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Announcement reads
Announcement posts on Yomu, summarised newest first.
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Announcement posts
More context, more confidence: The new CX Score explained
CX Score was created to give support teams a broader view of customer experience than survey-based measures such as CSAT and NPS, which capture only a subset of interactions. Its latest iteration evaluates more of each conversation, combining answer quality for Fin and human teammates with customer effort, strong emotion, product or service feedback, and policy feedback. The update also expands scoring to shorter and more transactional threads, adds reasons behind individual ratings, and enriches summaries with the issue, handling, and drivers of the score. The stated goal is to help teams identify operational problems, route conversations for review or follow-up, and move from measurement toward continuous improvement. The new version is rolling out gradually to all customers and is scheduled to be in workspaces by December 3rd.
Unwrap Innovation: How Sellers and Buyers Use AI to Brighten the Holidays
eBay describes how its AI tools aim to reduce holiday-season friction for sellers and improve discovery and trust for buyers. More than 10M unique sellers have used its AI features, while sellers create more than half a million new listings daily using Generative AI. The simplified listing experience can start with an image, background enhancement adds festive professional-grade backgrounds, and AI Assistant for messaging drafts replies to common questions about item specifics or shipping. For shoppers, an AI shopping assistant pilot, LLM-powered fashion recommendations, and access to eBay’s inventory through third-party agents including OpenAI partnerships support personalized discovery. Trust features include Authenticity Guarantee expert verification for handbags, jewelry, and trading cards, plus Certilogo’s digital IDs and authentication for apparel, while eBay says these measures support safer participation in the circular economy.
OVHcloud on Hugging Face Inference Providers 🔥
OVHcloud is now integrated as a supported Inference Provider on the Hugging Face Hub, expanding serverless inference options across model pages and client SDKs. The integration enables access to open-weight models, including gpt-oss, Qwen3, DeepSeek R1, and Llama, using European infrastructure with pay-per-token pricing starting at €0.04 per million tokens. Developers can connect via Python and JavaScript SDKs using either direct custom API keys or automatic routing through Hugging Face tokens. The service supports structured outputs, function calling, multimodal workflows, and embedding models while providing sub-200ms first-token response times. Calls routed through Hugging Face pass through standard provider pricing without markups, and PRO tier subscribers receive monthly inference credits.
Unlocking Peak Performance on Qualcomm NPU with LiteRT
Google introduces the LiteRT Qualcomm AI Engine Direct (QNN) Accelerator, developed with Qualcomm to replace the previous TFLite QNN delegate and simplify NPU deployment across supported Qualcomm SoCs. It integrates vendor compilers and runtimes behind a unified workflow, supports ahead-of-time and on-device compilation, and can fall back to GPU or CPU when needed. Across 72 canonical vision, audio, and NLP models, the accelerator supports 90 LiteRT ops, enables full NPU delegation for 64, and reports up to 100x CPU and 10x GPU speedups. On Snapdragon 8 Elite Gen 5, FastVLM-0.5B uses int8 weights, int16 activations, and specialized transformer kernels to reach 0.12 second time-to-first-token, over 11,000 prefill tokens per second, and over 100 decode tokens per second.
20x Faster TRL Fine-tuning with RapidFire AI
Hugging Face TRL now officially integrates with RapidFire AI to accelerate LLM fine-tuning and post-training experimentation through concurrent configuration evaluation. Instead of executing training configurations sequentially, the platform shards datasets into discrete chunks and cycles multiple model configurations across GPUs at chunk boundaries. The runtime handles automatic checkpointing via a shared-memory-based adapter and model spilling mechanism to maintain consistent training state. Experimenters can monitor live metrics on an MLflow-based dashboard and use Interactive Control Ops to stop underperforming runs or clone and warm-start promising configurations mid-flight. Benchmark results on NVIDIA A100 GPUs demonstrate experimentation speedups ranging from 15x to 20x over sequential runs when training TinyLlama-1.1B and Llama-3.2-1B models.
Introducing AnyLanguageModel: One API for Local and Remote LLMs on Apple Platforms
Apple developers frequently face integration friction when trying to support a mix of local and cloud language models across disparate APIs. To resolve this fragmentation, AnyLanguageModel introduces a unified Swift package that acts as a drop-in replacement for Apple's Foundation Models framework. The package standardizes interactions across local backends such as Core ML, MLX, and llama.cpp alongside cloud providers like Anthropic and OpenAI. To avoid dependency bloat from multi-backend support, the library employs Swift 6.1 package traits so projects only import the specific runtime engines they require. Furthermore, the library extends beyond current Foundation Models limitations by adding prompt image support for vision-language models.
Intercom is now a Shopify Plus Technology Partner
Intercom announces that it is now a certified Shopify Plus Partner on the Technology Track. The program recognizes technology providers whose product quality, service, performance, privacy, and support meet advanced requirements for Shopify Plus merchants. Intercom says its integration is vetted and optimized, and describes recent additions including Data Connector templates for Fin, multi-store support, inbox order actions, EU workspace support, and updated data mapping and custom fields. The announcement also lists planned expanded Fin Tasks, Model Context Protocol support, and smarter product search powered by Shopify data, positioning these capabilities as ways to resolve ecommerce support requests faster and personalize conversations at scale as merchants prepare for peak season and rising customer expectations.
Join the AMD Open Robotics Hackathon
AMD, Hugging Face, and Data Monsters announced the AMD Open Robotics Hackathon, an in-person competition scheduled for Tokyo and Paris in December 2025. Participating teams of up to four adults will compete over three days across two core missions. The first mission covers an instructor-led session on configuring the LeRobot development environment using AMD AI solutions. During the second mission, teams spend two days developing a freestyle project to address a real-world problem using LeRobot. Participants receive access to SO-101 robotics kits, AMD Ryzen AI laptops, and AMD Instinct MI300X GPUs via AMD Developer Cloud, with prizes awarded to the top seven teams in each city based on creativity, difficulty, ease-of-use, and practicality.
Past, Present, and Future
Cursor has announced a $2.3 billion Series D financing at a $29.3 billion post-money valuation, nearly two years after describing a vision for an AI-assisted code editor that could make programming more helpful, answer codebase questions instantly, and reduce the visibility of source code. The company says the early stages of that vision are taking shape while substantial work remains to realize Cursor’s potential. It reports a team of more than 300 engineers, researchers, designers, and operators, over $1 billion in annualized revenue, millions of developers and major engineering organizations as customers, and in-house models generating more code than almost any other LLMs in the world. Existing investors Accel, Thrive, and Andreessen Horowitz participated alongside new partners Coatue, NVIDIA, and Google, while the funding will support further research and Cursor’s next magical moments.
Building for an Open Future - our new partnership with Google Cloud
Hugging Face and Google Cloud announced an expanded strategic partnership designed to streamline the deployment and management of open models on Google Cloud infrastructure. Prompted by a tenfold increase in Hugging Face usage on Google Cloud over three years, the collaboration introduces a joint CDN Gateway using Hugging Face Xet technology to cache models and datasets directly on Google Cloud. This caching mechanism aims to shorten download times, strengthen model supply chain resilience, and accelerate time-to-first-token across Vertex AI, Google Kubernetes Engine, Cloud Run, and Compute Engine virtual machines. Hugging Face plans to integrate native library support for Google Cloud TPUs, lower instance prices on Inference Endpoints, and enhance Hub security scanning via VirusTotal, Google Threat Intelligence, and Mandiant.
Heroku Support for .NET 10 LTS: What Developers Need to Know
Heroku now supports building and running .NET 10 applications, including ASP.NET Core 10, C# 14, and F# 10, as the new three-year Long Term Support release becomes available. Its .NET buildpack detects single-file C# applications, installs the latest SDK, builds and publishes them, and configures web apps without project or solution files; it also supports both .sln and .slnx formats. Heroku CI continues to run dotnet test by default, with the .NET 10 SDK integrating the Microsoft Testing Platform into that command. .NET 8 and .NET 9 remain supported with updates but reach End of Support on November 10, 2026, while apps targeting net10.0 RC will use stable .NET 10 on their next push and can pin SDK versions through global.json.
MongoDB Announces Leadership Transition
Dev Ittycheria announced his decision to retire as MongoDB President and Chief Executive Officer after eleven years of leading the company. Chirantan Desai will become the new Chief Executive Officer effective November 10, 2025. The transition follows a succession planning process initiated earlier this year when Ittycheria concluded he could not commit to an additional five-year term requested by the Board. Desai previously scaled ServiceNow organically from over $1 billion to more than $10 billion in revenue and served as President of Product and Engineering at Cloudflare. Ittycheria will remain on MongoDB's Board to support Desai through the transition into the company's next phase of growth.
Introducing Cursor for Enterprise
Cursor is introducing enterprise features intended to make its coding agents more capable, transparent, and secure for organizations already using the product. Hooks expose the agent loop to custom scripts that can log actions and tool calls, enforce compliance or command allowlists, scrub sensitive material, connect external systems, and trigger automations; they can be distributed through MDM or Cursor’s cloud option. Team Rules provide shared context and can recommend or require standards such as API schemas, conventions, and workflows, while upgraded analytics report activity, adoption, AI lines of code, directory-group filters, and exportable data with updates every two minutes. The release also adds an Audit Log covering 19 event types and Sandbox Mode, which restricts network and file access by default, with administrators controlling availability and team-wide Git and network access.
Heroku Connect: Faster, More Reliable Data Sync with Salesforce CDC
Heroku Connect customers needing current Salesforce data for applications such as custom quoting have faced stale records because legacy synchronization could lag, with Opportunity Line Items among unsupported objects for Accelerated Polling. Heroku is rolling out support for Salesforce Change Data Capture (CDC), allowing Accelerated Polling to listen for changes instead of relying only on the Salesforce Streaming API. That change adds more than 170 Salesforce standard objects to Accelerated Polling, including Opportunity Line Items, Pricebook2, Asset, and OpportunityLineItem, so critical data can synchronize more quickly. To enable it, a Salesforce administrator turns on CDC for selected objects, after which the corresponding Heroku Connect mappings expose the “Uses Accelerated Polling” option.
Headlines from Pioneer 2025: Fin 3, the vision for a unified Customer Agent, and what’s next for customer experience
Pioneer 2025 presented Intercom’s latest customer-service AI plans, centered on Fin 3 and a longer-term vision for a single Customer Agent covering the entire customer experience. Fin 3 adds Procedures for complex, policy-controlled resolutions, Simulations for pre-release testing, Slack and Discord deployment, improved Voice, and Insights features such as CX Score Reasons, Topic Trends, and AI-powered Suggestions. The proposed Customer Agent would combine specialized roles, user-defined goals, persistent memory, business knowledge, and interoperability across tools, systems, and channels. Customer examples described phased rollouts, rapid feedback, broad scaling, and support-team involvement, while Anthropic reported two specialists enabling nearly 50 full-time employees’ worth of coverage in its volume. The event framed AI as a force for converging products, roles, and organizational structures, with the Customer Agent future described as arriving quickly.
What’s new with Fin 3: The best AI Agent for complex queries across every channel
Fin 3 is presented as an AI Agent for customer service focused on increasing automation rate by handling complex queries end-to-end across more channels. Procedures combine natural-language instructions with data connectors, conditional steps, code snippets, and approval checkpoints, allowing teams to encode standard operating procedures with varying levels of control. Simulations provide multi-turn testing for different customer segments and scenarios, while Fin Voice, Slack, and Discord expand deployment options. Insights upgrades add CX Score Reasons, Topic Trends, and AI-powered Suggestions that surface quality changes, topic shifts, and content improvements. The announcement says Fin 3’s broader goal is to increase the share of overall support workload it handles, beyond a resolution-rate metric that had reached 66% on average across more than 6,000 customers.
Preparing for the Customer Agent future
At Pioneer 2025, Eoghan McCabe presented a plan for Fin to become a unified Customer Agent spanning the entire customer experience, from first contact through purchase, support, success, and upsell. The proposal responds to the risk that separate AI Agents for sales, marketing, success, and service will use conflicting priorities, disconnected information, and inconsistent interactions. Fin is intended to evolve from a task-based system into an agentic system with fluid roles, user-defined goals, persistent customer memory, comprehensive business knowledge, and interoperability across tools, systems, and channels. The post argues that customer service leaders are positioned to guide this wider AI rollout because they have experience, data, and operational insight from early AI adoption. Early activity includes WHOOP using Fin for sales conversations, where it is resolving 84%, while new capabilities are expected to roll out over the coming months.
Cloud Agents
Cursor’s Cloud Agents let developers run multiple agents remotely without keeping a laptop connected to the internet. Agents can be launched and managed from the Cursor editor, cursor.com/agents, Slack, Linear, and GitHub, supporting background bug fixes, small todos, and larger feature work. For difficult bugs, the team commonly has multiple models attempt the same problem and selects the best result; for complex features, a locally developed plan can be sent to a cloud agent for implementation, allowing work to continue on another task. Cursor also revamped its GPT-5 Codex agent harness for longer time horizons in the cloud, while plan mode supports sending implementation plans remotely. The workflow is available today in Cursor editor and Cursor Web, as well as the listed integrations.
Building our next R&D hub in Berlin
Intercom will open its next R&D hub in Berlin on January 19, 2026, to support investment in its AI customer service platform and Fin, its AI Agent. It has already welcomed its first Berlin hires and plans to hire 100 people over the following year across engineering, AI, data science, product, and design. Berlin was chosen for its technical talent, creative culture, AI-focused startups and research labs, and proximity to the existing R&D hubs in Dublin and London. Fin is described as the primary contributor to this growth, with more than 7,000 businesses having transformed customer service with it and Fin months away from passing $100 million in ARR. The new office at Zimmerstraße 78 will host an R&D recruitment event on February 26, 2026, while an AI builders day is planned for February.
Composer: Building a fast frontier model with RL
Composer is a mixture-of-experts agent model for software engineering that targets interactive use, with reported frontier coding results and generation speed four times faster than similar models on the authors’ benchmarks. It is trained with reinforcement learning on real-world software engineering challenges in large codebases, using production search and editing tools, terminal commands, and codebase-wide semantic search. Training responses may be code edits, plans, or informative answers, while the process rewards efficient tool use, parallelism, minimal unnecessary responses, and evidence-based claims. Evaluation uses Cursor Bench, built from real agent requests and curated optimal solutions, measuring correctness alongside adherence to existing abstractions and software engineering practices. The training stack combines asynchronous reinforcement learning with PyTorch and Ray, MXFP8 MoE kernels, expert parallelism, hybrid sharded data parallelism, and sandboxed cloud environments scaled to hundreds of thousands concurrently.
Top topics
- Architecture830
- Performance812
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- AI Agents542
- AI454
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