news:title>The briefing, 2026-11-08: Alibaba-led preprint: the best of ten coding agents fully finishes 26.4% of real user requests</news:title>
    </news:news>
  </url>
</urlset>
