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Announcement reads
Announcement posts on Yomu, summarised newest first.
- 1,477 posts
- 20 companies
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Announcement posts
TCS and Anthropic bring Claude to regulated industries
TCS and Anthropic are partnering to bring Claude to regulated industries, with TCS providing access to 50,000 employees across 56 countries and developing client offerings. As the partnership’s “customer zero,” TCS will use Claude across engineering, finance, legal, marketing, and sales, then apply those lessons through a dedicated practice of consultants, engineers, and industry specialists. The practice will package and operate industry-specific systems, including claims processing for insurers and lending advisory for banks, while TCS teams contribute reusable Claude Code skills and plugins focused initially on claims adjudication and lending advisory. Other announced work includes Diligenta using Claude for more than 22 million policyholders and TCS iON delivering training and certification after conducting more than 75 million annual assessments.
Anthropic opens Seoul office
Anthropic has opened its Seoul office and announced partnerships with Korean enterprises, startups, researchers, and the Ministry of Science and ICT. Through an MOU, the company will collaborate on AI safety and cybersecurity, including Korean-language model-safety evaluation with the Korea AI Safety Institute and information exchange on AI-enabled cyber threats. Korean deployments described include Claude Code across NAVER’s engineering organization, Claude at LG, Hanwha, Samsung SDS, and Nexon, plus Claude-powered products and nonprofit use. Anthropic will provide Claude access to up to 60 NAIRL-affiliated researchers, launch Claude for Startups in Korea, and support developer events and a hackathon. The office is led by KiYoung Choi and is hiring across a range of roles.
ClickHouse achieves AWS Cloud Operations Competency
ClickHouse has achieved the AWS Cloud Operations Competency in the Monitoring and Observability category, recognizing validated expertise in operating reliable AWS systems with logs, metrics, and traces. The post describes observability as a high-volume, high-cardinality, high-concurrency workload where legacy systems may require sampling, field reduction, or short retention. ClickHouse Cloud uses columnar storage, compression, parallel queries, compute-compute separation, and ClickPipes integrations with Amazon Kinesis, Amazon MSK, and Amazon S3 to support full-fidelity telemetry. Customer examples include Modal’s 1 to 2 million events per minute, Exabeam’s 1.2 million events per second per region, and Qonto’s reduction of 231 TB to 376 GB. The company also describes MCP servers, AI Notebooks, and managed ClickStack as investments for collaborative incident investigation.
Streamlining Resource Binding with End-to-End Support for Vulkan Descriptor Heaps
Vulkan introduces the VK_EXT_descriptor_heap extension to refactor GPU resource binding, replacing set-based layouts and pool allocations with application-managed descriptor memory heaps. This approach aligns Vulkan closer to Direct3D 12 and benefits workloads like dynamic texture indexing and complex ray tracing shaders. Developers manage memory directly, binding a single resource heap and a separate sampler heap globally to avoid high rebinding overhead. Shaders can access descriptors either through mapping structures using constant offsets or push constants, or directly via untyped pointers enabled by VK_KHR_shader_untyped_pointers. Support is integrated into NVIDIA drivers 610, Vulkan Headers 1.4.340, and Nsight Graphics 2026.2 for frame capture and inspection.
Announcing Silk: a silky smooth fiber runtime for ClickHouse
Silk is a C++ stackful-fiber library and scheduler created for ClickHouse’s highly concurrent, I/O-bound components, including object-storage I/O, distributed cache lookups, replica coordination, and HTTP fan-out. Its design combines one pinned OS scheduler thread per CPU, NUMA-aware work stealing, io_uring for asynchronous I/O and timers, and zero heap allocation in the steady-state hot path; fiber stacks are mmap’d from per-fiber pools with guard pages, while runtime containers are intrusive. The post reports benchmarks including roughly 3.6-nanosecond fiber yields with cross-CPU stealing, 5.9 million file IOPS in a working configuration, and about fifteen times boost::asio’s throughput at one connection. At 10,000 concurrent S3-style requests, internal measurements showed a roughly 65% improvement in 99.9th-percentile latency versus an equivalent thread-pool executor, with identical median throughput; distributed cache is the first intended ClickHouse integration.
ClickHouse is now a native connection in Notion Custom Agents
ClickHouse is now a native, preconfigured connection in Notion Custom Agents, allowing agents to access ClickHouse Cloud data without leaving Notion. After an OAuth connection, agents can explore schemas, translate plain-language questions into ClickHouse SQL, run read-only queries, and return results in the workspace. The connection exposes 14 read-only tools covering databases and tables, SELECT queries against ClickHouse and Managed Postgres, and organization, service, ClickPipes, backup, and cost information; users can set each tool to run automatically or require approval. Custom Agents can run on a schedule, including a daily observability report that queries error rates, p99 latency, and request volume from a Managed ClickStack service. The connector is in beta and requires a ClickHouse Cloud service with Remote MCP enabled plus a Notion Business or Enterprise workspace.
10 Years of MongoDB Atlas: Built for What’s Next
Launched in 2016, MongoDB Atlas was designed to bring MongoDB's developer experience to the cloud while eliminating operational overhead for production environments. Over ten years, Atlas expanded beyond a managed database into a multi-cloud data platform that supports multi-document ACID transactions, Queryable Encryption, native search, and stream processing. The platform introduced Atlas Vector Search in 2023 and acquired Voyage AI in 2025 to embed advanced embedding and reranking models natively. These integrated capabilities address the requirements of retrieval-augmented generation and autonomous AI agents without relying on disparate vector stores or sync pipelines. Atlas now serves more than three trillion queries daily across over 125 AWS, Google Cloud, and Microsoft Azure regions for nearly 70,000 customers.
How Notion used the Cursor SDK to embed coding agents
Notion integrated Cursor coding agents into its product so users can delegate work by tagging Cursor in a document, mentioning it in a thread, or assigning a database issue. Built with the Cursor SDK in a couple of weeks, the integration lets agents plan, build, test, verify work, and open pull requests while Notion focuses on product and user experience rather than agent infrastructure. Notion placed Cursor behind a provider-agnostic harness: a Notion thread maps to an agent, each message starts a run, and the first run can specify the prompt, repository, model, MCP servers, and automatic PR creation. Follow-up runs stream over SSE, support resumption after dropped connections, and use remote MCP to let Cursor read and write workspace state in real time; templates, custom instructions, selected tools, skills, subagents, and triggers provide further customization.
Databricks positioned highest in execution and furthest in vision for the second consecutive year in Gartner Magic Quadrant
Databricks says Gartner positioned it highest for execution and furthest for vision in the Magic Quadrant for the second consecutive year. The post connects this recognition to a category reclassified from “Data Science and Machine Learning” to “AI Platforms for Data Science and Machine Learning,” and argues that agentic applications require enterprise data, governance, observability, and business context. Databricks presents a unified approach combining the lakehouse, Lakebase, Agent Bricks, Unity Catalog, and Unity AI Gateway to build, monitor, and govern agents, models, data, apps, and tools. Reported examples include YipitData’s 20x increase in company coverage with 92–95% tagging accuracy, Block’s unified AI and data estate, and Novo Nordisk’s attribution of more than $157 million in net new value to governed clinical-trial optimization.
Long Story Short: I Found My Place Between Code and Community
Aasawari Sahasrabuddhe describes moving from backend software development into developer relations after finding that coding alone felt incomplete. Her DevRel work combines community engineering, content creation, strategy, workshop building, technical writing, hands-on workshops, and public speaking, while retaining a technical base in Java, Quarkus, and Spring Boot. She also discusses deeper interests in containers, Kubernetes, Docker, CI/CD, and GitOps, along with recognition as a MongoDB Champion for community contributions. The announcement introduces her move to Okta, where she wants to examine the intersection of identity, security, and AI, including how identity supports trust, access, and governance for AI systems. She frames this role as a way to stay close to community while continuing to work with code and content.
Announcing the Managed ClickStack MCP Server
Managed ClickStack in ClickHouse Cloud now includes the ClickStack MCP server, extending its observability investigation capabilities to external agents and AI workflows. Unlike the generic ClickHouse MCP server’s SQL-oriented interface, it offers semantic tools for log patterns, outlier correlation, slow traces, and repeatable investigations across logs, metrics, and traces. For event patterns, the server samples matching events, processes them with Drain3 in the MCP layer, and extrapolates and ranks counts, reducing output cardinality and making query overhead fixed rather than linear in the full dataset. Internal benchmarks report 25% fewer tool calls, 2.5x greater consistency, and an almost 20% increase in evaluation scores versus the standard ClickHouse MCP. Managed deployments also support full-fidelity telemetry, dedicated compute for agent workloads, and orchestration such as persisted dashboards, while native SQL remains available for unusual or deeper questions.
Introducing a better way to process Stripe's thin events
Stripe introduces event notification handlers to simplify processing thin events, unversioned JSON payloads that remain identical across API versions. The problem is that current integrations require developers to validate and route notifications, manage Stripe-Context for connected accounts, and manually maintain event-type strings, while API-version or SDK upgrades can cause runtime errors. Handlers move casting, routing, validation, and conversions into the SDK: typed callbacks are registered with handler.on, and callbacks receive a parsed notification plus a StripeClient already bound to the event context. The handler also provides a fallback for unhandled events and supports normal function-level testing, while the webhook endpoint only needs to pass the request body and signature to handler.handle. The pattern is supported in seven server-side SDKs, with feedback sought before general availability and possible future improvements to validation and framework integrations.
Introducing Cash Trips: A New Way for Riders to Pay and for You to Earn
Uber is introducing cash trips in select cities for riders who lack convenient access to bank accounts or cards, or prefer cash, while creating another earning opportunity for drivers. Only verified riders can use the option, and drivers see “Verified” and “Cash” badges plus the rider’s rating before accepting. At trip end, drivers tap “Collect Payment,” enter the exact cash received, and see that amount recorded as a negative payout because it was collected directly; negative balances are offset by future digital earnings. Drivers are automatically opted in at launch but can opt out in Preferences, while Uber says it will handle underpayments, provide change to riders through Uber Cash, and prohibit cash payment on trips not marked as cash.
The 2026 Developer Survey is now open (for human developers only)!
The 2026 Developer Survey is open to gather data on software builders' tools, working lives, and emerging practices. Marking fifteen years since its initial 2011 release, the annual survey focuses heavily on the role of artificial intelligence and autonomous agents across the software development lifecycle. Past survey results indicated that while developer adoption of AI and agents doubled, user trust declined alongside escalating concerns regarding generated code quality. In addition to modern AI trends and financial return considerations, the questionnaire maintains traditional inquiries regarding day-to-day technologies and developer workflows. The survey is hosted on the Qualtrics platform, which requires users to pause third-party ad blockers and adheres to regional access restrictions across multiple countries.
What's New in pg_clickhouse v0.3.2: Postgres 19, TLS, Regex, and Memory
pg_clickhouse v0.3.2 updates the Postgres interface for querying ClickHouse, with changes centered on PostgreSQL 19 Beta1 support, TLS configuration, regular-expression pushdown, and memory consumption. The release adds CREATE SERVER options for forcing TLS or plaintext, selecting a minimum TLS version, and enabling ClickHouse native-protocol compression. Revised pushdown logic maps Postgres regular-expression flags to ClickHouse behavior, while regexp_match() can now be pushed down when its pattern has no capturing groups. Two memory issues were fixed: one involving unbuffered HTTP-driver queries and another involving repeated foreign scans such as parameterized inner scans in nested-loop joins. The minor update requires no reload, restart, or ALTER EXTENSION UPDATE, and also fixes empty-array ANY() errors on ClickHouse versions before 25.
Toward More Controllable AI Video Editing: An Early Research Exploration at Netflix
Generative video editing tools often regenerate entire video clips, which inadvertently modifies untouched scene details or violates physical continuity during object deletion. To provide artists with precise control, two research prototypes were developed: Vera and VOID. Vera uses a layered video diffusion framework with a Mixture-of-Transformers architecture to jointly generate separate edit and alpha matte layers, compositing them with original footage while leaving unchanged pixels untouched. VOID addresses object deletion by conditioning on interaction-aware quadmasks and using a second-pass appearance refiner to reconstruct scenes with plausible physical continuity. In a user study evaluated across 75 real-world scenarios, reviewers selected VOID 64.8% of the time over six baselines.
Introducing Modal Auto Endpoints: Optimized inference you actually own
Modal Auto Endpoints is a self-serve service for production-grade LLM inference that gives teams ownership of the entire serving stack, not just an API. Unlike proprietary providers, it exposes the inference code, engine flags, and GPU selection, and provides detailed metrics like speculative decoding acceptance length and per-replica token latency quantiles in a dashboard. Built on Modal’s infrastructure, it uses autoscaling to handle traffic spikes by spinning up additional replicas automatically, global GPU capacity without capacity management, and Modal Servers for ultra-low-latency routing with only 5ms overhead. For each supported model, it offers a pre-configured deployment using speculative decoding with the DFlash block-diffusion drafter from Z Lab, and teams can benchmark latency and throughput tradeoffs with a click after deployment. The platform is designed with a declarative interface based on workloads and SLOs, with future automation levels including autoinference, autospec, autodistill, and autoresearch for continuous improvement of inference performance.
What's new in ClickStack - May 2026
ClickStack’s May and early-June release focused on making observability dashboards more useful during investigations and expanding access to related workflows. Dashboard table actions can open searches against selected sources with templated WHERE clauses or link to other dashboards, while scoped filters prevent source-specific conditions from affecting unrelated tiles. Number visualizations gained fixed or threshold-based colors and automatic text scaling, and the service map added latency percentiles, throughput metrics, server-side filtering, and focus mode. The release also includes a Browser RUM dashboard template, experimental PromQL support through the ClickHouse TimeSeries Engine, expanded MCP tools, AI Notebooks beta for Managed ClickStack, and ClickStack Cloud in private preview.
Uber Advertising: Introducing Uber Marketing Manager, Creative Studio Expansion, and New Strategic Partnerships
Uber Advertising is introducing Uber Marketing Manager as a self-serve platform intended to unify advertising across Uber and Uber Eats, building on Ads Manager for restaurants. It also outlines Creative Studio expansion, new APIs, and a Mastercard Commerce Media partnership designed to connect campaign activation, offers, measurement, and real-world experiences across consumer journeys. Examples include Krispy Kreme’s Destination Offers campaign in Mexico, Molson Coors’s multi-format soccer campaign, and adidas’s pan-European Journey Takeover. Creative Studio will expand to Australia and Brazil in 2026, followed by continued expansion across LATAM, EMEA, and APAC throughout 2027. Uber says its connected approach is intended to help advertisers engage consumers across Uber, Uber Eats, and beyond, while a third-party validated Affinity Solutions study found a 27% incremental lift in sales across all channels and a 5% lift in brick-and-mortar sales for Sponsored Listings on Uber Eats.
CCCL Runtime: A Modern C++ Runtime for CUDA
NVIDIA CCCL runtime introduces modern C++ abstractions for fundamental CUDA programming concepts starting in CUDA Toolkit 13.2 and CCCL 3.2. Designed as an alternative to the traditional CUDA runtime API, the library eliminates implicit global state by requiring explicit dependencies, such as binding streams directly to specific device references. The API enforces strong typing through owning types and non-owning reference types, omits default stream usage to ensure all streams remain non-blocking, and handles errors via standard C++ exceptions. In addition, CCCL runtime simplifies kernel launches through kernel functors that enable automatic template argument deduction and automatically transforms owning buffer arguments into device spans.
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