---
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

### [Mercedes-Benz builds a cross-cloud data mesh with Delta Sharing and intelligent replication, cutting costs by 66%](https://yomu.fyi/post/mercedes-benz-builds-a-cross-cloud-data-mesh-with-delta-sharing-and-in.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Alexander Summa, Aleksandar Dragojevic
- Published: Apr 20, 2026
- Type: Problem & solution

Mercedes-Benz built a cross-cloud data mesh to share after-sales data between AWS and Azure while supporting its data-defined vehicle strategy. Existing direct queries incurred egress costs, and weekly full loads delayed updates for datasets that included vehicle over-the-air events and workshop visits; source tables were in Iceberg while many consumers expected Delta. Using Unity Catalog and Delta Sharing, the company federated AWS Glue tables, established cross-metastore shares, and used periodic serverless Sync Jobs with Delta Deep Clone to incrementally replicate selected tables into Azure object storage for local querying. This hybrid model preserves direct sharing for fresher workloads while reducing transfer for less time-sensitive ones. For the initial ten data products, egress costs fell 66%, update frequency improved from weekly to every second day, and the source reports an approximately 93% annual reduction in its 50-use-case comparison.


### [What Is a Transactional Database?](https://yomu.fyi/post/what-is-a-transactional-database.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Apr 20, 2026
- Type: Explainer

Transactional databases handle large volumes of short, real-time read and write operations for systems such as orders, payments, account balances, and customer records. They support online transaction processing (OLTP) by treating related steps as one logical unit: successful work commits, while failures roll back the full transaction. ACID—atomicity, consistency, isolation, and durability—protects integrity under concurrency and failures, with row-oriented storage optimized for individual-record access, locking and isolation levels coordinating concurrent work, and write-ahead logging (WAL) supporting crash recovery. The source positions these databases as foundations for banking, e-commerce, healthcare, reservations, and telecommunications, while noting that row-oriented execution is less suitable for large analytical workloads and that horizontal scaling is more complex than in distributed NoSQL systems.


### [Launch Week 6: Wrap Up](https://yomu.fyi/post/launch-week-6-wrap-up-up.md)
- Company: [Resend](https://yomu.fyi/company/resend.md)
- Published: Apr 20, 2026
- Type: Announcement

Launch Week 6 concluded with five feature releases and one announcement covering email automation, content creation, developer tooling, tracking, and community events. Automations orchestrates lifecycle emails from application events with delays, waits, conditions, test runs before publishing, and real-time visibility into runs. The AI-extended editor turns URLs into on-brand drafts, supports inline block editing and mistake detection, and connects to agentic stacks through the Resend MCP server, while CLI 2.0 adds React-file sending, automation and event management, webhook listening, and AI-agent skills across more than 50 API commands. Custom tracking domains support click and open tracking, React Email 6 adds an embeddable editor and extensions API, and Resend Forward was announced as a San Francisco conference scheduled for October 21.


### [Terraform & OpenAPI for ClickPipes is now Generally Available](https://yomu.fyi/post/terraform-openapi-for-clickpipes-is-now-generally-available.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Marta Paes
- Published: Apr 20, 2026
- Type: Announcement

ClickHouse Cloud announced the general availability of ClickPipes resources in Terraform and OpenAPI, expanding infrastructure-as-code support across its managed data ingestion platform. The release resolves previous beta gaps by adding full connector coverage, including Change Data Capture for Postgres, MySQL, and MongoDB, alongside support for BigQuery, Azure Blob Storage, and reverse private endpoints. Operators can provision new data ingestion pipelines, pause or resume sync operations, and scale resources programmatically through OpenAPI endpoints or the ClickHouse Terraform provider starting at version 3.14.0. Existing ClickPipes can also be imported into Terraform state using native import blocks and automated configuration generation. Although SSH tunneling remains under active development, nearly all UI capabilities now map cleanly to programmatic interfaces.


### [Resend Forward: A Conference about Craft](https://yomu.fyi/post/resend-forward-a-conference-about-craft.md)
- Company: [Resend](https://yomu.fyi/company/resend.md)
- Published: Apr 18, 2026
- Type: Announcement

Resend Forward is a newly announced conference for developers who treat software as a craft. It will take place in San Francisco on October 21st and run for a full day focused on the craft behind building software. The program will feature leaders working at the edge of software and AI, with special emphasis on practical tools and ideas that attendees can use. Food, conversations, and swag are planned between sessions, while the stated goal is to connect people who care about quality, share what’s working, and leave them more excited to build. More details are expected in the coming months; tickets will go on sale after the waitlist notification.


### [Introducing Genie Agent Mode](https://yomu.fyi/post/introducing-genie-agent-mode.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Hanlin Sun
- Published: Apr 17, 2026
- Type: Announcement

Databricks introduces Agent mode in Genie spaces, an agentic process that plans, explores, and reasons over data to answer business questions. For each question, Genie can confirm an issue, test potential contributors through multiple queries, reflect on results, and decide what to investigate next, using Unity Catalog metadata and author-defined semantics from the Genie space. It produces a findings report with quantified results, identified contributors, visualizations, and references to the underlying SQL, and may include actionable recommendations. The agent scales its reasoning to task complexity, using validation for straightforward questions and more planning for multi-step investigations; in AI/BI Dashboards, Genie uses Agent mode by default. Workspace admins enable the feature in Workspace Previews, after which users turn on the Agent toggle in Genie spaces; API support and unstructured document analysis are planned additions.


### [Governing coding agent sprawl with Unity AI Gateway](https://yomu.fyi/post/governing-coding-agent-sprawl-with-unity-ai-gateway.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Aarushi Shah, Ankit Mathur, Bilal, Kevin Stumpf, Rohit Agrawal, Harish Gaur, Ana Nieto
- Published: Apr 17, 2026
- Type: Announcement

Databricks introduces coding agent support in Unity AI Gateway to address security, cost, and visibility challenges created by organizations using multiple coding tools. The gateway provides a unified governance hub for Codex, Cursor, and Gemini CLI, combining access controls, usage statistics, operational observability, cost management, guardrails, and inference capacity. Agent access can be governed centrally, with audit logs in Unity Catalog, MCP servers managed in Databricks, MLflow tracing, shared cost limits, and coding metrics and traces ingested into Unity Catalog-managed Delta tables through OpenTelemetry. The announcement says developers can authenticate with Databricks credentials across connected services, use centralized budgets and model capacity, and let organizations analyze adoption, developer velocity, and rate-limit pressure in the lakehouse; support for Cursor, Gemini CLI, and Codex CLI is available to all Databricks customers.


### [otel.fyi - OTel Collector docs made simple](https://yomu.fyi/post/otel-fyi-otel-collector-docs-made-simple.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: The ClickStack Team
- Published: Apr 17, 2026
- Type: Problem & solution

OpenTelemetry Collector documentation is often fragmented across separate contrib repositories as individual README files, making component configuration difficult and time-consuming to navigate. To address this friction, the team created otel.fyi as a dedicated platform to aggregate, simplify, and structure documentation from across the ecosystem. The implementation parses contrib repositories to pull configuration examples and normalize metadata across receivers, processors, exporters, and extensions into a unified format. By surfacing structured component information upfront, the site allows practitioners to assemble working configurations rapidly without digging through multiple GitHub repositories. Originally developed for internal operational workflows, the platform has been released publicly to assist the broader community, with future plans to introduce an AI assistant.


### [“A generational leap”: How Trio unified payment analytics and cut storage by 88% with ClickHouse Cloud](https://yomu.fyi/post/a-generational-leap-how-trio-unified-payment-analytics-and-cut-storage.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: ClickHouse
- Published: Apr 17, 2026
- Type: Problem & solution

Brazilian payment processor Trio faced severe data challenges after scaling and acquiring PayBrokers, processing over 243 million payments in early 2025 across disparate legacy databases. Because financial reconciliation and compliance demand absolute precision, the engineering team unified their analytics layer by migrating to ClickHouse Cloud. To handle out-of-order and duplicate events from their Redpanda streaming pipelines, Trio implemented sliding-window refreshable materialized views alongside ReplacingMergeTree engines rather than recomputing entire historical datasets. A custom ETL service manages schema drift before inserting clean records into ClickHouse, while batch ingestion is coordinated through Airflow. Consequently, Trio reduced storage consumption by approximately 88% through columnar compression, ingested a 5-billion-row migration without issue, and maintained real-time query performance across more than one billion daily ledger data points.


### [What is pgvector?](https://yomu.fyi/post/what-is-pgvector.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Apr 17, 2026
- Type: Explainer

pgvector is an open-source PostgreSQL extension that adds vector storage, indexing, and similarity search for embeddings alongside relational application data. It supports semantic search, recommendations, retrieval-augmented generation (RAG), image similarity, anomaly detection, and deduplication without requiring a separate vector database for many workloads. The extension uses the vector data type and distance metrics including L2, cosine similarity, and inner product, with HNSW and IVFFlat indexes offering different speed and memory trade-offs. Vector queries can also combine relational filters with Postgres full-text search for hybrid retrieval. pgvector is positioned as a practical choice for existing Postgres deployments, while pgvectorscale can extend its usefulness as data and query demands grow; dedicated vector databases become more relevant at larger scales, and Databricks AI Search serves complementary lakehouse workloads.


### [Banks don't have an AI problem — they have a data platform problem](https://yomu.fyi/post/banks-don-t-have-an-ai-problem-they-have-a-data-platform-problem.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Naeem Rehman, Jennifer Miller
- Published: Apr 17, 2026
- Type: Explainer

The post argues that banks’ difficulty scaling AI stems less from model capability than from fragmented data, weak governance, and limited real-time access. Examples from CBA Live 2026 include model drift in credit scoring, fragmented customer signals, and a collections model that predicted, with 85% accuracy, how many days newly delinquent accounts would take to cure using governed data. It also presents Erica’s 3.2 billion interactions since 2018 as evidence that production AI requires continuous tuning, monitoring, and edge-case management, while generic models decay in frontline settings. The proposed Databricks architecture combines Lakehouse, Unity Catalog, Lakeflow, Lakebase, MLflow, Model Monitoring, Online Feature Store, Genie, and Agent Bricks to support governed analytics, low-latency decisions, auditable models, and constrained agent actions. Its conclusion is that a shared data platform should precede additional AI use cases because it improves deployment speed, trust, explainability, and regulatory defensibility.


### [React Email 6.0](https://yomu.fyi/post/react-email-6-0.md)
- Company: [Resend](https://yomu.fyi/company/resend.md)
- Published: Apr 17, 2026
- Type: Announcement

React Email 6.0 announces an open-source visual editor as its centerpiece, available as a standalone package that outputs email-ready HTML for major inbox providers. The editor is built in two layers: a core that works without configuration and a composable API using EmailNode for custom extensions, with optional themes for styling. The release ships new authentication and e-commerce templates from Character Studio, available as React Email templates or Figma files. All components are now unified into a single package except the editor, simplifying imports and reducing package management. The project has reached 2 million weekly downloads, a 108% increase since the last major release five months ago.


### [Open Platform, Unified Pipelines: Why dbt on Databricks is Accelerating](https://yomu.fyi/post/open-platform-unified-pipelines-why-dbt-on-databricks-is-accelerating.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Srilekha Dornadula, Ramiz Bozai
- Published: Apr 16, 2026
- Type: Explainer

dbt provides structure for transforming raw data into curated datasets, but the post argues that its effectiveness depends on the underlying platform. Databricks is presented as an open lakehouse combining storage, compute, governance, orchestration, and monitoring to reduce duplicated data, fragmented permissions, and operational overhead. Lakeflow Jobs runs dbt alongside ingestion, downstream actions, retries, and dependencies, while Unity Catalog supplies persistent permissions, documentation, lineage, and fine-grained controls. The integration also supports Delta Lake and Apache Iceberg, query tags for cost tracking, Photon, Predictive Optimization, Liquid Clustering, and dbt materialized views. The post concludes these capabilities provide openness, integrated operations, governance, and price-performance for dbt workflows, citing one customer’s consolidation of notebooks and 7+ source systems and more than 2,900 customers already running dbt on Databricks.


### [Building a Unified Pipeline for AI Token Spend](https://yomu.fyi/post/building-a-unified-pipeline-for-ai-token-spend.md)
- Company: [Ramp](https://yomu.fyi/company/ramp.md)
- Author: Kedar Thakkar, Richard Wang, Veeral Patel
- Published: Apr 16, 2026
- Type: Explainer

AI token spend is volatile, consumption-based, and distributed across teams, making usage and cost difficult to monitor. Ramp's pipeline ingests LiteLLM and OpenRouter events through authenticated, tenant-scoped webhooks, Kafka, and ClickHouse, then aggregates them for REST dashboards and AI-generated forecasts. LiteLLM uses callbacks with token counts and metadata, while OpenRouter sends OTLP traces; ReplacingMergeTree deduplicates replayed events using business\_id, source, and event\_id. Customers can connect gateways with an API key, configure LiteLLM callbacks or OpenRouter Broadcast, and pass attribution metadata. The resulting visibility supports breakdowns by provider, model, department, user, project, and use case, and exposed phantom Gemini reasoning tokens after a LiteLLM upgrade, geo pricing premiums, runaway loops, and prompt bloat.


### [How GitHub uses eBPF to improve deployment safety](https://yomu.fyi/post/how-github-uses-ebpf-to-improve-deployment-safety.md)
- Company: [Github](https://yomu.fyi/company/github.md)
- Author: Lawrence Gripper
- Published: Apr 16, 2026
- Type: Problem & solution

Deployment scripts can introduce dangerous circular dependencies when they rely on services or assets from platforms that are currently experiencing outages. Blocking network access at the host level is impractical because stateful nodes continue serving live traffic during rolling deployments. To solve this, GitHub isolates deploy scripts into dedicated Linux cGroups and attaches custom eBPF programs via the cilium/ebpf Go library. The system uses socket-address hooks to redirect DNS queries to a userspace proxy that checks a domain blocklist, while egress packet hooks map DNS transaction IDs to process IDs. This approach successfully prevents deploy-time circular dependencies, provides full command-line audit logs for blocked requests, and speeds up incident recovery.


### [April 2026 newsletter](https://yomu.fyi/post/april-2026-newsletter.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Mark Needham
- Published: Apr 16, 2026
- Type: Announcement

ClickHouse 26.3 LTS introduces experimental materialized common table expressions, WebAssembly user-defined functions, and enables asynchronous inserts by default. Alongside the release, Alasdair Brown launched clickhousectl to manage local installations and cloud deployments with built-in agentic development features and authentication safeguards. User case studies show Goldsky accelerating historical blockchain backfills by twelve times through direct ClickHouse reads using Apache Arrow, replacing their prior Kafka and Avro architecture. Additionally, the engineering team redesigned the full-text search index with front-coding compression, a sparse lookup index, and adaptive posting lists to handle expensive random reads on object storage. ClickHouse also previewed community architecture patterns for lightweight SIEM setups using Clickdetect and Wazuh log collection.


### [Why your agents can't read enterprise documents — and how to fix it](https://yomu.fyi/post/why-your-agents-can-t-read-enterprise-documents-and-how-to-fix-it.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Archika Dogra, Sergei Tsarev, Erich Elsen
- Published: Apr 16, 2026
- Type: Announcement

Enterprise agents often reason well over clean text but struggle with scanned PDFs, inconsistent layouts, nested tables, images, and handwriting, making document processing an accuracy ceiling for business workflows. The post announces Document Intelligence, a pipeline of chainable AI Functions: ai\_parse\_document converts scans into layout-enriched structured text, while ai\_classify and ai\_extract support routing and entity extraction. On OfficeQA treasury-bond documents, preprocessing with ai\_parse\_document produced a 16% average performance gain across tested agent frameworks without changing their reasoning harness. Across invoice, contract, medical-note, and financial-filing extraction tasks, it reportedly delivered the highest accuracy at 5–7x lower cost than comparable pipelines, with serverless batch infrastructure scaling the same SQL call from 100 to 100,000. Databricks integrates ingestion, orchestration, governance, and agent building through Lakeflow Connect, Lakeflow Jobs or Spark Declarative Pipelines, Unity Catalog, and Agent Bricks, aiming to replace fragmented services with reusable workflows.


### [Building with Databricks Document Intelligence and Lakeflow](https://yomu.fyi/post/building-with-databricks-document-intelligence-and-lakeflow.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Giselle Goicochea, Joanna Zouhour
- Published: Apr 16, 2026
- Type: Tutorial

The post presents a production-oriented approach to Intelligent Document Processing (IDP) that brings PDFs, images, and office documents into Databricks’ governed data lifecycle. Lakeflow Connect ingests files from sources such as SharePoint and Google Drive into Unity Catalog Volumes and tables, applying access control, lineage, and auditing while supporting incremental reads and writes. Databricks’ Document Intelligence then uses ai\_parse\_document to preserve structure in VARIANT output, with ai\_extract, ai\_classify, and ai\_prep\_search available for enrichment, routing, and retrieval preparation. Lakeflow Jobs productionizes the workflow with orchestration, control flow, retries, triggers, serverless scaling, and observability across ingestion, parsing, and serving tasks. The post also recommends joining extracted data to master data, using service principals, and monitoring drift and extraction accuracy, presenting the combined platform as a way to create trusted, queryable datasets from unstructured content.


### [Databricks on Google Cloud: Innovate faster. Smarter. Together.](https://yomu.fyi/post/databricks-on-google-cloud-innovate-faster-smarter-together.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Taylor Hoss, Sarah Jack
- Published: Apr 16, 2026
- Type: Announcement

Databricks and Google Cloud are presenting their partnership at Google Cloud Next ’26 as a route from governed enterprise data to production AI, including autonomous agents and modernized workloads. In 2025, Databricks became a first-party provider of Gemini models, giving users direct API access to build, customize, and deploy agentic AI on governed data across all three Databricks clouds without moving data or managing infrastructure. The post reports more than 55% quarter-over-quarter growth in Gemini adoption, 85% year-over-year growth in Google Cloud consumption, and 4,000-plus Marketplace sign-ups, alongside support for Google Axion processors. Customer examples include Databricks SQL Serverless savings for Digital Turbine, faster Marketplace procurement for Dun & Bradstreet, regional compliance in Saudi Arabia and Brazil, and 30% faster analytics delivery through Lakeflow-powered pipelines. At the event, Databricks is offering demos, talks, expert sessions, and a free $400 trial through Google Cloud Marketplace.


### [What is Generative AI in Marketing?](https://yomu.fyi/post/what-is-generative-ai-in-marketing.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Apr 16, 2026
- Type: Explainer

Generative AI in marketing creates content, insights and recommendations that can personalize experiences, optimize campaigns and improve performance. Unlike traditional analytics, which mainly reports on past results, it produces net-new outputs such as ad copy, audience segments, product recommendations, visual assets and strategic summaries. A typical workflow prepares campaign, customer and brand data, grounds or fine-tunes models, generates outputs, applies targeting and optimization, and uses human review and refinement. It distinguishes pretrained tools such as ChatGPT, Claude and Perplexity from customized models and broader AI transformation, noting trade-offs between speed, investment, relevance and strategic alignment. Successful adoption depends on high-quality, consented data, governance, privacy controls, human oversight, monitoring and cross-functional ownership; the conclusion presents AI as a force multiplier rather than a replacement for human creativity and judgment.


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