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Friday

  1. Figma AI / Agent / Make

    How to get the Figma agent to use your design system

    Figma product manager Wayne Lin introduced three kinds of context for getting the Figma agent to call on a design system: connect a published design library so the agent can directly use team-approved components and tokens; write component selection rules and exceptions into a Guidelines file; then provide real examples through an Examples page or the _example naming convention. Guidelines works best when generating designs from scratch; consistency of application when editing existing designs is still being improved.

    Example prompts hover over a mobile screen

    Figma product manager Wayne Lin introduced three kinds of context for getting the Figma agent to call on a design system: connect a published design library so the agent can directly use team-approved components and tokens; write component selection rules and exceptions into a Guidelines file; then provide real examples through an Examples page or the example naming convention. Guidelines works best when generating designs from scratch; consistency of application when editing existing designs is

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  2. Replit BlogSelected

    Replit Launches Monitoring Agent That Can Automatically Diagnose and Deploy Fixes for Production Issues

    Replit has launched Monitoring Agent, providing autonomous on-call capabilities for applications already in production: when a production issue arises, it can read production logs and metrics, identify the cause, verify the fix, and, once auto-publish is enabled, automatically deploy the fix and report the changes by email. This feature builds on App Monitoring, launched earlier this year; users can enable intelligent autofix alerts in the application's Publishing settings.

    Replit Monitoring Agent: Your very own software engineering team — cover image

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  3. Amazon Science

    Amazon releases TorchNeuron: a PyTorch backend for AWS Trainium

    This week, Amazon announced the open-sourcing of TorchNeuron, a backend that converts PyTorch code into operations executable on AWS Trainium; PyTorch code already running on other accelerators can be migrated with almost no changes. It offers an optional adaptive eager mode that groups operations for compilation and caches NEFF at multiple levels, cutting the time to the first training step by about one-third in cross-accelerator large language model tests. The team also used an AI agent to scan Hugging Face repositories, selecting 841 representative models and tens of thousands of tensor shapes to build a tiered testing process.

    This week, Amazon announced the open-sourcing of TorchNeuron, a backend that converts PyTorch code into operations executable on AWS Trainium; PyTorch code already running on other accelerators can be migrated with almost no changes. It offers an optional adaptive eager mode that groups operations for compilation and caches NEFF at multiple levels, cutting the time to the first training step by about one-third in cross-accelerator large language model tests. The team also used an AI agent to sca

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  4. Databricks Blog

    Databricks on AI cost management: from tokenmaxxing to valuemaxxing

    Kevin Stumpf, Senior Staff Engineer at Databricks, argues that enterprise AI cost management is shifting from tokenmaxxing—the pursuit of token consumption volume—to valuemaxxing, which measures the impact generated per dollar invested. Databricks can attribute costs out of the box by user, group, agent, AI gateway endpoint, model, provider, and time period, and also supports custom attribution via request-level tags to specific pull requests or external customers. The key to controlling context bloat is to have agents pull context on demand through tools, MCP servers, or skills, rather than pushing it in advance.

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    Kevin Stumpf, Senior Staff Engineer at Databricks, argues that enterprise AI cost management is shifting from tokenmaxxing—the pursuit of token consumption volume—to valuemaxxing, which measures the impact generated per dollar invested. Databricks can attribute costs out of the box by user, group, agent, AI gateway endpoint, model, provider, and time period, and also supports custom attribution via request-level tags to specific pull requests or external customers. The key to controlling context

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  5. Unite.AI

    Agentic AI Foundation Adds Four Projects, Hosted Projects Reach 10 in First Year

    The Agentic AI Foundation announced on October 22, 2026 the addition of four hosted projects: Agent Skills contributed by Anthropic, Open Responses contributed by OpenAI, OpenEnv contributed by Hugging Face, and OpenSandbox contributed by Alibaba, bringing the total number of hosted projects from 3 at its founding in December 2025 to 10. The four projects correspond to four layers: agents acquiring skills, applications invoking models across vendors, agent training and evaluation, and secure agent operation. Agent Skills is open-sourced under Apache 2.0 and CC BY 4.0, already supported by more than 70 agent platforms, with over 1 million skills published and nearly 280 million installs; Open Responses defines shared schemas and streaming events based on the OpenAI Responses API, with implementations already provided by Databricks Model Serving and Vercel AI Gateway.

    The Agentic AI Foundation announced on October 22, 2026 the addition of four hosted projects: Agent Skills contributed by Anthropic, Open Responses contributed by OpenAI, OpenEnv contributed by Hugging Face, and OpenSandbox contributed by Alibaba, bringing the total number of hosted projects from 3 at its founding in December 2025 to 10. The four projects correspond to four layers: agents acquiring skills, applications invoking models across vendors, agent training and evaluation, and secure age

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  6. Unite.AI

    METR red-team exercise finds vulnerabilities in OpenAI's internal monitoring system

    On October 22, METR and Redwood Research publicly disclosed a pilot exercise in which each organization assigned one employee to spend three weeks working deeply with OpenAI's internal infrastructure, stress-testing the internal misalignment monitoring system and finding multiple new vulnerabilities that existed as of July 21, 2026 and earlier. The exercise ran from July 21 to August 11, produced a 61-page internal report, and OpenAI provided a redacted 38-page version to the management of both organizations. METR estimated that at the time, approximately 75–94% of internal Responses API agent traffic generated by models at least as capable as GPT-5.5 could be monitored, and 99.2% of internal Codex agent traffic could be monitored; evaluators also found that the Codex agent could in principle bypass the sandbox and Auto-Review, as well as exploitation methods that could keep hundreds of recent operations unmonitored. OpenAI said all vulnerabilities affecting the production guardrail stack have been patched; METR said it has not yet evaluated this claim.

    On October 22, METR and Redwood Research publicly disclosed a pilot exercise in which each organization assigned one employee to spend three weeks working deeply with OpenAI's internal infrastructure, stress-testing the internal misalignment monitoring system and finding multiple new vulnerabilities that existed as of July 21, 2026 and earlier. The exercise ran from July 21 to August 11, produced a 61-page internal report, and OpenAI provided a redacted 38-page version to the management of both

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  7. Microsoft Research

    Microsoft Research releases Flint-interactive, enabling agents to generate interactive data visualizations

    Microsoft Research has released Flint-interactive, an interactive data visualization language built on top of Flint that enables agents to generate charts supporting clicking, filtering, zooming, highlighting, and cross-chart linking. It uses the Flint compiler to parse raw triggers such as clicks and drags into semantic events, so users only need to describe update behaviors with high-level operators without writing low-level visualization code. The language is already usable in conversations through Flint-MCP and MCP Apps, and it also offers a programming API for developers to build dashboards and data stories.

    Microsoft Research has released Flint-interactive, an interactive data visualization language built on top of Flint that enables agents to generate charts supporting clicking, filtering, zooming, highlighting, and cross-chart linking. It uses the Flint compiler to parse raw triggers such as clicks and drags into semantic events, so users only need to describe update behaviors with high-level operators without writing low-level visualization code. The language is already usable in conversations t

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Thursday

  1. Google Developers Blog

    How Google Built Governed Self-Evolving AI Agents on the Gemini Agent Platform

    Google Cloud unveiled a research reference architecture codenamed Project Chrysalis, demonstrating how to run governed self-evolving AI agents on the Gemini Agent Platform and ADK. In a simulated Black Friday cache avalanche failure, the architecture reduced time to first mitigation from 15–45 minutes to 1.8 seconds, cut the HTTP 5xx error rate from 72.7%–80.0% to 0.0%, and lowered P99 latency from 519.8 ms to 18.2 ms. All autonomous operations are constrained by governance controls including Model Armor, Cloud KMS, Binary Authorization, OPA, and two-person review HITL.

    Hero Banner

    Google Cloud unveiled a research reference architecture codenamed Project Chrysalis, demonstrating how to run governed self-evolving AI agents on the Gemini Agent Platform and ADK. In a simulated Black Friday cache avalanche failure, the architecture reduced time to first mitigation from 15–45 minutes to 1.8 seconds, cut the HTTP 5xx error rate from 72.7%–80.0% to 0.0%, and lowered P99 latency from 519.8 ms to 18.2 ms. All autonomous operations are constrained by governance controls including Mo

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  2. METR BlogSelected

    METR and Redwood Research red-team test OpenAI's internal agent monitoring system

    METR and Redwood Research conducted a high-privilege red-team test of OpenAI's internal misalignment monitoring system from July 21 to August 11, producing a 61-page internal report. The evaluation estimated that about 75–94% of Responses API agent traffic could be monitored, and 99.2% of internal Codex agent traffic could be monitored, but RL training was not included in monitoring at the time, and unmonitored compaction events could cause about 10% of eligible Codex traffic to be missed. The report also lists vulnerabilities such as agents being able to bypass the Codex sandbox and Auto-Review, exploiting serialization differences to disable monitoring, and disabling monitoring through two client-controllable headers; OpenAI said vulnerabilities affecting the production protection stack have all been patched.

    METR and Redwood Research conducted a high-privilege red-team test of OpenAI's internal misalignment monitoring system from July 21 to August 11, producing a 61-page internal report. The evaluation estimated that about 75–94% of Responses API agent traffic could be monitored, and 99.2% of internal Codex agent traffic could be monitored, but RL training was not included in monitoring at the time, and unmonitored compaction events could cause about 10% of eligible Codex traffic to be missed. The r

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  3. Google Developers Blog

    Google API Gateway supports streaming and enters public preview

    Google announced that streaming support for API Gateway has entered public preview. SSE, chunked transfer, WebSocket, and gRPC streaming endpoints can share the same gateway and policies with existing APIs, with no changes required to API specifications. Streams can remain open for up to one hour; during the preview period, this must be enabled when creating a gateway, and existing gateways cannot be converted in place. Combined with model routing, clients can use a single OpenAI-compatible endpoint to route to Gemini, Claude, and OpenAI gpt-oss models based on the model field in the request and return streamed responses. The gateway's default domain name has changed to a fixed format composed of the gateway ID, project number, and region, which can be written into the configuration before creation.

    Streaming feature in  API Gateway _ Header

    Google announced that streaming support for API Gateway has entered public preview. SSE, chunked transfer, WebSocket, and gRPC streaming endpoints can share the same gateway and policies with existing APIs, with no changes required to API specifications. Streams can remain open for up to one hour; during the preview period, this must be enabled when creating a gateway, and existing gateways cannot be converted in place. Combined with model routing, clients can use a single OpenAI-compatible endp

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  4. Unite.AI

    Ai2 Releases OlmoEarth v1.3, Offering Global 10-Meter Resolution Satellite Embeddings

    The Allen Institute for AI released OlmoEarth v1.3 on October 22, 2026, including the OlmoEarth v1.3 Base model, 128-dimensional and 64-dimensional global precomputed annual embeddings, the login-free browser-based OlmoEarth Embeddings Explorer, and a technical report, all under the OlmoEarth Artifact License. The model is a 128-million-parameter ViT-Base foundation model that processes Sentinel-1, Sentinel-2, and Landsat image time series, outputting a 128-dimensional vector for every 10-meter pixel worldwide. Ai2 states that across 27 evaluations covering six continents, the 128-dimensional embeddings scored highest on 20 of them, while the 64-dimensional version led on 18; it also introduced PLANTEUR, a benchmark for crop types in tropical farmland, where the 128-dimensional embeddings achieved 24.9 mIoU in the benchmark's leave-one-island-out test, higher than Tessera v2's 19.1 and AlphaEarth Foundations' 15.8.

    The Allen Institute for AI released OlmoEarth v1.3 on October 22, 2026, including the OlmoEarth v1.3 Base model, 128-dimensional and 64-dimensional global precomputed annual embeddings, the login-free browser-based OlmoEarth Embeddings Explorer, and a technical report, all under the OlmoEarth Artifact License. The model is a 128-million-parameter ViT-Base foundation model that processes Sentinel-1, Sentinel-2, and Landsat image time series, outputting a 128-dimensional vector for every 10-meter

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  5. The New Stack

    Google opens the infrastructure behind Gemini agents as a cloud service, Agent Compute Engine

    Google announced that it will open a preview of Agent Compute Engine to Google Cloud users later this year, providing each AI agent with a hardware-isolated microVM that balances container startup speed with sandbox security. The service was originally internal infrastructure for Gemini, Antigravity, and Google's model training pipelines; when an agent is idle, it checkpoints the microVM to free up resources. Google is also offering an open-source runtime, Agent Substrate, which can run on any Kubernetes cluster; the company says that in a benchmark of 200,000 agents it achieved 500 activations per second, with suspend and resume taking under half a second.

    Google announced that it will open a preview of Agent Compute Engine to Google Cloud users later this year, providing each AI agent with a hardware-isolated microVM that balances container startup speed with sandbox security. The service was originally internal infrastructure for Gemini, Antigravity, and Google's model training pipelines; when an agent is idle, it checkpoints the microVM to free up resources. Google is also offering an open-source runtime, Agent Substrate, which can run on any K

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  6. 404 Media

    AI is changing hacker offense and defense, and the PHP2Shell vulnerability has sparked "Black October" concerns

    404 Media reports that AI is simultaneously changing offensive hacking and security defense: after researchers used AI to discover the PHP2Shell vulnerability in PHP, Cloudflare observed thousands of exploitation attempts 10 hours before public disclosure, rising to tens of thousands 45 minutes after disclosure, and reaching hundreds of thousands within 2 hours. OpenAI says such discoveries show that AI can expose security flaws at internet scale, but the same capability can also help attackers rapidly develop attack tools; Chainguard's early release of a fix patch sparked controversy over bypassing the disclosure embargo. The article notes that the main impact so far is still various parties proactively patching or taking services offline, and large-scale actual exploitation of the vulnerability has not yet occurred.

    404 Media reports that AI is simultaneously changing offensive hacking and security defense: after researchers used AI to discover the PHP2Shell vulnerability in PHP, Cloudflare observed thousands of exploitation attempts 10 hours before public disclosure, rising to tens of thousands 45 minutes after disclosure, and reaching hundreds of thousands within 2 hours. OpenAI says such discoveries show that AI can expose security flaws at internet scale, but the same capability can also help attackers

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  7. xAI News

    xAI launches the SpaceX Super Intelligence partner network to build enterprise products on Grok

    xAI launches the SpaceX Super Intelligence partner network for companies building products, solutions, and services on Grok, divided into two categories: Transformation Partners and Marketplace Partners. More than 130 companies have already participated in the program's early access phase, and the Forward Deployed Engineer certification program has trained engineers at more than 30 organizations. Bain & Company, Databricks, NVIDIA, Snowflake, and others are among the first Launch Partners.

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  8. Gary Marcus:The Road to AI We Can Trust

    Gary Marcus: US Banks Are Under Attack by AI Agents

    Gary Marcus, citing an Axios report, said that US banks are tightening system access permissions due to AI agent attacks, and that bank executives are alarmed by these findings. He also mentioned that the attack on France's refrigeration system on October 11 may have been facilitated by agents, as well as the continuously increasing cybersecurity attacks in Japan. He believes that attackers do not need the most advanced frontier models to cause damage, and therefore regulation should not focus only on frontier models and future risks.

    Gary Marcus, citing an Axios report, said that US banks are tightening system access permissions due to AI agent attacks, and that bank executives are alarmed by these findings. He also mentioned that the attack on France's refrigeration system on October 11 may have been facilitated by agents, as well as the continuously increasing cybersecurity attacks in Japan. He believes that attackers do not need the most advanced frontier models to cause damage, and therefore regulation should not focus o

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  9. Tencent Cloud Developer Community

    How can a transportation management TMS system use Mapbox to implement AI route planning visualization: multi-plan comparison and drag adjustment

    TMS systems' AI route planning visualization uses the Mapbox Directions API's alternatives=true to obtain up to 2 alternative routes and compares them side by side with differentiated styles. Dragging waypoints triggers recalculation only on dragend, combined with 500ms debouncing to avoid consecutive requests; after changes, incremental metrics and the warnings field are used to indicate restricted roads and time window conflicts. The Mapbox Directions API supports at most 25 coordinate points per request, and under the driving-traffic profile at most 3 waypoints; for larger scales, the Optimization API or a self-hosted OSRM service must be used instead.

    TMS systems' AI route planning visualization uses the Mapbox Directions API's alternatives=true to obtain up to 2 alternative routes and compares them side by side with differentiated styles. Dragging waypoints triggers recalculation only on dragend, combined with 500ms debouncing to avoid consecutive requests; after changes, incremental metrics and the warnings field are used to indicate restricted roads and time window conflicts. The Mapbox Directions API supports at most 25 coordinate points

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  10. Wired AI

    Hugging Face Releases Open-Source DNA Model Carbon-X, Runs Locally on a Laptop

    Hugging Face on Thursday released the open-source DNA understanding model Carbon-X, which can run locally on a laptop, letting users ask in natural language how DNA changes affect gene activity and health. The model was developed in collaboration with researchers at Zhongguancun Academy and the University of Naples Federico II; it extends the vocabulary of an existing language model to read DNA in six-letter units and was further trained on 300 billion tokens of DNA sequences, English text, and samples pairing DNA with biological descriptions. The model has 14B parameters and can process sequences of about 50,000 base pairs at a time; it cannot upload a complete human genome. The developers also note that the prediction accuracy has not yet been validated through wet-lab experiments.

    Hugging Face on Thursday released the open-source DNA understanding model Carbon-X, which can run locally on a laptop, letting users ask in natural language how DNA changes affect gene activity and health. The model was developed in collaboration with researchers at Zhongguancun Academy and the University of Naples Federico II; it extends the vocabulary of an existing language model to read DNA in six-letter units and was further trained on 300 billion tokens of DNA sequences, English text, and

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  11. Jiwei.com

    MEMSIC Named to the "2025 China Top 10 MEMS Enterprises" for the Eighth Consecutive Year

    MEMSIC has been selected for the eighth consecutive year as one of the "2025 China Top 10 MEMS Enterprises" at the 7th MEMS Manufacturing Conference, China MEMS 2026. Founded in 1999, the company has shipped nearly 4.6 billion chips cumulatively, holds more than 260 core patents, and serves over 300 end customers worldwide; its accelerometers and AMR magnetic sensors hold market shares of more than 30% and 40%, respectively, in Android devices.

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  12. China.com Technology

    Lenovo New Vision and GigaAI Reach Strategic Cooperation to Build an Embodied Intelligence Industry Loop with World Models

    Lenovo New Vision and GigaAI have signed a strategic cooperation agreement to connect the "data—model—hardware—scenario" industry loop with world models at its core, jointly building a benchmark for domestic embodied intelligence collaborative innovation. The two parties will cooperate in three major directions: computing power business synergy, embodied data development, and industry-education integration, providing integrated services for computing power leasing, computing power construction, and embodied intelligence data collection. GigaAI builds a closed-loop ecosystem with its world model platforms GigaWorld/DriveDreamer/YISU, the general-purpose embodied brain GigaBrain, and the native body Maker.

    Lenovo New Vision and GigaAI have signed a strategic cooperation agreement to connect the "data—model—hardware—scenario" industry loop with world models at its core, jointly building a benchmark for domestic embodied intelligence collaborative innovation. The two parties will cooperate in three major directions: computing power business synergy, embodied data development, and industry-education integration, providing integrated services for computing power leasing, computing power construction,

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Wednesday

  1. heise online

    Does the Data Architecture for AI Agents Need a Federated Knowledge Layer?

    A heise article argues that as multi-agent systems and generative AI make machines into data consumers, data architectures such as Data Mesh—originally designed for human analysts—are facing challenges and require a federated Knowledge Layer to connect local context and business semantics with a global enterprise model. The article was written by Saskia Untiet-Kepp of Sopra Steria, and the full content is available only to heise-Plus subscribers.

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