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Announcement reads
Announcement posts on Yomu, summarised newest first.
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Announcement posts
tokenizers v1: encode, decode and scaling, measured
The tokenizers library is being reworked for version 1 with a heavy focus on performance, as tokenization can become a bottleneck that starves models of data when workloads scale. The work draws on ideas from other open-source tokenizers like gigatoken, tiktoken, and kitoken. Key optimizations include using SIMD instructions for UTF-8 text, ensuring merges never cross pre-token boundaries, and reusing scratch buffers to avoid allocations. The release candidate is implemented in the Rust pre-release on crates.io, with the crate split into tk-encode, tk-serialize, tk-convert, and tk-train. Batched model calls and faster decoding with parallel batch processing are also part of the improvements.
Your sandbox can now serve requests
Sandboxes have traditionally been outbound-only machines, unable to receive inbound connections because they sit behind NAT with no public IP or open ports. BoxCompute now enables sandboxes to serve requests by using Tailcat, an open-source library from Tailscale that performs NAT traversal. Tailcat establishes a direct peer-to-peer WireGuard-encrypted path between the client and sandbox, using a DERP relay only for the initial handshake. This approach avoids the latency and bandwidth bottlenecks of relay-based tools like ngrok or Cloudflare Tunnel, and keeps the relay out of the data path. The feature is rolling out as an early preview with scoped, short-lived grants for selected TCP ports.
Partnering with Accenture on embedded evaluation
Anthropic is partnering with Accenture’s specialist AI business, Faculty, on independent evaluation of frontier AI, advancing a commitment to embed evaluators within Anthropic. The work will cover model evaluation and red-teaming, alignment assessments, and testing safeguards, informed by Accenture’s experience deploying AI across industries. Anthropic and Accenture each expect to invest at least $1 billion in building capacity over five years, although operating details, access standards, reporting practices, and funding models remain unsettled. Embedded evaluators would work inside AI companies with employee-comparable access to observe training, follow development and deployment decisions, speak with staff, verify safety commitments, identify blind spots, and report incidents; Anthropic says its partnership is non-exclusive and that model safety remains its responsibility.
Making Local AI Smarter and Faster
Junie Local’s update introduces Qwen3.8-3.6-27B-blend, a merged model that balances speed and capability for local coding agents. The blend, created by merging Qwen3.6 and Qwen3.8 weights in equal proportions, completed 37 tasks in a 100-task internal benchmark, compared to 34 for Qwen3.6 and 39 for Qwen3.8, while generating 71% fewer output tokens than Qwen3.8. The runtime uses multi-token prediction (MTP), with a two-token proposal on M5 MacBook Pro making decoding 60% faster. A four-bit MTP head was kept over an eight-bit one due to similar acceptance rates and memory savings. The update also brings experimental NVIDIA RTX support on Windows for machines with at least 24 GB of VRAM.
Ktor 3.6.0 Is Now Available!
Ktor 3.6.0 introduces experimental typed authentication with full type safety, including role-based access and anonymous users, plus a dedicated OpenID Connect plugin that supports sessions and auto-refreshing tokens, and experimental HTTP/3 support for the Netty engine via QUIC. Request-parameter conversion now supports Kotlin’s Uuid, Byte, and unsigned numeric types, while receive() accepts nullable types, deprecating receiveNullable(), and more flexible routing syntax. The ContentNegotiation plugin gains a ContentTypeMergeStrategy.SkipIfPresent to preserve explicit Accept headers. Kotlin Multiplatform projects benefit from the ktor-client-engine-defaults artifact and file-based HttpCache storage using kotlinx-io Path, simplifying cross-platform configuration. Additional improvements include respondHtmlPartial for partial HTML output, asynchronous DNS resolution for the CIO engine, and WebRTC support for JVM.
Classic Engine Feature EOL: SSR, Desktop SSO, Device Trust
Okta will end support for Self-Service Registration, Desktop Single Sign-On using Integrated Windows Authentication (IWA), and Device Trust on Classic Engine on March 5, 2027. After that deadline, the capabilities will be turned off unless organizations upgrade to Okta Identity Engine, and Okta will no longer address related bugs, security vulnerabilities, or broken flows. The migration paths are Profile Enrollment Policy for self-service registration, Agentless Desktop Single Sign-On or Okta FastPass for desktop authentication, and management attestation with Okta Verify for mobile device trust. Identity Engine adds passwordless authentication, device assurance, phishing-resistant multifactor authentication, identity verification, zero-trust capabilities, and a newer policy framework, with the upgrade included at no additional licensing cost. Organizations are advised to assess feature usage, test in non-production, and schedule production migration before the hard deadline.
Databricks recognized as a Gartner® Peer Insights™ Customers' Choice for Analytics and BI
Databricks says it was recognized as a Customers’ Choice in Gartner Peer Insights’ Voice of the Customer for Analytics and Business Intelligence Platforms, based on verified reviews from customers using platforms in production. The post reports a 4.8 out of 5 overall rating and 94% willingness to recommend, while noting that the designation reflects customer adoption and overall experience meeting or exceeding market averages. It presents Databricks AI/BI, AI/BI Dashboards, Genie Spaces, and Genie as a unified architecture combining governed live data, AI, business intelligence, and Unity Catalog controls without moving or duplicating datasets. The described use cases include conversational exploration, dashboard and visualization development, consolidating fragmented reporting, and expanding governed analytics access, with the company positioning these capabilities as a foundation for agentic analytics.
Protect Performance and Reduce Surprise Costs with Default Warehouse
Databricks SQL’s generally available Default Warehouse lets administrators choose the SQL warehouse automatically used for ad hoc experiences, addressing manual selection and fallback behavior such as “Last Selected” or alphabetical ordering. A workspace-level setting applies across SQL Editor, Catalog Explorer, AI/BI Dashboards, Alerts, and Genie Spaces, while users can override it or retain “Last Selected”; admin APIs and a Terraform resource support per-user assignment, auditing, and control. The feature supports serverless, pro, and classic SQL warehouses and respects existing governance and access controls, with the setting opt-in and new assets automatically using it. In customer results, Catalog Explorer queries sent to smaller warehouses rose from 77% to 96%, and users running ad hoc SQL across multiple warehouses fell by 15%, while future coverage is planned for MLflow, Lakeflow CLI, and DBSQL MCP.
The next era of the open lakehouse: Apache Iceberg™ v3 in Public Preview on Databricks
Databricks has placed support for Apache Iceberg v3 into Public Preview, bringing new table-format capabilities to its open lakehouse. Unity Catalog Managed Iceberg v3 tables support Row Lineage, Deletion Vectors, and the VARIANT type, while interoperability extends these features to foreign Iceberg tables. Row IDs and modification sequence numbers identify changed rows, and lightweight delete files avoid immediate Parquet rewrites, with data manipulation reported as up to 10x faster than copy-on-write. VARIANT stores evolving semi-structured payloads beside relational columns for direct SQL querying, while Unity Catalog provides cross-catalog governance and Delta-Iceberg interoperability without data duplication. Iceberg v3 is available on Databricks Runtime 18.0+ with Unity Catalog enabled; Databricks is also advancing Iceberg v4 metadata proposals.
Auth0 Agent Gateway: The Identity Control Plane for Customer-Facing AI
Auth0 Agent Gateway is announced in beta as a Customer Identity and Access Management (CIAM) control plane for governing product-native, customer-facing AI agents in multi-tenant SaaS applications. It addresses a trust model involving organizations, delegated user access, customer consent, independently owned connected accounts, and cross-tenant data boundaries, rather than workforce-only identity. Positioned between an agent and its tools, the gateway evaluates each call using agent, user, and organization context; it uses Organizations, Agents as Principals, Token Vault, token exchange, tenant logs, and administrative controls. The described capabilities include short-lived agent-only tokens, user-scoped credentials, runtime tool authorization, audit logging with optional SIEM streaming, and an agent kill switch. Auth0 is seeking product and engineering teams to join the beta.
Move and Scale Faster with FGA Permissions Index
Auth0 FGA Permissions Index is announced in Early Access as a way for B2B SaaS applications to enforce permissions while handling expanding AI-agent activity and complex relationship graphs. Customers select relations used for search and filtering, typically high-cardinality relations such as can_view, and the index precomputes the access those relations imply. It streams the resulting data into the customer’s database alongside application data, allowing indexed permission checks through SQL JOINs instead of repeated authorization API calls or runtime graph traversal. Computation moves to relationship-write time, while relations outside the index continue to be evaluated by FGA in real time. The announcement positions this design as a path to consistently low-latency filtering at enterprise scale, with permission decisions described as precomputed, traceable, and compliant.
Optimize Your Identity Flows with Auth0 Identity Conversion Suite
Auth0 Identity Conversion Suite addresses identity friction across the visitor-to-user journey, where forced account creation and complicated checkout are cited as contributors to abandonment. It combines Anonymous Sessions, which uses OAuth 2.0 access tokens to track pre-authentication activity and transfer session data into an authenticated profile, with Experiment Center, which supports controlled authentication-flow tests. Visitors can be assigned to percentage- or segment-based variants, kept in the same variant during their journey, and measured through exposure, success-rate, and time-to-auth events across supported Auth0 surfaces. The Early Access release is available to Enterprise-plan Auth0 customers and is presented as a way to improve personalization, onboarding, guest checkout, and authentication decisions without changing application APIs or code.
Building the future of security with NAB with Lakewatch
National Australia Bank (NAB) is working with Databricks as one of five design partners for Lakewatch, an Open Security Lakehouse intended for modern security operations. NAB, part of Australia’s critical infrastructure, ingests more than 30TB of security data daily while confronting AI-enabled threats, expanding digital services, and growing third-party integrations. The partnership brings NAB’s threat-informed cyber-defense experience to a platform designed to unify signals across environments, apply advanced analytics and AI-driven workflows, generate higher-confidence insights, and automate response actions. Lakewatch is presented as an open, composable, AI-native foundation built natively on the Lakehouse for organizations facing constantly evolving threats, supporting enterprise-wide correlation, proactive threat hunting, detection, monitoring, and response at scale.
Databricks Announces Lakewatch: New, Agentic SIEM
Databricks announces Lakewatch, an agentic SIEM intended to help organizations defend against increasingly sophisticated, AI-driven attackers. Launching in Private Preview, it unifies security, IT, and business data in a governed lakehouse built on Unity Catalog, while supporting open OCSF formats and storage in customer-controlled cloud object stores. Lakeflow Connect ingests and normalizes major security sources, and Detection-as-Code lets teams define YAML rules with SQL queries or Python notebooks, backtest them against historical data, and deploy through CI/CD. Genie Code and Genie Spaces provide AI-assisted ingestion, detection authoring, rule refinement, investigation, and natural-language threat hunting, while custom models can support anomaly detection, behavioral analytics, and entity risk scoring. The announcement also introduces an Open Security Lakehouse Ecosystem and acquisitions of Antimatter and SiftD.ai; Lakewatch is available in Private Preview, with Adobe and Dropbox among the named customers.
Announcing the 2026 Built
Databricks has announced its third annual Built-On Databricks Startup Challenge, inviting early-stage startups that use Databricks as a core part of customer-facing, B2B applications to compete for more than $1M in prizes. Eligible companies must have been founded within the last five years, be incorporated in one of the listed countries, and be no later than Series B if funded. The competition offers a potential Databricks Ventures investment of up to $600,000, up to $500,000 in Databricks product credits across finalists, and access to Databricks resources, workshops, mentorship, and feedback. Judging considers Databricks usage, market potential, and founding team strength and experience; applications close May 22, 2026, with judging in late May and winner announcements during the week of June 15, 2026, at the Databricks Data + AI Summit in San Francisco.
Announcing General Availability and Open Sourcing of Unity Catalog Business Semantics
Databricks announces the general availability of Unity Catalog Business Semantics, a unified semantic foundation for consistent business definitions across BI dashboards, notebooks, SQL applications, and AI agents. Built into Unity Catalog, it applies existing governance, security, lineage, and access controls to centrally defined Metric Views, whose metadata includes display names, formats, and synonyms. Metric Views are authored declaratively in SQL, compiled and executed deterministically at query time, and can use materializations with automatic pre-aggregation, incremental refresh, intelligent query rewriting, and transparent routing; materialization remains in Preview. The core Metric View implementation is being open sourced in Apache Spark OSS for an upcoming release, with Unity Catalog OSS v0.5 support coming soon, while a point-and-click authoring UI is in Public Preview.
Accelerate business insights with Lakeflow Connect, now with a Free Tier
Databricks is introducing a Lakeflow Connect Free Tier to help teams ingest SaaS application and operational database data into the Databricks Data + AI Platform, addressing silos that can leave AI agents without complete enterprise context. Each workspace automatically receives 100 free DBUs per day for managed SaaS and database connectors only, with capacity advertised as up to 100 million records per workspace per day across eligible supported sources. Lakeflow Connect offers 30+ connectors, including SaaS services and databases, through a point-and-click UI and API, with Unity Catalog providing unified governance and end-to-end lineage. The offer uses standard pricing without volume-based premiums or row-based pricing, but actual capacity varies with workload characteristics, record sizes, and source types.
The official ClickHouse provider for Apache Airflow is now available
Apache Airflow users can now use an upstream ClickHouse provider, offering an officially maintained alternative to community plugins or custom integration code. The provider, apache-airflow-providers-clickhousedb, uses ClickHouse Connect over HTTP(S), integrates with Airflow’s common SQL framework, and supplies ClickHouseHook for bulk inserts, streaming, and client-specific operations. The post documents installation, connection setup, standard SQLExecuteQueryOperator DAGs, bulk insertion, and local or managed deployment through Astronomer, including TLS settings for ClickHouse Cloud. Production examples include Astronomer’s Astro Observe, Chartmetric’s 15-million-row playlist pipeline every five minutes, and ClickHouse’s warehouse, which schedules 76 DAGs across more than 40 sources and moves about 6 billion rows daily. The provider is available now, with future capabilities guided by community requests.
Introducing the Life Sciences Verification Program
The Life Sciences Verification Program (LSVP) opens beta access to Mythos, Opus, and Sonnet models for verified life science teams whose work may be blocked by generally available Fable models. Applicants undergo review of research credentials, security standards, and ethical oversight, then may receive annual Standard Use grants or six-month, project-specific High-risk Use grants. Standard Use employs more permissive biology classifiers across research, clinical, manufacturing, and other workflows, while High-risk Use removes life-science safeguards for specifically vetted projects; cyber safeguards remain. The program shifts enforcement from request-level blocking to offline monitoring of behavioral patterns, requiring 30-day retention of flagged-activity data, compartmentalized from training and life sciences research teams. Access is available through API, Claude Science, Claude.ai, Claude Code, and Enterprise or Team plans, but not individual plans, third-party platforms, or BAA-enabled organizations during beta.
A skills library for every agent
The post introduces Notion’s skills library and Skills API, aimed at helping teams share organizational knowledge across AI agents and workflows. The library is designed for nontechnical and technical users, with collaborative editing, database organization, supporting files, permissions, suggested edits, version history, usage analytics, and controls over skill distribution. The API provides endpoints for loading skills in spec-compliant file formats, with examples including synchronization to GitHub, installation through Vercel’s Skills CLI, and uploads or edits through MCP tools. Notion says early customers and partners are already using the API across agents and tools, while an open-source starter kit supports Notion-to-GitHub synchronization. Vercel’s Skills CLI can install individual Notion skill pages or workspace plugins, using standards-compliant files without handling Notion-specific formats.
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