---
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

### [Post-Train NVIDIA Cosmos 3 in One Day Using Agent Skills](https://yomu.fyi/post/post-train-nvidia-cosmos-3-in-one-day-using-agent-skills.md)
- Company: [NVIDIA](https://yomu.fyi/company/nvidia-developer-blog.md)
- Author: Tanya Lenz
- Published: Jul 14, 2026
- Type: Tutorial

Adapting vision reasoning models for specialized physical AI video tasks often demands days of manual container configuration, training script authoring, and hyperparameter tuning. NVIDIA Cosmos 3 Nano, an omnimodal mixture-of-transformers model, pairs an autoregressive Reasoner tower with an iterative diffusion Generator tower for video question answering. By integrating NVIDIA TAO agent skills with a coding agent like Codex, developers can automate data patching, evaluation, and Low-Rank Adaptation (LoRA) post-training. In experiments using the Woven Traffic Safety dataset, LoRA fine-tuning boosted zero-shot baseline accuracy from 54.41% to 87.14% while using approximately seven times fewer GPU hours than full-parameter supervised fine-tuning. Combining this agent workflow with TAO AutoML further elevated model accuracy to 93.35% before automated deployment via NVIDIA NIM.


### [Meet the first cohort of recipients shaping the future with the Uber Transit Innovation Fund](https://yomu.fyi/post/meet-the-first-cohort-of-recipients-shaping-the-future-with-the-uber-t.md)
- Company: [Uber](https://yomu.fyi/company/uber.md)
- Author: Valley Transit Authority (Santa Clara County, CA)
- Published: Jul 14, 2026
- Type: Announcement

The Uber Transit Innovation Fund will provide up to $50,000 each to 20 US public transit agencies, municipalities, and regional authorities to pilot on-demand mobility programs, with $1 million available overall. Its first announced cohort includes agencies and authorities from San Antonio, Volusia County, Polk County, Belton, Monterey, South Bend, the Quad Cities, and San Juan. Proposed projects cover late-night overflow rides, microtransit and paratransit supplementation, airport connections, curb-to-curb service, modernization of taxi vouchers, subsidized rides for opioid-use-disorder treatment, food-access mobility, and first-mile/last-mile trips to 16 rail stations. Applications remain open through June 30, 2026, with proposals reviewed on a rolling basis until funds are fully allocated.


### [How Retail Finance teams are using Agentic AI to protect omni-channel margins](https://yomu.fyi/post/how-retail-finance-teams-are-using-agentic-ai-to-protect-omni-channel.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Sarah Duffy
- Published: Jul 14, 2026
- Type: Explainer

Omni-channel retail has spread margin, cash, and markdown decisions across more channels, fulfillment paths, and return routes, while agentic systems increase the speed and complexity of change. The post presents ontology as a way to preserve the meaning and business context behind finance figures, keeping definitions, channels, and cost drivers current. Databricks Genie is described as a data-smart AI coworker that answers finance questions in plain language, grounding responses in an evolving ontology, source traces, permissions, and governed AI costs. It focuses on margin after fulfillment and returns, inventory cash tied up in the wrong place, and full-price revenue at risk from markdowns and returns, then prepares actions for a person to approve. Unilever deployed Genie to more than 1,200 finance and business users; analysis that took days now takes minutes, with expected multi-million-euro annual cost avoidance.


### [How we configure huge pages in ClickHouse Managed Postgres](https://yomu.fyi/post/how-we-configure-huge-pages-in-clickhouse-managed-postgres.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jul 14, 2026
- Type: Tutorial

ClickHouse Managed Postgres configures Linux huge pages to reduce the per-connection page-table cost and translation overhead of a large PostgreSQL shared\_buffers cache. The configuration reserves a quarter of machine memory before PostgreSQL starts, verifies HugePages\_Total, sets huge\_pages = 'on' to prevent silent fallback, and sizes shared\_buffers against the complete shared-memory segment, including buffer descriptors, WAL buffers, and lock tables. On an r7i.4xlarge with 32GB shared\_buffers, 4KB pages added 31.1MB of page tables per connection and reached 6.12GB at 200 connections, while 2MB huge pages reached 111MB. A select-only pgbench test at 100 clients also rose from 373,083 TPS to 418,087 TPS, a 12% increase, while startup failure without a sufficient pool made misconfiguration explicit.


### [Doing the right thing when things go wrong](https://yomu.fyi/post/doing-the-right-thing-when-things-go-wrong.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Mark Gorman
- Published: Jul 14, 2026
- Type: Explainer

Fin’s incident-management process is designed to reduce customer impact quickly when deployments, alarms, or customer reports indicate a disruption. It combines customer and product signals, including heartbeat metrics for workflows such as Fin’s response generation, with engineer monitoring of rollouts; a rollback can land in a little under two minutes. Responses run through incident.io and Slack, with defined engineering lead, incident commander, business lead, and resolution owner roles, plus the out-of-hours STRIKE responder group. The lifecycle covers triage, investigation, mitigation, and learning, with a stated preference for rolling back to a known state before fixing forward and with explicit alternatives when rollback is unavailable. After recovery, bounded follow-ups and incident reviews aim to improve recurrence prevention, blast-radius reduction, detection, and response, while early escalation and clear communication make the process repeatable rather than dependent on heroics.


### [Foundational context: Cross-industry & function-specific accelerators for Lakebase](https://yomu.fyi/post/foundational-context-cross-industry-function-specific-accelerators-for.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Amit Singh
- Published: Jul 14, 2026
- Type: Announcement

Databricks presents Lakebase as a fully managed, serverless, standard Postgres database for combining operational and analytical workloads on its Data + AI Platform. The platform separates compute from storage, integrates with the lakehouse through Synced Tables and Lakebase CDF, and uses Unity Catalog for governance; copy-on-write branching and autoscaling to zero are described as core infrastructure primitives. The post showcases partner-built, ready-to-deploy accelerators spanning technology, finance, marketing, sales, supply chain, human resources, customer service, and operations. Examples include PostgreSQL migration assessment, multi-agent Genie orchestration, stateful enterprise agents, autonomous data reliability, governed contact-center intelligence, and project operations management. These offerings package Lakebase patterns into migration controls, domain-specific solutions, and agent frameworks intended to accelerate modernization and reduce transformation complexity.


### [Blocking Slow-Burn Attacks: Contextual Policies in Omnigent](https://yomu.fyi/post/blocking-slow-burn-attacks-contextual-policies-in-omnigent.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Nishith Sinha, Matei Zaharia
- Published: Jul 14, 2026
- Type: Problem & solution

Omnigent’s post examines how a vendor-review assistant can leak confidential pricing terms when an attacker hides an indirect prompt injection in a shared runbook. Because the malicious workflow is divided into ordinary actions, stateless checks approve each step even though the session as a whole is unsafe. The demonstration compares an unprotected run, which sends the summary externally, with a contextual policy that stores a running risk score, adds 30 for each document read, and denies email after the score exceeds 50. It also shows that agents cannot remove or disable policies, new policies require human approval, and any denial prevails when policies are combined. Runtime enforcement therefore preserves the block even when the agent has been misled.


### [Systems Engineering Playbook: Optimizing Qwen 3.5-397B MoE on Ironwood (TPU7x)](https://yomu.fyi/post/systems-engineering-playbook-optimizing-qwen-3-5-397b-moe-on-ironwood.md)
- Company: [Google](https://yomu.fyi/company/google.md)
- Author: Google for Developers
- Published: Jul 14, 2026
- Type: Benchmark

Serving Qwen3.5-397B, a 397-billion-parameter sparse Mixture-of-Experts model, on Ironwood (TPU v7x) requires fitting roughly 400 GB of weights into HBM while sustaining utilization across contrasting workloads. The report applies a modular, model-agnostic playbook built from reusable JAX/Pallas kernels and hardware-aware cost models, focusing new work on Gated DeltaNet linear attention and Attention Data Parallelism while integrating changes into vLLM and SGLang. The architecture activates exactly 17 billion parameters per token and combines 15 repeating blocks of three GDN layers and one GQA layer. Benchmarks use a single host with four Ironwood chips, eight logical devices, 8K/1K prefill-heavy and 1K/8K decode-heavy workloads, and concurrency tiers from 64 to 512. Between April and June 2026, stated optimizations improved inference performance by approximately 4.7x for 512-concurrency prefill-heavy workloads and 3.1x for decode-heavy workloads.


### [Inside Shopify Hack Days: Building a prototype for music-playing pages](https://yomu.fyi/post/inside-shopify-hack-days-building-a-prototype-for-music-playing-pages.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jul 14, 2026
- Type: Explainer

During Shopify Hack Days 39, a 13-person team addressed why artists selling music on Shopify product pages lacked a built-in way to hear digital albums before buying. The team pursued two paths in parallel: a first-class Audio media type across Core, Admin API, admin-web, and storefront, and a standalone Shop Sounds app for release management. The app orchestrated product and variant creation, audio and artwork metafields, storefront access, and Online Store publication, while a theme extension provided track-level purchasing and a shared audio instance that continued across navigation. It also included six GLSL fragment shaders driven by bass, mid-range, treble, and overall energy, plus synced lyrics and a geolocated tour dates block. After three days, the team had a working prototype, but Shop Sounds was not a live product; the project demonstrated that native audio support and Shopify metaobjects and metafields could support a music toolkit without custom infrastructure.


### [Training Orchestrator: Unifying Model Training at Yelp](https://yomu.fyi/post/training-orchestrator-unifying-model-training-at-yelp.md)
- Company: [Yelp](https://yomu.fyi/company/yelp.md)
- Author: Ying Wang and Nathan Sponberg, Software Engineer
- Published: Jul 14, 2026
- Type: Problem & solution

Yelp developed Training Orchestrator to standardize machine learning pipeline execution and eliminate divergent training scripts across its applied engineering teams. Previously, monolithic Spark scripts coupled training logic directly to cluster runtimes, preventing local testing, slowing debug cycles, and causing inconsistent configuration drift across projects. The new framework introduces a declarative configuration layer backed by Pydantic models, enabling static type checking and step schema validation before runtime execution starts. Training workflows are defined as modular step hierarchies that the orchestration engine compiles into directed acyclic graphs for execution in topological order. By injecting Spark and MLflow contexts into steps, the architecture ensures reproducible tracking, automated Slack alerts, and parity across local development and production environments.


### [Building Service Topology at Scale: Architecture, Challenges, and Lessons Learned](https://yomu.fyi/post/building-service-topology-at-scale-architecture-challenges-and-lessons.md)
- Company: [Netflix](https://yomu.fyi/company/netflix.md)
- Author: Netflix Technology Blog
- Published: Jul 13, 2026
- Type: Problem & solution

Engineers at Netflix required a unified, real-time view of service dependencies to navigate distributed architecture and improve incident troubleshooting. Traditional batch systems introduced stale data, so the team created a streaming-first platform backed by reactive streams and backpressure handling to ingest flow records from multi-region Kafka streams and Server-Sent Events without data loss. The architecture partitions data into physically separate graph and columnar storage layers covering eBPF network flows, IPC metrics, and distributed traces. Network flow ingestion relies on a three-stage distributed aggregation pipeline using consistent hashing to resolve network intermediaries into logical application connections. The resulting production system serves time-travel and topology queries with sub-second latency while continuously updating dependency views.


### [NVIDIA Ising Decoding Cuts Color Code Logical Error Rates by Over 300x](https://yomu.fyi/post/nvidia-ising-decoding-cuts-color-code-logical-error-rates-by-over-300x.md)
- Company: [NVIDIA](https://yomu.fyi/company/nvidia-developer-blog.md)
- Author: Elizabeth Goodman
- Published: Jul 13, 2026
- Type: Announcement

Fault-tolerant quantum computing requires effective quantum error correction, but color codes have historically been constrained by difficult decoding demands. NVIDIA introduced the Ising Decoder ColorCode 1 Fast, a pre-decoder designed to accelerate and improve color code logical error rates. The framework uses a 3D Convolutional Neural Network trained via cuStabilizer in NVIDIA cuQuantum alongside PyTorch to handle localized error syndromes. In benchmark testing at code distance d=31 with a 0.3% physical error rate, the decoder achieved over 347.7x lower logical error rates and 7.3x faster runtime compared to the Chromobius decoder. These local, space-time predictions scale to arbitrary distances, supporting parallel blockwise decoding for real-time quantum algorithm execution.


### [Ultra-Fast Anomaly Detection using Apache Spark Real-Time Mode](https://yomu.fyi/post/ultra-fast-anomaly-detection-using-apache-spark-real-time-mode.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Jitesh Soni
- Published: Jul 13, 2026
- Type: Benchmark

The post presents a reusable real-time guardrail pattern for flagging suspicious Ethereum blockchain transactions and routing them for downstream action. Its rules identify impossible blocks where gas\_used exceeds gas\_limit and scan extra\_data for email addresses, JWT tokens, or AWS access-key patterns, producing ALLOW or QUARANTINE decisions with reasons. The implementation uses Apache Spark Structured Streaming Real-Time Mode, whose continuous data flow, pipeline scheduling, streaming shuffle, pre-allocated execution pipelines, and asynchronous checkpointing target millisecond latency without a separate streaming engine. On a four-worker DBR 16.4 LTS cluster, the stateless Kafka-to-Kafka test processed about 23 million records at 69,713 rows per second, with P95 below 0.5 milliseconds and P99 at 1 millisecond. The post notes that RTM with a Kafka sink provides at-least-once delivery and that more complex stateful workloads may incur higher latency.


### [Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler](https://yomu.fyi/post/modernizing-the-meta-ads-service-with-an-open-source-kernel-scheduler.md)
- Company: [Meta](https://yomu.fyi/company/meta.md)
- Published: Jul 13, 2026
- Type: Problem & solution

Meta’s ads serving fleet processes more than 5 million requests per second, so millisecond-scale latency changes can affect ads relevance and advertiser ROI. During a move from kernel 6.4 with CFS to kernel 6.9, the team observed a latency regression associated with EEVDF and used sched\_ext, an upstream BPF-based framework, to encode ads-specific scheduling priorities. The policy soft-partitions CPUs between latency-critical request-path threads and less-sensitive work, adjusts pool sizes with load-based heuristics, and runs as a user-space binary that loads BPF, enabling policy changes without rebuilding or reinstalling the kernel. Initial results were a 28% reduction in ads retrieval p99 latency, 3.28 megawatts of fleet power savings, and a 1.1% increase in weighted ads ranked; two later user-space updates delivered an additional 60% p99 reduction and an 18% decrease in critical-path timeout errors, with iterations shipping in days rather than months.


### [Claude for Creative Work](https://yomu.fyi/post/claude-for-creative-work.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Jul 13, 2026
- Type: Announcement

Claude for Creative Work describes a set of connectors and workflows intended to help creative professionals expand ideation, reduce repetitive work, and take on larger-scale projects. The connectors connect Claude with tools including Ableton, Adobe Creative Cloud, Affinity by Canva, Autodesk Fusion, Blender, Resolume, SketchUp, and Splice, supporting documentation access, asset production, 3D modeling, live visual control, and sample search. The described uses also include tutoring, Claude Code scripts and plugins, cross-application pipeline work, Claude Design exploration with export to Canva, and batch processing. Blender has an officially available MCP connector that can analyze and debug scenes, batch-apply object changes, and add tools through Blender’s Python API; because it uses MCP, it is accessible to other LLMs. The post also describes access for students and faculty in three art and design programs, whose feedback will inform understanding of creative practitioners’ needs.


### [Anthropic Sydney office](https://yomu.fyi/post/anthropic-sydney-office.md)
- Company: [Anthropic](https://yomu.fyi/company/anthropic.md)
- Published: Jul 13, 2026
- Type: Announcement

Anthropic has officially opened a Sydney office and appointed Theo Hourmouzis as General Manager for Australia and New Zealand. Hourmouzis brings more than 20 years of technology leadership experience across Asia Pacific and most recently served as Snowflake’s Senior Vice President for Australia, New Zealand and ASEAN. He will lead the growing local team, shape a regional strategy for customers, and bring Claude into important work. The team will deepen relationships with enterprise customers and AI for Science research partners while delivering on commitments in a memorandum of understanding with the Australian government. Local partnerships include Canva, Xero, and YMCA South Australia, where custom Claude AI skills turn operational data into actionable insights, reduce branded content production from hours to minutes, and bring previously outsourced technical work in-house.


### [Extreme Event Likelihoods with Guided Generative Models](https://yomu.fyi/post/extreme-event-likelihoods-with-guided-generative-models.md)
- Company: [NVIDIA](https://yomu.fyi/company/nvidia-developer-blog.md)
- Author: Elizabeth Goodman
- Published: Jul 13, 2026
- Type: Explainer

Estimating the likelihood of extreme, high-impact events using brute-force Monte Carlo simulations requires excessive model iterations for expensive physics-based climate models. While guided diffusion models steer generation toward rare events like tropical cyclones, oversampling distorts the true probability distribution. To address this, researchers guide the diffusion-based climate emulator NVIDIA cBottle toward specific events and compute log-odds ratios between guided and unguided distributions. Reweighting the guided samples via these odds ratios enables importance sampling under the original climate distribution. Implemented in NVIDIA Earth2Studio, this technique reduced standard error by 25% compared to simple Monte Carlo sampling when evaluating tropical cyclone states.


### [How Insider One uses ClickHouse Cloud to power real-time customer engagement at scale](https://yomu.fyi/post/how-insider-one-uses-clickhouse-cloud-to-power-real-time-customer-enga.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jul 13, 2026
- Type: Problem & solution

Insider One’s Unified Customer Database (UCD) unifies event data, user attributes, identity resolution, and profiles across channels to support real-time segmentation, personalization, and analytics. The platform initially ran ClickHouse in a self-managed AWS deployment, but growth brought larger datasets, more concurrent queries, and increasing work tuning clusters and balancing performance against cost. In a proof of concept, the team migrated an anonymized dataset from one of its largest customers to ClickHouse Cloud and replayed UI segmentation, audience-count, and scheduled-campaign workloads. Average query latency fell 50–60% without significant changes, reaching 70–75% for the largest customers, while latency percentiles became more predictable; the managed service also reduced operational burden and gave the team more capacity for product development and its AI-oriented roadmap.


### [Practical Guide To Python App Hosting](https://yomu.fyi/post/practical-guide-to-python-app-hosting.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Jul 13, 2026
- Type: Explainer

Python app hosting is presented as both an infrastructure choice and, for data-intensive or AI applications, a data-architecture choice. The guide defines a hosting stack comprising application code, runtime, dependency manager, application server and reverse proxy, and contrasts it with traditional web hosting. It compares shared hosting, VPSs and cloud VMs, PaaS, container platforms and serverless functions by control, operational effort, scalability and workload fit. It notes that long-running data and AI tasks such as model training, vector indexes, cached datasets, ETL jobs and lengthy inference pipelines can exceed practical serverless limits. The conclusion is that public APIs and lightweight web apps allow broad platform choice, while apps accessing governed data, model endpoints or AI agents should be evaluated by where data lives and how access is governed, with Databricks Apps presented as an option when data already resides in a lakehouse.


### [How to Evaluate General-Purpose Robot Policies for Real-World Deployment](https://yomu.fyi/post/how-to-evaluate-general-purpose-robot-policies-for-real-world-deployme.md)
- Company: [NVIDIA](https://yomu.fyi/company/nvidia-developer-blog.md)
- Author: Brad Nemire
- Published: Jul 12, 2026
- Type: Problem & solution

Evaluating robotics foundation models accurately in simulation remains challenging due to visual domain overlap, benchmark saturation, diagnostic gaps, and small sample sizes. RoboLab addresses these deficiencies by providing a robot-agnostic simulation platform that supports rapid task creation and diagnostic evaluation suites. Tasks in RoboLab can be compiled across varying robot embodiments and target visual, procedural, and relational competencies. Statistical analysis using the Clopper-Pearson method reveals that narrowing the confidence interval around a 90 percent success rate from ten to two percentage points demands increasing rollouts from 70 to 1,030. Developed by NVIDIA Research, RoboLab powers the open-source Isaac Lab-Arena simulation framework to establish scalable evaluation for real-world robotic policies.


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