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Announcement reads
Announcement posts on Yomu, summarised newest first.
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Announcement posts
ClickHouse Release 26.6
ClickHouse 26.6 is a release marking the 10-year anniversary of ClickHouse becoming open source, with 56 new features, 79 performance optimizations, and 366 bug fixes. Hypothetical skip indexes let users evaluate set indexes in a session without building them; on a 487.24-million-row UK property dataset, the example estimated skip ratios of 77.0% at granularity 128 and 92.2% at granularity 1. The release overhauls dependencies between refreshable materialized views, addressing schedule drift that could make dependent stages lag or miss a refresh cycle. It also introduces experimental continuous queries, the aiEmbed function, embedding quantization to 8 bits and below, and workload-level memory reservations.
ClickHouse Agents is now available for Managed Postgres
ClickHouse Agents is now available for all Managed Postgres services in ClickHouse Cloud, extending its plain-English agent interface to operational data. The beta service, powered by Claude and built on LibreChat, combines an agent builder and chat interface with a sandboxed code interpreter; it is read-only by default and supports MCP-compatible systems. Agents can inspect Postgres schemas, run read-only queries, return the SQL used, and reason across Postgres and ClickHouse by querying each engine independently before merging results. Additional skills guide migration from Postgres to ClickHouse through discovery, access-pattern analysis, schema design, type mapping, CDC ingestion, and validation, while other workflows use metrics, Query Insights, and EXPLAIN to rank performance fixes. Planned extensions include scheduled recommendations and safe automated remediation, but the current release focuses on exploration, analysis, monitoring, and guided database work.
Celebrating the Winners of the 2026 Built-On Databricks Startup Challenge
The 2026 Built-On Databricks Startup Challenge recognized early-stage startups building B2B applications on Databricks, with winners presented at the 2026 Data + AI Summit. VisionHeight won the Grand Prize for an agentic threat-intelligence platform that maps adversary infrastructure across the Internet while it is being constructed, aiming to give defenders earlier warning. Linkup took second place with a production-grade Web Search API that independently crawls and indexes the open web at the fact level, delivering sourced results in about two seconds. Intelo placed third with five coordinated AI Agent Teams covering retail merchandising and planning, while Clarecast, Gemini Sports, and LakeFusion received Honorable Mentions. Judges assessed market potential, founding-team caliber, and innovative Databricks use; the announced Startup Program also offers qualifying startups up to $200,000 in combined Databricks and Neon credits.
Securing Heroku CLI Credentials with System Keychain Storage
Heroku CLI 11.8.0 changes credential storage by making the system keychain the default and retaining .netrc as a fallback. The transition began in 11.6.0, when the CLI stored tokens in both locations to preserve existing workflows. The credential manager uses macOS security, Linux Secret Service through secret-tool, or Windows PasswordVault, storing credentials under “heroku-cli” with the account email as the identifier. Authentication lookup prioritizes HEROKU_API_KEY, then HEROKU_NETRC_WRITE, keychain storage, and .netrc files; unsupported or failing keychain access falls back to .netrc. Version 11.8.0 also adds a Git credential helper, so commands such as git push heroku main continue without configuration changes, while CI/CD can keep using HEROKU_API_KEY and Linux users may need secret-tool.
Redeploying Claude Fable 5
Access to Claude Fable 5 and Mythos 5 was restored after US export controls had temporarily suspended both models for all users. The post says Fable 5 will return globally on July 1 across Claude Platform, Claude.ai, Claude Code, and Claude Cowork, while Mythos 5 access has resumed for some US organizations and broader partner access remains under discussion. Anthropic describes a new safety classifier intended to block the bypass reported by Amazon researchers in more than 99% of cases; blocked Fable 5 requests are sent to Opus 4.8, although the classifier increases false positives in coding and debugging. It also outlines defense-in-depth safeguards, a proposed shared industry framework for assessing jailbreaks, and expanded government collaboration on pre-release evaluation, information sharing, and joint research.
Claude Fable 5 and Claude Mythos 5
Claude Fable 5 and Claude Mythos 5 are presented as a joint launch of the same underlying model, with Fable 5 intended for general use and Mythos 5 initially reserved for selected cyberdefenders and infrastructure providers. Fable 5 uses conservative safeguards that route some sensitive queries to Claude Opus 4.8, while Mythos 5 lifts safeguards in selected areas through Project Glasswing and a planned trusted-access program. The post reports strong results in software engineering, knowledge work, vision, long-context tasks, cybersecurity, protein design, molecular biology, and genomics, including a reported 50-million-line Ruby migration completed in a day. Both models are priced at $10 per million input tokens and $50 per million output tokens, with Fable 5 available through the Claude API and staged subscription access.
Forecasting at the speed of modern retail
Retail and CPG forecasting now spans hundreds of thousands, sometimes far more, time series across fragmented channels, promotions, and short-lived products, making legacy methods and manual exception management difficult. Multi-model forecasting addresses this complexity by evaluating a range of techniques against actual data and selecting the best-performing model for each series, but enterprise-scale experiments require scarce forecasting and distributed-systems expertise. Released in 2024, Databricks’ open-source Many Model Forecasting (MMF) integrates more than 35 statistical, deep-learning, and foundation time-series models and runs on distributed Databricks compute. MMF Agent, built on Genie Code, guides users through data quality, series classification, compute configuration, forecasting, post-processing, and model selection, while Unity Catalog helps it use organizational data context. The workflow is intended to reduce setup from days to hours, improve targeting and accuracy, and make rigorous forecasting more accessible while remaining customizable for technical teams.
Celebrating the Winners of the 2026 Built-On Databricks Startup Challenge - Cloned
The 2026 Built-On Databricks Startup Challenge recognized early-stage startups building B2B applications on the Databricks platform, with winners announced at the Data + AI Summit in San Francisco on June 16. VisionHeight won the grand prize for an agentic threat-intelligence platform that maps adversary infrastructure across the Internet while it is being built; Linkup placed second with a production-grade Web Search API delivering results in about two seconds, and Intelo placed third with an agentic workforce for retail merchandising and planning. Clarecast, Gemini Sports, and LakeFusion received honorable mentions for predictive intelligence, football squad planning, and an AI-native data foundation combining MDM, PIM, and LakeGraph. Judges assessed market potential, founding-team caliber, and innovative use of Databricks, while the startup-program offer provides qualifying startups up to $200,000 in credits across Databricks and Neon.
Announcing our $800M Series C to accelerate the shift to open-source AI
Together AI announces an $800M Series C to accelerate its open-source AI platform as production demand for inference grows. The company says the round includes $800 million from investors including Aramco Ventures, NVIDIA, Vista Equity, General Catalyst, and others, plus commitments for more than 500 MW of compute capacity to be capitalized independently by new investors. Together argues that closed frontier-model economics become unsustainable as agents and workflows scale, while open-weights models such as DeepSeek, Nemotron, MiniMax, Kimi, and GLM can provide equal or better performance at lower cost. Its full-stack approach spans models, kernels, compilers, inference systems, training infrastructure, hardware utilization, and software, with cited work including FlashAttention-4, Together Megakernel, together.compile, and expanded post-training APIs for tool calling, reasoning, and vision-language models.
Build agentic full-stack apps with Genkit
Genkit Agents is an open-source, full-stack foundation for conversational AI and agentic applications, supporting TypeScript, Go, Dart, and Python. The Agents API packages message history, tool loops, streaming, persistence, and frontend communication behind a shared interface: agents can run in process or behind HTTP, and clients use chat() through remoteAgent(). Developers can choose client-managed state or session-store-backed snapshots, resume by session ID, branch from snapshot ID, stream text, custom state, and artifacts, and pause tools for human approval. The framework also supports detached long-running work, specialist delegation, persistence choices including in-memory, file, Firestore, and custom stores, plus an Agent Runner in the Developer UI. The Agents API is in preview for TypeScript and Go, with breaking changes possible in minor releases.
ML Development in VS Code with Google Cloud Power: Workbench Extension Now Available
Google Cloud has launched the Google Cloud Workbench Notebooks extension for VS Code, allowing developers to use managed cloud notebook environments from a local IDE. Workbench, described as a managed Jupyter platform optimized for data science, can provide access to Google Cloud's AI-optimized infrastructure and high-performance compute when local machines need more capacity. The workflow connects through VS Code's Extensions view, the Jupyter extension, and a notebook's Select Kernel menu, where users choose Google Cloud, Workbench, authenticate, select a project, and choose an active instance. The extension runs notebooks on Workbench instances, preserves local settings and extensions, is fully open-sourced, and is available through the VS Code Marketplace, with GitHub contributions invited.
Agentic Coding on Supabase with OpenCode
Supabase has made its OpenCode integration available, connecting an AI coding agent to Supabase account and project management APIs and bundled Supabase skills. Users invoke /supabase, authenticate, and, for database, Edge Functions, logs, and other project-scoped capabilities, are guided through connecting Supabase MCP; the integration requires OpenCode 1.3.4 or later. It can list organizations and projects, create projects, open the MCP setup flow, monitor agent activity in real time, and let agents query data, check logs, and deploy functions, while the plugin is open source. The post demonstrates the workflow in Minecraft, where OpenCode connected through MCP, created and populated a table, and deployed an Edge Function on a real Supabase project.
Anthropic integration with Modal brings scalable compute to Claude Science
Anthropic launched Claude Science, an AI workbench where life sciences researchers run computational workloads from conversation with Claude. The workbench addresses the fragmented toolchain of local machines, HPC clusters, and cloud VMs by centralizing execution in one place. Modal integrates with Claude Science as the compute backend, routing GPU and CPU-heavy workloads to Modal sandboxes automatically and fanning out parallel tasks like virtual screening across hundreds of containers to reduce hours to minutes. Researchers can prompt for tasks such as predicting GFP structure, and Claude writes the folding code, runs it on a Modal GPU, and returns the structure with confidence scores inside the conversation, with Modal handling scheduling, shared storage, and reproducible environments. Modal is committing up to $100,000 in compute for the Claude Science Cohort, with 500– 2,000 allocations per project.
Together AI at ICML 2026: frontier research across the full stack
Together AI says nine papers from its researchers and peers were accepted to ICML 2026 in Seoul, spanning frontier agents, model shaping, algorithmic and systems optimization, and kernels. The collection is presented as a full-stack view of AI research, with work ranging from DSGym’s unified evaluation and training API for more than 1,000 data-science tasks to ThunderAgent’s program-aware scheduling, TTT-Discover’s test-time reinforcement learning, and RARO’s verifier-free adversarial training. Reported results include up to 3.6× agent throughput, state-of-the-art discoveries from an open 120B model, a 25% expert-response win rate without a verifier, and 5M-token context on one node for Untied Ulysses. Aurora illustrates the research-to-production loop: its adaptive speculative-decoding work ships as the ATLAS speculator on the Together platform.
Build reliable multi-agent applications with ADK Go 2.0. Discover our new graph-based workflow engine, built-in human-in-the-loop, and dynamic orchestration
ADK for Go 2.0 introduces a graph-based workflow engine for composing multi-agent applications whose execution can classify, branch, fan out, gather results, pause for human input, retry, and loop. Graphs consist of typed nodes and routed edges, with constructors for functions, emitting functions, agents, tools, joins, parallel workers, state-bound nodes, dynamic orchestration, and nested workflows; a scheduler handles concurrency, persistence, backpressure, cancellation, and resumption. Its built-in human-in-the-loop primitive validates responses, supports handoff or re-entry, and can resume durably after process restarts, while agent modes and a unified node runtime align single agents with full graphs. The release is highly additive for ADK 1.0 users, though context and event APIs require mechanical migrations, and it provides workflow examples for basic, routing, dynamic, HITL, and complex graphs.
The Builder Revolution: Why We're Shifting to Builder Advocacy
The team formerly known as Developer Advocacy, within Developer Success, has been renamed Builder Advocacy within Builder Experience (BX). The change responds to an expanded definition of who builds with technology: alongside traditional developers, AI builders and no-code or low-code automators are creating production-level experiences and mission-critical infrastructure. The organization says its advocacy will serve developers, prompt engineers, LLM integrators, AI-agent creators, ML practitioners, and automation-focused builders, while continuing support for traditional coders, engineers, and architects. The announcement cites GitHub’s 180 million developers, 36 million new developers in 2025, and Stack Overflow’s finding that 84% use or plan to use AI tools. The rename is effective immediately and begins broader investments in resources, content, and community programs for this wider builder community.
Teen rides return to Los Angeles
Uber for teens is now available in Los Angeles, allowing teens to request their own rides while guardians can book rides on their behalf. The service lets guardians track trips live, sends realtime notifications, pairs teens with highly rated drivers, and keeps PIN verification and RideCheck enabled for every ride. Guardians and teens can also message the driver in a shared group chat, while on-demand pickups and dropoffs must remain within the designated service area; Reserve trips remain available outside it. To book, a guardian selects “Where to?”, changes the rider from “For me” to the relevant teen, and chooses “Uber for teens.” Trips to or from airports cannot currently be requested.
Build from anywhere with Cursor for iOS
Cursor for iOS is available in public beta on all paid plans, bringing agent-based development to a native mobile app. Users can choose a repository, select a frontier model, provide voice input or slash commands, and launch agents in the cloud or control agents running on their computers through Remote Control. The app supports asynchronous workflows with Live Activities and push notifications, while cloud agents use isolated virtual machines and full development environments to test, verify, and produce demos, screenshots, logs, and merge-ready pull requests. Developers can review diffs, provide follow-up instructions, merge pull requests, and hand sessions between local and cloud environments, including sending a local plan to the cloud or returning a cloud session to the computer for local testing. Cursor says repo-less chats are planned, and offers 75% off Composer 2.5 runs in the mobile app through July 5, 2026.
Cursor Mobile App for iOS
Cursor for iOS is available in public beta for all paid plans, bringing agent management and development workflows to mobile. Users can choose a repository, launch a cloud agent with any frontier model, provide voice input, and guide it with slash commands; agents run in isolated virtual machines with full development environments for testing, verification, and demos. Sessions can move from local to cloud, while Remote Control lets people continue directing a computer-based agent from the phone, with an option to keep the computer awake; Teams and Enterprise administrators must enable that feature in Cursor Dashboard. Live Activities and push notifications report agent status, including completion, requests for input, and review readiness, and the app supports reviewing artifacts such as demos, screenshots, logs, and diffs, leaving instructions, and merging pull requests.
DXC integrates Claude into systems regulated industries rely on
Anthropic and DXC Technology announced a multi-year global alliance to bring Claude into mission-critical systems used by banks, airlines, insurers, manufacturers, and government agencies. DXC will train tens of thousands of Claude-certified forward-deployed engineers, while adding its own curriculum for regulated, mission-critical environments to Anthropic Academy’s certification. DXC first used Claude internally, including as the default foundation model for DXC OASIS, an AI-native managed-services orchestration platform whose code was more than 95% generated by Claude and reviewed by engineers; DXC estimates this accelerated development tenfold. The alliance initially targets insurance, legacy modernization, cybersecurity, and application services, including an always-on security engineer subagent for security operations centers. OASIS serves more than 50 DXC customers, with broader rollout planned.
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