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Announcement reads
Announcement posts on Yomu, summarised newest first.
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Announcement posts
Deploy and manage coding agents at scale with the Unity Gateway CLI
Organizations face a challenge as new frontier models appear roughly every five days, making it difficult to balance flexibility with governance. Databricks introduces the Unity Gateway CLI, which lets admins centrally configure approved coding agents, models, MCP servers, skills, and spending policies. Developers launch any approved agent with a single ug command, and the CLI handles authentication and applies the published settings. Features include Smart Routing that selects cost-appropriate models per task, budget-aware defaults that switch to lower-cost options as spending thresholds are reached, and tracing to capture tool calls and skill invocations for waste analysis. In internal use, the system processed over 61 billion input tokens across roughly 360,000 requests, and tracing helped identify bugs that saved an estimated 1.2 million per year.
From Dockerfile to Kit: the Docker Sandboxes Kit Specification
The Docker Sandbox Kit Specification v3 defines how an agent declares the networks, credentials, and volumes it needs, so these grants travel with the artifact rather than living in shell history or dashboards. A Kit is an ordinary OCI image whose manifest carries a descriptor annotation vnd.docker.sandbox.kit.descriptor, so it builds with docker buildx, pulls with docker pull, and gets scanned and signed by existing tooling. Capability types like network-policy@2 and credential@1 are versioned independently, and each normative statement in the specification is covered by a conformance check or a written waiver. Two Kit types exist: a workload supplies the root filesystem, while a mixin adds overlays such as a CLI with its network rule; the runtime rejects required capabilities it cannot satisfy. Composition uses strict provides/requires resolution, so authority changes appear as diffs, and a conforming runtime can gate upgrades that widen the grant set.
Accelerating vision-language models with LFM2.5-VL-DSpark
Liquid AI released an experimental DSpark draft model for their vision-language model LFM2.5-VL-3B. The drafter adds a speculative decoding path that trades a minimal increase in memory footprint for a larger speedup without changing output quality. The 280M-parameter drafter, a 4-layer attention-only transformer, captures the target model’s hidden states at fixed tapped layers to draft a block of candidate tokens. On an M5 Max, decoding runs 2.30x to 3.13x faster by task, with end-to-end latency improvements of 1.56x to 2.62x. The drafter ships with day-one support for llama.cpp, MLX-VLM, and SGLang, and is available on Hugging Face in Safetensors and GGUF formats.
Continuing to Move PHP Open Source Forward
Each year, PhpStorm selects five open-source projects to sponsor for a full year, providing financial support and raising awareness of open source in the PHP community. For this year, the chosen projects are PHPUnit, Lerd, static-php-cli, Composer, and Larabelles, selected from community suggestions based on their impact and need for financing. Sebastian Bergmann, creator and maintainer of PHPUnit, offers the most widely used testing suite for PHP. George Dumitrescu’s Lerd manages local PHP installations and servers, while Jerry Ma’s static-php-cli is used by FrankenPHP and Native PHP. PhpStorm continues its sponsorship of the PHP Foundation and encourages other organizations to contribute to open source, as every bit of support makes a substantial difference when added together.
Measuring the back/forward cache with Application Metrics
The back/forward cache (bfcache) allows instant page restores by freezing snapshots, yet its hits register no events in traditional telemetry, creating a blind spot for teams. Sentry’s bfcacheMetricsIntegration fills this gap by modeling three browser-provided signals as application metrics: a navigation counter with hit/miss outcome, a per-reason counter for misses via the notRestoredReasons API, and a distribution of fallback reload duration. The integration is opt-in and launched in JavaScript SDKs v11; detailed miss reasons are currently Chromium-only due to browser API support. Users can query these metrics to break down bfcache health by route, release, or browser, enabling discovery of regressions caused by unload listeners, cache-control headers, or third-party scripts. This turns the bfcache from an invisible performance feature into a measurable, trackable signal that teams can monitor and improve.
Turn your REST APIs into MCP tools with Google Cloud API Gateway
Most enterprise REST APIs are invisible to AI agents, forcing teams to run separate MCP servers that duplicate their existing gateway logic. Google Cloud API Gateway in Public Preview solves this by acting as a remote MCP server — annotate the OpenAPI 3.0.x/3.1.x spec with x-google-api-management.mcp and deploy it with no extra infrastructure. The gateway accepts MCP JSON-RPC requests on a single /mcp endpoint, transcodes tools/call into the corresponding REST call, runs it through existing policies, and returns the response as an MCP result. Authentication via JWT or API key works unchanged for REST operations; tools/list is unauthenticated by default and requires JWT in production for security. With no separate server to operate, teams in Public Preview can expose up to 1,000 tools per gateway that support existing authentication and quota, and the MCP server is automatically discoverable via API hub and Agent Registry.
Welcoming Gaby Garcia, our new Recruiter
Resend announced the hiring of Gaby Garcia as a new full-cycle recruiter who combines a people-first approach with strategic sourcing and a passion for creating thoughtful, scalable recruiting processes. Garcia holds a background in Psychology, which she says brings curiosity and empathy to her work, and she continually looks for ways to improve how teams hire. She spent the last five years at Automattic hiring engineers and designers, making her well acquainted with developers and the DevTools space. Garcia expressed excitement about Resend’s focus on culture and growing together, stating she loves helping people find a place where they can do meaningful work and feel like they belong. She aims to help Resend grow while being part of that kind of team herself, bringing her expertise to the company’s hiring process.
Bringing Private Processing to Meta AI Glasses
Meta AI glasses require cloud processing for advanced AI features like streaming transcription and long-term recall, but traditional cloud architectures expose data during use. Private Processing uses confidential virtual machines with Trusted Execution Environments (TEEs) on CPUs and GPUs to keep data encrypted even while being computed. Before sending context, glasses perform remote attestation, verifying the server’s TEE certificate against a public transparency ledger that records all deployed binary images. Non-targetable routing via blind-signed tokens and third-party OHTTP relays prevents tying requests to specific users, while encrypted storage ensures data is only accessible with user-provided keys. This infrastructure, already proven for WhatsApp and Meta AI, extends to glasses, with security audits by firms like NCC Group and a bug bounty program for independent research.
Introducing NV-Reason-CT Open 3D CT VLM for Radiologist Chain-of-Thought Reasoning
NVIDIA released NV-Reason-CT, a vision language model for 3D CT analysis that processes volumes as true 3D input rather than independent 2D slices. The model generates structured diagnostic reports covering 30 chest and 29 abdominal abnormalities and emulates radiologist chain-of-thought reasoning with systematic anatomical reviews and uncertainty articulation. Its architecture pairs a Qwen3.5-4B language model with a full 3D ViT encoder that processes volumes resampled to 192³ voxels at 2mm isotropic resolution using 8x8x8 patch tokens and 3D MRoPE for spatial token relationships. Training uses supervised fine-tuning on roughly 550,000 QA examples from CT-RATE, NIH CT, and CancerVerse followed by Group Relative Policy Optimization that refines reasoning quality based on diagnostic accuracy. NV-Reason-CT is an open research foundation not a cleared clinical product and sits within NVIDIA’s Medical AI ecosystem alongside NV-Reason-CXR, NV-Segment-CTMR, and NV-Generate-CTMR.
Claude discovers a novel enzyme system
Anthropic launched a new life sciences research group to use AI agents for fundamental biology discovery. In one of their first programs, Claude agents autonomously analyzed over 200,000 reverse transcriptase sequences from a DNA database. After 21 hours and 210 million tokens, one agent spotted a repeating DNA pattern next to a reverse transcriptase gene, which it identified as a CRISPR-like system. The system, called ART (array-associated reverse transcriptases), consists of the RT, an accessory protein, and an array of non-coding DNA repeats that are expressed as distinct small RNAs. Its function remains unknown, but the pattern of repeats is only found together in other programmable DNA-cutting systems, suggesting ART may be a new tool for biotechnology.
Unity Catalog Pages: a governed home for your business knowledge in Genie Ontology
Business concepts like active customer or completed trip are often defined differently across teams, scattered in Slack threads and spreadsheets, causing AI agents to guess confidently when answering questions. Databricks introduces Unity Catalog Pages as a governed home within Genie Ontology where data stewards with Genie Code define the authoritative meaning of those terms and entities. Pages complement existing semantics — metric views how to calculate, domains where to look, and certification what to trust — by capturing what each concept means. Genie Code can bootstrap Pages by extracting definitions from Confluence, Slack, Google Docs, or GitHub via MCP-connected tools, turning weeks of work into minutes. When Genie One uses a Page to ground an answer, the Page is cited as a clickable source so users can inspect the definition and verify the reasoning.
**Know Who Spoke When: Build Real-Time, Multi-Speaker AI with NVIDIA Nemotron 3 Diarization**
NVIDIA Nemotron 3 Diarization is an open-weight, 100M-parameter model that ranks #1 on VoiceArena’s Diarization-Bench leaderboard with a 14.72% Diarization Error Rate (DER). It classifies who spoke when in conversations, handling overlapping speech and supporting up to eight speakers across live and recorded audio. The model uses a Sortformer approach with arrival-order speaker labeling, a 31-layer Transformer encoder, and two memory mechanisms for streaming inference. It accepts 16 kHz single-channel audio and outputs a floating-point tensor of speaker-activity probabilities at a configurable time step. Developers can combine its timestamps with automatic speech recognition to produce speaker-attributed transcripts, with recommended input-buffer latencies ranging from 0.32 to 30.4 seconds.
ClickHouse release 26.9
ClickHouse 26.9 ships with 56 new features, 135 performance optimizations, and 464 bug fixes. Among the highlights are conditional LIMIT boundaries that control output based on ordered stream values, incremental refreshes for append-only materialized views, and disk spilling for high-cardinality DISTINCT queries that automatically spills when memory usage reaches half the limit. The CREATE TOKEN feature issues time-limited credentials with a default lifetime of 30 minutes and restricted privileges, reducing the impact of leaked keys. Arithmetic operations between DateTime and Time types now support configurable overflow behaviors—throw, saturate, or ignore. PromQL support expands in a private preview on ClickHouse Cloud, bracket syntax simplifies JSON subcolumn access, and queries for min, max, and count receive performance improvements.
How to Guide Your Language Flow
Probe guidance, a novel method for guiding flow matching models, is introduced. It uses the frozen internal states of an existing diffusion model to construct a guidance signal, operating on a similar principle as autoguidance but removing the need for an additional forward pass at inference time. The method provides a reliable path ensuring the weak and strong models share similar dynamics. Probe guidance sets a new state-of-the-art performance on unconditional generation when benchmarked on continuous diffusion language models. Applied to a 1.7B diffusion language model, it consistently improves multiple choice question answering benchmarks.
Rollouts and Security Review
Cursor launched two bots for the last mile of shipping code: Rollouts and Security Review. Rollouts watches every change as it deploys and reports health per environment, with verdicts of verified healthy, regression detected, or inconclusive. It reads the diff and systems a pull request touches, writes a monitoring plan as a PR comment, and tracks deploy events per environment. Security Review reads every pull request in the context of the codebase and posts one review comment reporting exploitable bugs, including injection, authentication bypasses, and secrets. Both bots are available today on Teams and Enterprise plans, with usage credits for the next 10 days.
Conversations in the AI Era: Manchester Meetup Recap
Twilio and Ciptex hosted the Conversations in the AI Era meetup in Manchester on September 3rd, 2026, drawing developers, tech leads, and founders from the local scene. Darragh O’Connor demonstrated using a SIP trunk to connect callers directly into a livestream, emphasizing solving the problem with the simplest tool. Matthew Duggan of Ciptex presented an architecture where AI and human agents share conversation state and tools, treating handoff as a change of ownership rather than a recovery path. Paul D’Ambra of PostHog discussed how cheap code generation made reviewing code the bottleneck, leading them to build AI review agents that substantially dropped their revert rate. The next meetup is scheduled for November 4th, 2026.
Introducing Support for Local AI Models in the Antigravity SDK
The Antigravity SDK now supports local AI models, starting with Gemma 4 26B A4B via Google AI Edge’s LiteRT, enabling offline agentic assistance on local GPU and RAM with a recommended machine of 24GB VRAM or unified memory. Local execution eliminates API costs and rate limits while keeping code and requests on-device, offering privacy and offline resiliency. The SDK supports hybrid workflows where a cloud model like Gemini 3.8 Flash plans while local Gemma 4 instances execute, as in a code auditing task where 97.2% of tokens (3,322 of 3,417) ran locally. A built-in example generates a live-updating CLI resource monitor using psutil and rich from a single prompt, with the agent autonomously writing the script, creating requirements.txt, and testing the code entirely offline. The SDK also supports any OpenAI-compatible server like Ollama, LM Studio, or vLLM via LocalOpenAIAgentConfig without changing agent orchestration.
AI Agent Observability: Making Silent Production Failures Visible and Actionable
Agentforce Health Monitoring (AHM) addresses silent availability failures in production AI agents that traditional monitoring misses because agents can appear healthy even when unreachable. The team unified telemetry from approximately five or six locations across sessions, reasoning steps, tool calls, errors, and escalations into a coherent representation. End-to-end alerting latency was reduced from roughly 20 minutes to several minutes by converting Data 360 ingestion to streaming and simplifying query complexity. AHM provides 16+ built-in metrics including agent availability, error rate, response/escalation rate, engagement, and latency, with a drill-down interface connecting alerts to session context. The roadmap includes cost, TTFT/TTLT, toxicity, feedback metrics, RAG Quality Monitoring integration, and eventually a runtime insight agent for root-cause analysis and automated remediation.
The Genie One MCP is now Generally Available
Databricks has announced general availability of the Genie One Model Context Protocol (MCP) server, now a managed service within Unity Gateway with centralized governance, fine-grained policies, and audit logging across every invocation. The MCP provides a single governed interface for any AI agent to access structured and unstructured data from Genie One, grounded in governed business context from Genie Ontology, eliminating agent sprawl and inconsistent answers. It exposes tools for asking questions, getting query results, checking incremental progress, and steering responses, with an optional MCP App for real-time interactive visualizations and Genie Ontology citations. Connected agent clients automatically interpret domain semantics via Genie Ontology across relational data and document repositories without custom connectors. Use cases include enriching slide creation with richer data, bringing customer usage context to outreach agents, and integrating business definitions into developer workflows, as noted by GetYourGuide.
How Fountain rebuilt its data plane on ClickHouse Cloud to power Cue, the Frontline Superintelligence
Fountain rebuilt its data plane on ClickHouse Cloud to power Cue, its agentic AI platform for frontline hiring, moving off a multi-vendor BigQuery and S3/Iceberg batch stack. The migration cut analytics latency from three hours to under two minutes, with most queries returning in under a second, at roughly 66% lower cost. Data from 13 Postgres production databases and four MongoDB databases streams into ClickHouse Cloud via ClickPipes managed CDC, landing as Iceberg and Parquet in S3 before reaching BigQuery and ClickHouse. The new architecture uses two symmetrical pipelines—one for Postgres, one for MongoDB—each running a short path: source, ClickPipes, materialized views, and Cue. The system now carries 8.48 billion CDC rows replicated continuously by ClickPipes and 10.3 billion analytics rows across 15 deployments, served by over 2,000 incremental materialized views.
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