---
title: "Latest reads"
description: "The engineering internet, summarised so you can actually read it."
---

# Latest reads
> The engineering internet, summarised so you can actually read it.

## Articles

### [Anthropic raises $124 million Series A](https://yomu.fyi/post/anthropic-raises-124-million-series-a.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

Anthropic, an AI safety and research company led by CEO Dario Amodei and President Daniela Amodei, has raised $124 million in a Series A financing round. The funding will support its research roadmap, computationally intensive work, and prototypes of reliable and steerable AI systems, with an emphasis on systems that are interpretable and robust. Its immediate priorities include increasing the reliability of large-scale AI models, developing techniques and tools for interpretability, and integrating human feedback more tightly into AI development and deployment. The round was led by Jaan Tallinn, co-founder of Skype, and included James McClave, Dustin Moskovitz, the Center for Emerging Risk Research, Eric Schmidt, and others; Anthropic is hiring researchers, engineers, and operational experts.


### [Five AI Questions We're Hearing from Financial Services Leaders](https://yomu.fyi/post/five-ai-questions-we-re-hearing-from-financial-services-leaders.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Junta Nakai, Erin Butler, Roshni Joshi, Antoine Amend, Jennifer Miller, Andrea DeSosa, Rajaram Suresh, Kim Hatton, Naeem Rehman, Spencer Cook, Ed Bullen, Felix Mutzl
- Published: Sep 9, 2026
- Type: Announcement

Financial services leaders are shifting from asking whether AI works to asking whether it can earn trust, amid governance and audit concerns. The post frames five operational questions around moving finance from reporting to action, using AI in financial crime without losing control, supporting bankers and investment teams, using real-time data, and managing expanding costs. Examples include governed GL-to-Risk reconciliation with cited evidence, human maker-checker oversight and an audit trail; AML agents that draft SARs while humans file; and multi-agent workflows for client and portfolio analysis. The post also cites Coinbase's sub-100ms P99 fraud-detection benchmark and warns that token costs manageable in pilots may grow in production, making model routing and spend visibility relevant. Databricks presents these topics through live demos, talks and meetings at Sibos 2026 in Miami, scheduled for September 28–October 1, including a session on governing AI in financial-crime operations.


### [Announcing ClickHouse Managed Postgres on Google Cloud](https://yomu.fyi/post/announcing-clickhouse-managed-postgres-on-google-cloud.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Sep 9, 2026
- Type: Announcement

ClickHouse Managed Postgres is entering Private Preview on Google Cloud, extending the fully managed, NVMe-backed Postgres service previously launched on AWS. The GCP deployment targets teams wanting Postgres for OLTP and ClickHouse for OLAP in one cloud, avoiding cross-cloud replication, egress costs, and separate networking and compliance management. It uses GCP Local SSD storage, native change data capture through ClickPipes, in-region networking, and pg\_clickhouse, which pushes filters, joins, and aggregations to ClickHouse behind a single Postgres connection. Preview capabilities include zonal high availability with two standbys and quorum replication, point-in-time recovery, read replicas, PgBouncer, more than 90 Postgres extensions, monitoring, Query Insights, scheduled upgrades, and infrastructure-as-code support through OpenAPI, Terraform, and clickhousectl. Access is invitation-only via a waitlist, with availability in every GCP region where ClickHouse Cloud runs and hands-on migration support from Cloud SQL, AlloyDB, RDS, Aurora, Neon, or self-managed Postgres.


### [Why Rider and ReSharper Were Slow to Start, and How Microsoft Helped Fix the Problem](https://yomu.fyi/post/why-rider-and-resharper-were-slow-to-start-and-how-microsoft-helped-fi.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Alexander Ulitin
- Published: Sep 9, 2026
- Type: Explainer

After ReSharper’s out-of-process (OOP) architecture launched, users reported slower Windows startup, and profiling traced the delay to Microsoft Defender scanning the separate process. Defender spends only a couple of seconds on processes in write-protected paths but can add tens of seconds when ReSharper loads DLLs from a user installation directory. The investigation used Microsoft Defender ETW logs and direct CPU-time measurements, with cold-start tests repeated 10 times inside an 8-vCPU, 8-GB Hyper-V VM; JetBrains IDEs took roughly 10–40 seconds to scan, while Microsoft IDEs and other editors stayed under one second. Collaboration with Microsoft led to Defender optimizations in version 1.449.454.0, improving scanning for ReSharper OOP and Rider in write-protected directories. JetBrains also released the Defender Performance Tool for live monitoring, offline snapshots, and CSV export.


### [Announcing ‘The 2026 AI Sentiment Report’: How end users feel about AI Agents](https://yomu.fyi/post/announcing-the-2026-ai-sentiment-report-how-end-users-feel-about-ai-ag.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Maia Bridi
- Published: Sep 9, 2026
- Type: Announcement

The 2026 AI Sentiment Report examines how end users feel about AI Agents in customer service and other uses such as shopping. Overall sentiment improved: 49% reported positive experiences, up nine percentage points from 2025, and that figure rose to 74% after respondents watched an Agent resolve a real query. Trust remains conditional, with 54% willing to trust AI with simple or routine issues but not complex ones involving discretion, privacy, continuity, accountability, or judgment. The research identifies easy escalation to a human and upfront disclosure that users are interacting with AI as the two leading ways to increase comfort, while trust also varies by channel, with chat strongest and social weakest. It concludes that businesses can treat trust as a design problem, including reassuring customers that shopping assistants serve their interests rather than merely the company’s financial goals.


### [A practical approach to end-to-end Solvency II reporting in Databricks](https://yomu.fyi/post/a-practical-approach-to-end-to-end-solvency-ii-reporting-in-databricks.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Laurence Ryszka, Jack Yallop
- Published: Sep 9, 2026
- Type: Explainer

Solvency II reporting connects data, actuarial reserving, capital calculation, quantitative reporting templates (QRTs), the ORSA, approvals, and disclosure, but fragmented systems make readiness and cross-process questions difficult to manage. The described Databricks implementation provides a governed workflow and control tower around existing actuarial and capital suites, automating ingestion checks, data-quality review, reconciliation, orchestration, reporting, and audit trails. It uses MLflow-managed reserving models alongside engines such as Prophet, RAFM, and Igloo, while narrow-scope AI agents can investigate QRT mismatches, suggest remediation, route questions, and support human review. An LLM can draft an ORSA from current numbers, while scenario analysis assesses doubling a cyber book over 12 months; reviewers retain decision authority. The workflow is presented as easier to monitor and investigate.


### [PwC deploys Claude across its business](https://yomu.fyi/post/pwc-deploys-claude-across-its-business.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

Anthropic and PwC are expanding their strategic alliance to use Claude for technology delivery, deal execution, and AI-led redesign of enterprise functions. PwC will roll out Claude Code and Cowork from U.S. teams toward a global workforce of hundreds of thousands, establish a joint Center of Excellence, and train and certify 30,000 professionals. The collaboration targets agentic technology builds, AI-native deal-making, and production operating models for finance, supply chain, HR, and engineering, alongside a new Claude-based Office of the CFO for regulated industries. Reported deployments include insurance underwriting reduced from ten weeks to ten days, an HR application delivered in under two months, and cybersecurity response accelerated from hours to minutes, with improvements of up to 70%.


### [Anthropic acquires Stainless](https://yomu.fyi/post/anthropic-acquires-stainless.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

Anthropic is acquiring Stainless, an SDK and MCP server tooling company founded in 2022, to expand how Claude and other agents connect to data and tools. Stainless has generated every official Anthropic SDK since the API’s early days and is used by hundreds of companies to produce SDKs, CLIs, and MCP servers from API specifications. Its tooling supports TypeScript, Python, Go, Java, and other languages, with libraries designed to feel native while remaining fast and reliable. The companies say combining their teams will advance developer experience and agent connectivity on the Claude Platform, while Stainless’s founder, Alex Rattray, said the team will continue its work within Anthropic.


### [KPMG integrates Claude across its workforce](https://yomu.fyi/post/kpmg-integrates-claude-across-its-workforce.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

KPMG announced a global alliance with Anthropic to integrate Claude across its workforce and client services in 138 countries and territories. Every 276,000+ KPMG employees will receive access, while Claude is embedded in Digital Gateway, the Microsoft Azure-based platform that combines tax expertise, proprietary tools, and client data; initial client tools target tax and legal work. Claude Cowork and Managed Agents are intended to let professionals build capabilities inside the platform, while KPMG and Anthropic will use Claude to identify and fix vulnerabilities under KPMG’s Trusted AI framework and develop offerings for private-equity portfolio companies. The alliance also names KPMG a preferred private-equity partner, introduces offerings including KPMG Blaze with Claude Code, and draws on joint UT Austin research emphasizing employee judgment, workflow design, output evaluation, and decision-making alongside AI.


### [KiYoung Choi named Representative Director of Korea](https://yomu.fyi/post/kiyoung-choi-named-representative-director-of-korea.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Sep 9, 2026
- Type: Announcement

KiYoung Choi is joining Anthropic as Representative Director of Korea ahead of the planned opening of its Seoul office. Korea is described as one of Claude.ai’s most active markets, with usage more than 3.5 times the rate expected for its population size and concentrated in technical and creative work. Choi joins from Snowflake, where he was General Manager for Korea, bringing over three decades of experience across technology businesses in Korea and Asia-Pacific, including country leadership roles at Google Cloud, Adobe, Autodesk, and Microsoft. He will lead a Korea go-to-market strategy, build the local team and partnerships, and support enterprise, startup, government, research, and developer engagement; examples of existing use include Law&Company’s legal assistant and SK Telecom’s custom customer service model.


### [IBM releases SOTA Granite Time Series PatchTST-FM-r2 model with commercial-friendly license](https://yomu.fyi/post/ibm-releases-sota-granite-time-series-patchtst-fm-r2-model-with-commer.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Roman Vaculin, Wesley M. Gifford, Jiri Navratil, Chandra Reddy, Ayhan Sebin
- Published: Sep 9, 2026
- Type: Announcement

IBM has released Granite Time Series PatchTST-FM-r2, a roughly 385-million-parameter foundation model for zero-shot forecasting across demand, prices, energy loads, traffic, telemetry, and other time series. The model uses conformer blocks combining multi-head self-attention with temporal convolution, 50% overlapping patches with Hamming-window weighting, overlap-and-add forecasting, contexts up to 8,192 steps, and a 99-quantile prediction head for probabilistic outputs and imputation support. On GIFT-Eval, it ranks second for both CRPS and MASE among replicable zero-shot models as of September 8, 2026, and first in that category among permissively licensed models; including pretrained models, it ranks third for CRPS and fourth for MASE. IBM provides open weights, architecture, inference code, and reproducibility code under Apache 2.0 and OpenMDW 1.0. The release also describes Python use and streaming integration through Apache Flink on Confluent Cloud.


### [Deploy NeMo Guardrails on Red Hat OpenShift AI](https://yomu.fyi/post/deploy-nemo-guardrails-on-red-hat-openshift-ai.md)
- Company: [Red Hat](https://yomu.fyi/company/red-hat.md)
- Author: Rob Geada
- Published: Sep 9, 2026
- Type: Tutorial

This article shows how to deploy an evaluated NeMo Guardrails configuration on a Red Hat OpenShift AI cluster, continuing a series on local development and dataset-based evaluation. It requires OpenShift AI 3.5 or later and namespace write access, while OpenShift AI 3.2 or newer can be configured to use the 3.5 NeMo Guardrails image through TrustyAI service-operator changes. Deployment uses a ConfigMap for the configuration, a NemoGuardrails custom resource, and an authentication annotation that protects the server route; an empty rails.co file is sufficient when no custom algorithms are defined. The deployed server accepts v1/guardrail/checks requests with a bearer token, and the demonstrated classifier permits a benign prompt, blocks a prompt injection, and rejects an invalid token. The article notes that LLM proxying and LLM-based guardrailing are outside its scope.


### [Get Gemini 3.8 Flash With 75% Off](https://yomu.fyi/post/get-gemini-3-8-flash-with-75-off.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Dmitry Savelev
- Published: Sep 9, 2026
- Type: Announcement

Google’s Gemini 3.8 Flash is now available in Junie’s IDE plugin and Junie CLI, accompanied by a limited-time 75% introductory discount. The model targets long, multi-step engineering tasks: it spends more tokens exploring directories, retrying failed code, writing bug-reproduction scripts, running tests through tool calls, and checking changes before completion. Google’s DeepSWE v1.1 testing is described as showing 3.8 Flash outperforming most larger frontier models at significantly lower cost, although the source does not provide specific scores. Gemini 3.7 Flash remains available for minor fixes and small refactorings, where its lower per-token cost may be preferable, while 3.8 Flash can be selected from the model picker without setup or a waitlist.


### [Beyond embedding: How to secure AI/BI Dashboards for every viewer](https://yomu.fyi/post/beyond-embedding-how-to-secure-ai-bi-dashboards-for-every-viewer.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Sonakshi Pandey
- Published: Sep 9, 2026
- Type: Explainer

Embedding a Databricks AI/BI Dashboard in a customer-facing application is straightforward; authorization determines which rows each viewer may see. The pattern supports external partners and internal Databricks teams with one dashboard and shared dataset, while applying different regional access and masking rules. An entitlements table stores partner IDs and IdP-synchronized group names alongside regions and PII-mask flags; a secured view filters on the signed \_\_aibi\_external\_value from the embed token. Direct SQL access is separately protected by Unity Catalog row filters and column masks, which evaluate the querying user's identity and groups. The design provides a default-deny, pooled logical multi-tenancy model that centralizes rules while covering both application and workspace query paths.


### [Use a local and open source code assistant](https://yomu.fyi/post/use-a-local-and-open-source-code-assistant.md)
- Company: [Red Hat](https://yomu.fyi/company/red-hat.md)
- Author: Seth Kenlon
- Published: Sep 9, 2026
- Type: Tutorial

Closed or cloud-based coding assistants can expose work to external services, so the article presents a local, open-source alternative built around OpenCode. OpenCode is an AI coding agent—not an LLM—that runs as a terminal interface, desktop application, or IDE extension and connects to models through the Model Context Protocol (MCP). The setup installs OpenCode, selects a local model runtime such as Ollama for AMD/NVIDIA GPUs or OpenVINO Model Server with INT4 Qwen3-8B for Intel integrated graphics, then configures opencode.jsonc and an editor plug-in. Examples cover Qwen3:14b with Ollama, Podman-based OpenVINO serving, and NetBeans integration; the resulting assistant can answer queries and edit files after permission is granted, although local inference may be slow and generated advice can be unreliable.


### [Introducing Consort: Test-driven development on a branching database](https://yomu.fyi/post/introducing-consort-test-driven-development-on-a-branching-database.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Kevin Hartman
- Published: Sep 9, 2026
- Type: Announcement

Consort is introduced as an open-source agentic development framework for test-driven development on branching Lakebase Postgres databases. It addresses the limitations of mocks, shared staging databases, and risky schema-change ceremonies by bringing integration testing into the inner loop. Its build lane runs red/green/refactor cycles against isolated copy-on-write branches of real data, while versioned migrations keep code and schema changes together and pull-request checks test migrations against fresh branches. Consort organizes work through role-based agents and a deterministic conductor, preserving feature artifacts in dedicated directories and supplying scoped context packages. A VS Code plugin pairs Git and Lakebase branches, while an observability dashboard exposes agent turns and human approval gates; the project is community-supported rather than a bundled platform feature with an SLA.


### [Adaptive Instructed-Retriever: Frontier-Quality Search at 2x Lower Latency](https://yomu.fyi/post/adaptive-instructed-retriever-frontier-quality-search-at-2x-lower-late.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Cheng Li, Jialu Liu, Sean Kulinski, Arnav Singhvi, Wen Sun, Michael Bendersky, Cindy Wang
- Published: Sep 9, 2026
- Type: Benchmark

Adaptive Instructed-Retriever addresses the tension between retrieval quality and latency for enterprise data agents, especially on multi-hop questions that benefit from sequential search. It combines parallel single-step retrieval with bounded multi-step search, using a fixed upper limit and an adaptive stopping policy that spends extra steps only when they are likely to improve results. The model is trained with online reinforcement learning using CISPO, a reward that balances trajectory quality against search cost, and synthetic multi-hop data alongside Instructed-Retriever-1 data. Across seven held-out internal and external benchmarks, it matches leading third-party and open-source models while answering in 5.8 seconds, reported as more than twice as fast as the compared alternatives, and substantially improves over single-step search. Varying the step penalty produces checkpoints spanning different quality-latency tradeoffs for production workloads.


### [How we rebuilt Cloudflare Workers’ module registry for Node.js compatibility](https://yomu.fyi/post/how-we-rebuilt-cloudflare-workers-module-registry-for-node-js-compatib.md)
- Company: [Cloudflare](https://yomu.fyi/company/cloudflare.md)
- Author: Logan Gatlin
- Published: Sep 9, 2026
- Type: Explainer

Cloudflare has rebuilt the module registry in workerd, the open-source core of the Workers runtime, to improve speed, standards compliance, and alignment with Node.js. The change addresses compatibility beyond runtime APIs by making module resolution, loading, and caching behave more like Node.js across ESM, CommonJS, and WebAssembly. The new registry uses URLs as specifiers, supports import.meta.url, import.meta.main, and import.meta.resolve(), distinguishes modules by query strings and fragments, validates import attributes, follows require(esm) rules, and compiles modules lazily while sharing caches across isolates. It also supports WebAssembly source phase imports and consistent loading errors; the existing registry remains in place, and the new implementation must be enabled with the new\_module\_registry compatibility flag.


### [Join our live webinars: Migrating from Atlassian to YouTrack](https://yomu.fyi/post/join-our-live-webinars-migrating-from-atlassian-to-youtrack.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Elena Pishkova
- Published: Sep 9, 2026
- Type: Announcement

YouTrack announces live webinars for teams considering migration from Atlassian after Atlassian’s stated discontinuation of Data Center sales and support. The worldwide English-language session is scheduled for September 30, 2026, at 2:00 pm CET on YouTube, alongside a Japanese Zoom session and a Russian-language regional session hosted by Noventiq on October 28. The agenda covers migrating projects, users, and data from Jira, Confluence, and Jira Service Management, with a live demo, customer stories, pricing, licensing, deployment options, user packs, and partner support. It is aimed at administrators, project managers, and team leads, and presents YouTrack as a place to combine project management, documentation, and customer support. The Japan session additionally covers workflow automation and connecting AI agents through MCP, while registration for the Asia and Caucasus session is not yet open.


### [Rust AI in Practice: Building LLM Applications With Rig](https://yomu.fyi/post/rust-ai-in-practice-building-llm-applications-with-rig.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Irina Mihajlovic
- Published: Sep 9, 2026
- Type: Explainer

Rig is an open-source Rust library that provides a common interface for LLM providers including OpenAI, Anthropic, and Gemini, avoiding application rewrites when switching services. It structures applications around a provider client, completion model, agent, preamble, and registered tools, with async APIs handling provider network requests. In the Rat Code demo, built with Ratatui, separate tools read and write files and run shell commands, while Rig’s streaming API updates the terminal as responses arrive. The library also supports RAG through vector store abstractions, local inference via Ollama, llama.cpp, or Candle, and cassette-based integration tests that replay recorded HTTP interactions in CI; live model quality requires separate scheduled testing.


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