---
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

### [Remote control for local agents](https://yomu.fyi/post/remote-control-for-local-agents.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Published: Oct 6, 2026
- Type: Announcement

Cursor has introduced Remote Control, allowing users to view and interact with local agents running on their computer from the Cursor iOS app; agents appear in a list and users can tap one to see its activity or send a message. The feature is enabled by default for all users except Enterprise organizations; users tap their computer in the app and approve a pairing request in the Cursor desktop app. Agents remain running on the user’s computer, which must stay on and online; the app provides a “Keep this computer awake” setting to prevent sleep, and the computer must be plugged in with the lid open. Enterprise admins can enable Remote Control in Org settings under Security and identity. Remote Control does not rely on cloud agents and is available now in the Cursor iOS app.


### [Expanding our enterprise inference capacity with IBM Cloud and NVIDIA](https://yomu.fyi/post/expanding-our-enterprise-inference-capacity-with-ibm-cloud-and-nvidia.md)
- Company: [Together AI](https://yomu.fyi/company/together-ai.md)
- Published: Oct 6, 2026
- Type: Announcement

Together AI is collaborating with IBM and NVIDIA to scale enterprise-grade AI inference using a dedicated cluster of NVIDIA B300 GPUs on IBM Cloud with NVIDIA Spectrum-X Ethernet networking. This is the first large-scale inference cluster of its kind on IBM Cloud, and Together AI is the first customer running on it. Together AI operates the inference layer, IBM provides the cloud, and NVIDIA delivers the silicon and networking. The company serves hundreds of trillions of tokens per month to over a million developers, and demand continues to climb. Enterprises choose open models to keep their data sovereign and achieve frontier-level performance at a fraction of closed-model cost.


### [Data-Driven, Interoperable Core Banking: A BIAN and MongoDB Perspective](https://yomu.fyi/post/data-driven-interoperable-core-banking-a-bian-and-mongodb-perspective.md)
- Company: [MongoDB](https://yomu.fyi/company/mongodb.md)
- Published: Oct 6, 2026
- Type: Explainer

Core banking modernization is hindered by semantic fragmentation, where the same banking concepts are defined differently across systems, creating duplicated logic and fragile integrations. The Banking Industry Architecture Network (BIAN) provides a shared semantic foundation by defining common banking domains, boundaries, and service interactions, enabling a composable architecture. MongoDB’s document model, using JSON as both storage and interchange format, allows banks to represent business domains flexibly and evolve incrementally without schema migrations, eliminating the ORM impedance mismatch. MongoDB ensures financial integrity through single-document atomicity for common ledger updates and multi-document ACID transactions for complex cross-domain workflows, while Change Streams enable event-driven operations. Together, BIAN and MongoDB create an operating model for continuous transformation, where teams modernize domain by domain, supported by a shared business language and a scalable, flexible data platform.


### [EmbeddingGemma 2: The Developer Guide](https://yomu.fyi/post/embeddinggemma-2-the-developer-guide.md)
- Company: [Google](https://yomu.fyi/company/google.md)
- Author: Maarten Grootendorst, Ian Ballantyne
- Published: Oct 6, 2026
- Type: Tutorial

Modern search and RAG applications need to work across diverse content types, but finding models with strong retrieval accuracy and low latency without massive compute is challenging. EmbeddingGemma 2 is a compact open model under Apache 2.0, based on Gemma 4, that maps text, code, images, video, and audio into a unified 768-dimensional space with a modular architecture scaling from 270M to 740M parameters. Key capabilities include native multimodal retrieval, superior code understanding, modular memory footprint, and flexible vector storage via Matryoshka Representation Learning enabling dynamic truncation from 768 to 128 dimensions. Under the hood, it uses modular encoders—a text/code decoder, vision encoder, and audio encoder—that project into a shared space and can be loaded selectively to minimize memory. The developer guide demonstrates how to use sentence-transformers to load the model, embed with task prompts, handle media inputs, truncate dimensions, and choose configurations based on storage and recall needs.


### [Bring multimodal semantic search to the edge with EmbeddingGemma 2](https://yomu.fyi/post/bring-multimodal-semantic-search-to-the-edge-with-embeddinggemma-2.md)
- Company: [Google](https://yomu.fyi/company/google.md)
- Author: Google AI Edge Team, Android ML Team
- Published: Oct 6, 2026
- Type: Announcement

Google DeepMind launched EmbeddingGemma 2, an open-weight multimodal embedding model that maps text, images, video frames, and audio into a single vector space. Designed for local, privacy-first applications, it runs on as little as ~191MB active RAM for text-only weights and ~567MB for the full multimodal model on a Google Pixel 11 Pro. The model powers two new interactive showcases in Google AI Edge Gallery: Instant Media Search, which retrieves local images and videos via natural language or example images, and Video Moments Finder, which locates specific visual moments in local video files without transcribing audio. Google AI Edge Foresight for Mac uses EmbeddingGemma 2 alongside Gemma 4 for local meeting note-taking, cross-modal retrieval, and live question answering. Optimizations include modular encoders, quantization-aware training to INT4/INT8, and Matryoshka Representation Learning slicing to reduce storage footprints by up to 8x.


### [Turning Customer Identity into A Growth Engine](https://yomu.fyi/post/turning-customer-identity-into-a-growth-engine.md)
- Company: [Auth0](https://yomu.fyi/company/auth0.md)
- Author: Bradford Peirce
- Published: Oct 6, 2026
- Type: Announcement

Customer Identity and Access Management (CIAM) has traditionally been viewed as a security obligation, but Auth0 argues it can be a growth driver when optimized for conversion. The Auth0 Identity Conversion Suite combines Anonymous Sessions and Experiment Center to transform identity from a rigid gatekeeper into a dynamic growth engine. Anonymous Sessions issue scoped access tokens to track anonymous users from their first interaction, preserving cart contents, preferences, and consent selections when they convert to authenticated accounts. Experiment Center enables native A/B testing and gradual rollouts of authentication flows, allowing teams to test changes on controlled traffic segments before global deployment with audit trails. The suite addresses high cart abandonment in retail, cross-device context loss in travel, and onboarding friction in financial services by enabling seamless guest transitions, cross-channel journey unification, and progressive trust and compliance.


### [NEAREST BY Join: Scaling Vector Search in Databricks Runtime](https://yomu.fyi/post/nearest-by-join-scaling-vector-search-in-databricks-runtime.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Zero Qu (Zero), Alexis Schlomer, Akash Nayar, Yingyi Bu, Sergei Tsarev
- Published: Oct 5, 2026
- Type: Explainer

Batch vector search workloads, such as entity resolution and semantic tagging, require high throughput across millions of queries against billions of vectors, unlike real-time serving. Databricks built NEAREST BY, a first-class top-k ranking join syntax, directly into its runtime engine rather than federating to an external endpoint. The feature is implemented as a logical join that the optimizer lowers onto standard relational operators, enabling fault tolerance and elastic parallelism. A fused Photon operator collapses the plan’s middle section with a blocked GEMM kernel designed to approach peak arithmetic intensity for vector scoring. An optional IVF index, stored as an ordinary liquid-clustered Delta table, allows approximate queries to probe only relevant clusters while preserving the same primitives and correctness guarantees.


### [AI Agents Need Memory: Building Persistent Memory for Agentforce](https://yomu.fyi/post/ai-agents-need-memory-building-persistent-memory-for-agentforce.md)
- Company: [Salesforce](https://yomu.fyi/company/salesforce.md)
- Author: Scott Nyberg
- Published: Oct 5, 2026
- Type: Explainer

Enterprise AI agents without persistent memory suffer from the “Groundhog Day” problem, repeatedly asking users to re-explain themselves. Agentforce Memory addresses this by giving agents persistent memory that retains user preferences, conversation history, and context across sessions. The team first established a shared terminology document to define concepts like semantic and episodic memory before architectural discussions could proceed. The architecture evolved incrementally, starting with conversation history injection and later adding semantic retrieval to find relevant past information regardless of recency. Memory retrieval uses keyword search during pre-orchestration to balance context quality with low latency, and moving memory into the Reasoner simplified configuration for administrators. Privacy and user trust were treated as architectural requirements from the start, enabling individual user controls over memory creation and management.


### [How Genie Ontology powers product development at Databricks](https://yomu.fyi/post/how-genie-ontology-powers-product-development-at-databricks.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Nicole Esibov
- Published: Oct 5, 2026
- Type: Problem & solution

General-purpose AI agents fail on business questions because they lack enterprise context such as authoritative tables, business rules, and trusted experts; the missing institutional knowledge is scattered across dashboards, documents, and people. Databricks’ Genie Ontology addresses this by continuously updating institutional knowledge from certified Unity Catalog concepts and automatically learned snippets from dashboards, notebooks, SQL queries, and connected apps. OntoRank ranks sources by authority using certification, usage, and authorship signals, so Genie grounds answers in the most trusted and relevant data. In a weekly adoption review, a product manager prompts Genie, which uses MCP to search Google Docs and Jira while running live SQL for fresh analysis. The resulting report includes citations, forecasting, scheduling, and even conversion into a shareable Genie Agent, all within permission boundaries.


### [Announcing the AWS Digital Sovereignty Well-Architected Lens](https://yomu.fyi/post/announcing-the-aws-digital-sovereignty-well-architected-lens.md)
- Company: [AWS](https://yomu.fyi/company/aws.md)
- Author: Rodrigue Vitini
- Published: Oct 5, 2026
- Type: Announcement

The new AWS Digital Sovereignty Well-Architected Lens offers extended guidance for designing, building, and operating sovereign workloads, addressing challenges not fully covered by existing guidance. It includes procedures to deploy Oracle Database on Amazon EVS with FSx for ONTAP, covering provisioning, NFS mounting, and SnapMirror replication. It details multi-day AZ evacuation drills with ARC Zonal Shift across ECS, EKS, RDS for PostgreSQL, and Aurora PostgreSQL, providing CLI commands and observability metrics. MHK built the SmartProminence AI Orchestrator on Amazon Bedrock, a HIPAA-eligible framework that reduced manual medical review by 90% and cut deployment from months to weeks. CSIRO developed Serverless Beacon for genomic variant querying on AWS, implementing the GA4GH standard with S3, Lambda, DynamoDB, and Athena.


### [Executable UDFs are now generally available on ClickHouse Cloud](https://yomu.fyi/post/executable-udfs-are-now-generally-available-on-clickhouse-cloud.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Oct 5, 2026
- Type: Announcement

Executable user-defined functions (UDFs) have moved from public beta to general availability on ClickHouse Cloud across AWS, GCP, and Azure. The GA release adds a Native runtime for precompiled statically linked binaries in Rust, Go, C++, and JavaScript, requiring both amd64 and arm64 architectures, alongside the existing Python support. UDFs now have network access to public endpoints, a per-process memory limit, a deterministic flag that enables query caching, and are not billed separately, running inside service pods. ClickHouse 26.6+ provides eight ProfileEvents counters and two asynchronous metrics for per-query UDF cost monitoring, and the Cloud API and Terraform provider support UDF management with per-service version pinning. The post demonstrates counting LLM tokens and grading completions using these UDFs, showing how to put tokenization libraries next to the data in ClickHouse.


### [dotInsights | October 2026](https://yomu.fyi/post/dotinsights-october-2026.md)
- Company: [Jetbrains](https://yomu.fyi/company/jetbrains.md)
- Author: Rachel Appel
- Published: Oct 5, 2026
- Type: Announcement

The dotInsights newsletter from JetBrains collects recent .NET and software development articles for developers. Topics include C# 15 collection expression arguments, union serialization with System.Text.Json, and control flow obfuscation for .NET and Java teams. Several posts focus on ASP.NET Core, covering middleware, RAG integration, and using passkeys for second factor authentication. The newsletter also features discussions on event-driven architecture versus CRUD over pub/sub and the impact of AI on database schema design. JetBrains announces the Rider 2026.2.3 release and explains how Microsoft helped fix slow startup times for Rider and ReSharper.


### [Making the best of a bad situation: Lessons from an Intercom outage - The Intercom Blog](https://yomu.fyi/post/making-the-best-of-a-bad-situation-lessons-from-an-intercom-outage-the.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Incident / postmortem

Intercom’s outage began with a page about elevated exceptions, leading engineers to dive into Datadog and uncover a lurking 32-bit integer limit in one of the most critical parts of the app’s data model. The chaotic five-hour incident marathon required monkey patches, data migrations, and feature flag gymnastics to restore normal operations. After stabilizing the system, the team applied important technical changes to the Rails application to prevent integer overflow and similar failures. Miles McGuire presented the postmortem at Rails World 2024, sharing the debugging process and the key lessons learned from the unusual incident. The talk covers monitoring data model limits, using feature flags for safe rollouts, and enhancing application resilience to avoid future recurrence.


### [How we scaled engineering enablement and infrastructure at Intercom - The Intercom Blog](https://yomu.fyi/post/how-we-scaled-engineering-enablement-and-infrastructure-at-intercom-th.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Problem & solution

Intercom’s engineering enablement team transformed the company from a patchwork of legacy systems and recurring incidents into a stable infrastructure that empowers fast-moving product teams. The company learned that selecting core technologies is not enough without a clearly defined strategy for understanding, guiding their use, and investing in the teams behind them, as lacking this leads to persistent friction. They defined a dedicated core technology team, learned and standardized their tooling, and implemented approaches to hire and grow engineers who own the infrastructure. These efforts reduced operational friction and incident frequency, allowing the business to move more confidently. As a result, product teams run faster and the infrastructure is now a reliable foundation for growth.


### [Intercom on Product: How we became an AI-first company - The Intercom Blog](https://yomu.fyi/post/intercom-on-product-how-we-became-an-ai-first-company-the-intercom-blo.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Explainer

Intercom’s Chief Product Officer and Co-founder discuss how generative AI reshaped their strategy, product development, and internal rituals. They describe moving from isolated AI tasks to AI-native products built from the ground up with AI at their core. A key move was launching Fin, their AI agent, as a standalone product on competitor platforms like Zendesk, prioritizing AI leadership over platform exclusivity. They draw parallels to Facebook’s mobile pivot and the iPhone’s initial skepticism, arguing generative AI will face similar resistance but have profound disruptive potential. The conversation emphasizes that second- and third-order effects of AI will create entirely new workflows and behaviors, making full impact hard to predict.


### [Start Good Trouble: Mastering SaaS metrics with Equals' Bobby Pinero - The Intercom Blog](https://yomu.fyi/post/start-good-trouble-mastering-saas-metrics-with-equals-x27-bobby-pinero.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Explainer

Equals co-founder and CEO Bobby Pinero joined the Start Good Trouble webinar to discuss how SaaS metrics unlock business potential and tell a compelling story. He argued that spreadsheets remain central despite the explosion of new BI tools, because everything eventually ends up back in a spreadsheet connected to live data. Drawing on seven years as Intercom’s senior director of finance, where he scaled ARR from under $1 million to over $150 million, Pinero highlighted the complexity of early-stage metrics like CAC, LTV, and retention. Equals recently published The Guide to SaaS Metrics to help leaders understand, optimize, and report on key drivers, and Pinero emphasized the need to tailor metrics to the business model and start with the story. He also recommended writing consistently and authentically to clarify ideas and connect with audiences, and noted that horizontal products require narrowing down use cases to scale effectively.


### [This is getting real: Welcome to the AI revolution - The Intercom Blog](https://yomu.fyi/post/this-is-getting-real-welcome-to-the-ai-revolution-the-intercom-blog.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Explainer

The talk traces the tech industry’s journey from the late stages of SaaS in 2019, through pandemic virtual offices and NFTs, to the 2022 downturn and ChatGPT’s launch in November 2022. 2023 was a year of prototypes and ‘thin wrappers’ on ChatGPT, but also real learning about building with LLMs, including non-deterministic approaches. The author argues the AI transformation is now real, moving beyond superficial features to fundamentally rethinking products, exemplified by the shift from ‘Software as a Service’ to ‘Service as Software.’ The future of customer service includes proactive, personalized bots, video and voice bots, and the ability to analyze all conversations to deeply understand customers. The author cites Bloom’s 2 sigma effect as an example of AI’s potential in education and urges optimism, noting that learners will inherit the earth.


### [The Ticket: Stacy Sherman on how to design customer experiences that drive loyalty - The Intercom Blog](https://yomu.fyi/post/the-ticket-stacy-sherman-on-how-to-design-customer-experiences-that-dr.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Explainer

Customer expectations have never been higher, and the experience a business delivers can determine whether it wins or loses customers. Stacy Sherman, a CX author and speaker, joined The Ticket podcast to discuss her Doing CX Right framework for designing standout customer experiences. She emphasizes that companies must move from merely planning to taking action, and that walking in customers’ shoes to get the basics right is essential. Sherman advises validating every approach with real customers and ensuring internal teams feel valued to create a culture of customer excellence. She also recommends mapping the customer journey to identify where AI can enhance interactions and where the human touch should be preserved.


### [The Ticket: Fueling The AI machine with the knowledge it needs](https://yomu.fyi/post/the-ticket-fueling-the-ai-machine-with-the-knowledge-it-needs.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Problem & solution

The performance of an AI-driven customer support engine depends directly on the quality of the knowledge that feeds it, as accurate, up-to-date content is critical for giving customers instant and trustworthy answers. Investing time and care into help content can significantly boost automated resolution rates, as Intercom has experienced firsthand. Many busy support teams struggle to prioritize maintaining their help centers due to limited resources, but filling content gaps and updating content after launching new products is essential for AI success. Knowledge content compounds in value over time; Intercom’s transition from its Resolution Bot to the Fin AI chatbot resulted in resolution rates skyrocketing from the start. Knowledge management should be cultivated as a company-wide responsibility, with input from product, engineering, sales, and marketing teams, and in the near future, internal knowledge will also be fed to AI to help agents answer complex queries.


### [Intercom on Product: The evolution of product management in the age of AI - The Intercom Blog](https://yomu.fyi/post/intercom-on-product-the-evolution-of-product-management-in-the-age-of.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Published: Oct 5, 2026
- Type: Explainer

Product management is at a critical juncture as generative AI reshapes how products are conceived, built, and used. Indiscriminately adding AI is risky; product managers must ensure the technology solves real user problems rather than being an end in itself. Curiosity is essential for driving exploration of generative AI’s new possibilities. A foundational understanding of AI is important, but the ability to collaborate with AI and ML experts is even more critical for bridging technical possibilities with customer needs. The future of product management will be shaped by those willing to learn, adapt, and explore the art of the possible.


[Newer posts](https://yomu.fyi/posts/page/21.md) · [Older posts](https://yomu.fyi/posts/page/23.md)