Total Articles: 20 from 7 sources
AWS News
1. Get started with OpenAI GPT-5.5, GPT-5.4 models, and Codex on Amazon Bedrock
Published: 2026-06-01 21:33
Summary:
OpenAI frontier models GPT-5.5 and GPT-5.4, and Codex, the OpenAI coding agent, are now generally available on Amazon Bedrock Deploy frontier models on Bedrock’s high performance inference engine with built-in security, governance, and pay-per-token pricing.
2. AWS Weekly Roundup: Claude Opus 4.8 on AWS, Aurora MySQL with Kiro Powers, and more (June 1, 2026)
Published: 2026-06-01 14:25
Summary:
In my last Week in Review post, I shared what I’d been hearing from customers in the AI-Driven Development Lifecycle (AI-DLC) workshops I’ve been delivering Last week I was back at it, this time in Denver for a two-day AI-DLC workshop, where I helped facilitate 17 teams to deliver nearly 20 separate use cases in […]
3. Introducing the next generation of AWS Resilience Hub for generative AI-based SRE resilience journey
Published: 2026-05-28 19:29
Summary:
AWS launches the next generation of AWS Resilience Hub with a significantly expanded experience that brings together a new application model, dependency discovery assessment, generative AI-powered failure mode analysis, modular resilience policies, and organization-wide reporting.
Dropbox Engineering
1. Beyond code generation: rethinking engineering productivity in the age of AI agents
Published: 2026-05-28 18:00
Summary:
How Dropbox is moving from AI tools that assist engineers to agentic systems that can execute scoped tasks, and how we’re building platforms to support those workflows.
2. Introducing Nova, our internal platform for coding agents
URL: https://dropbox.tech/machine-learning/introducing-nova-our-internal-platform-for-coding-agents
Published: 2026-05-21 16:00
Summary:
Nova lets engineers run multiple coding sessions in parallel and lets internal systems use AI agents as part of automated workflows.
GitHub Blog
1. Still a developer. Just outside. Our latest GitHub Shop collection is here.
Published: 2026-05-28 18:18
Summary:
The ESC collection lets you escape the confines of your desk and get out into the sun where good ideas are bound to happen The post Still a developer Our latest GitHub Shop collection is here. appeared first on The GitHub Blog.
2. GitHub for Beginners: Getting started with Git and GitHub in VS Code
Published: 2026-05-25 16:00
Summary:
Discover how to use VS Code to interact with GitHub and maintain your projects The post GitHub for Beginners: Getting started with Git and GitHub in VS Code appeared first on The GitHub Blog.
3. GitHub recognized as a Leader in the Gartner® Magic Quadrant™ for Enterprise AI Coding Agents for the third year in a row
Published: 2026-05-22 16:10
Summary:
We are committed to empowering every developer by building an open, secure, and AI-powered platform that defines the future of software development The post GitHub recognized as a Leader in the Gartner® Magic Quadrant™ for Enterprise AI Coding Agents for the third year in a row appeared first on The GitHub Blog.
Google Developers
1. Agents CLI in Agent Platform: create to production in one CLI
URL: https://developers.googleblog.com/agents-cli-in-agent-platform-create-to-production-in-one-cli/
Published: 2026-06-02 12:38
Summary:
Google Cloud has introduced the Agents CLI, a specialized tool designed to bridge the gap between local development and production-grade AI agent deployment The CLI provides coding assistants with machine-readable access to the full Google Cloud stack, reducing context overload and token waste during the scaffolding process By streamlining evaluation, infrastructure provisioning, and deployment into a single programmatic backbone, the tool enables developers to move from initial concept to a live service in hours rather than weeks.
2. Building real-world on-device AI with LiteRT and NPU
URL: https://developers.googleblog.com/building-real-world-on-device-ai-with-litert-and-npu/
Published: 2026-06-02 12:38
Summary:
LiteRT is a production-ready framework designed to help mobile developers unlock the power of Neural Processing Units (NPUs), overcoming the performance and battery limitations of traditional CPU or GPU processing By providing a unified API that abstracts away hardware complexities, it allows industry leaders like Google Meet and Epic Games to deploy sophisticated AI models for real-time video, animation, and speech recognition with significantly higher efficiency The platform further supports developers through benchmarking tools and cross-platform compatibility, enabling seamless AI deployment across mobile devices, AI PCs, and industrial IoT hardware.
3. Speeding Up AI: Bringing Google Colossus to PyTorch via GCSFS and Rapid Bucket
Published: 2026-06-02 12:38
Summary:
Google Cloud has introduced a high-performance integration that connects Rapid Storage directly to PyTorch via the fsspec interface to eliminate AI training bottlenecks By utilizing Google’s Colossus architecture and bidirectional gRPC streaming, the solution offers up to 15 TiB/s aggregate throughput and significant reductions in latency These improvements allow developers to speed up total training time by 23% with zero code changes required beyond updating the storage bucket type.
Meta Engineering
1. SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems
Published: 2026-05-26 16:00
Summary:
We’re introducing SilverTorch, a reimagining of recommendation systems that unifies all retrieval components for user generated content under a unified architecture Our research paper, “SilverTorch: A […] Read More The post SilverTorch: Index as Model — A New Retrieval Paradigm for Recommendation Systems appeared first on Engineering at Meta.
2. Reel Friends: Building Social Discovery that Scales to Billions
Published: 2026-05-13 13:00
Summary:
It highlights Reels your friends have watched and reacted to But sometimes the features that seem the most straightforward require the deepest engineering work The post Reel Friends: Building Social Discovery that Scales to Billions appeared first on Engineering at Meta.
3. Migrating Data Ingestion Systems at Meta Scale
Published: 2026-05-12 16:00
Summary:
Meta’s data ingestion system, which our engineering teams leverage for up-to-date snapshots of the social graph, has recently undergone a significant revamp to enhance its reliability at scale Moving from our legacy system to our new architecture required a large-scale migration of our entire data ingestion system The post Migrating Data Ingestion Systems at Meta Scale appeared first on Engineering at Meta.
Netflix TechBlog
1. High-Throughput Graph Abstraction at Netflix: Part I
Published: 2026-05-29 18:49
Summary:
Looking ahead, we plan to leverage the graph schema for additional improvements, such as:Minimizing Query Fanout: By using edge cardinality within edge mappings, we aim to select the most efficient traversal paths and minimize query fanout.Improved Developer Experience: The schema will support generating a type-safe data access layer and enhance the Gremlin-like API with schema awareness.Next, let’s look at how this data is organized in a real-time index within the KV Abstraction.Real-Time Index: Key-Value StorageBefore we discuss how the data is organized into graph indexes, let’s discuss how KV organizes data within namespaces and provides idempotency guarantees:Data partitioning: A namespace is associated with a table in the underlying storage layer In order to ensure optimal performance without exerting too much memory pressure, we aim to limit the number of edges per source node within the system.Next, let’s explore the caching strategies used by the Abstraction.Caching Strategies in Graph AbstractionAlthough the Graph Abstraction already provides efficient reads and writes to durable storage, caching remains critical for the stability and performance of any graph datastore for two key reasons:Write amplification: A single write on the fronting service can result in multiple writes to the backing durable storage due to the use of multiple indexes As illustrated in the diagram below, both the caching layer and durable storage replicate data asynchronously across regions, resulting in an eventually consistent system.Now that we’ve covered storing the real-time graph index, let’s see how it enables graph traversals.Graph TraversalsThe Abstraction provides a custom gRPC traversal API, inspired by Gremlin, which enables exploration of the distributed graph by letting users chain traversals, apply filter criteria, sort results, limit results, and more.Let’s explore a hypothetical scenario where the Abstraction is used to recommend shows to users on a shared device, by considering the duration of the most recent viewing session for each show across all profiles and accounts associated with that device:TraversalRequest.newBuilder() .setNamespace("
2. From Silos to Service Topology: Why Netflix Built a Real-Time Service Map
Published: 2026-05-29 14:01
Summary:
We needed to combine multiple sources.These lessons shaped every decision we made in building Service Topology.What We Needed: A Living MapWe set out to build something specific: a living map of our infrastructure — one that updates in real-time as services deploy, as traffic patterns shift, as new dependencies form and old ones disappear.The requirements were clear:Real-time updates, not stale snapshots: In an environment where services deploy continuously, yesterday’s topology map is archaeology, not observability.Fast queries at scale: When an engineer is troubleshooting at 3am, they can’t wait minutes for a query to return This graduated approach also prevents hot spots by distributing load across multiple points even when specific applications or network intermediaries see 100x more traffic than others.Graph Storage: We persist the topology in Netflix’s graph database, an abstraction layer built on top of our distributed key-value storage infrastructure Each of our three data sources (network flows, IPC metrics, tracing) creates a separate graph that can be queried independently or merged.gRPC API: We expose the topology through a gRPC service that supports multi-hop traversal, filtering by availability tier and business domain, pagination for large result sets, and sub-second query response times.The technical details of building this at Netflix scale — handling Kafka lag, managing memory and garbage collection, optimizing distributed processing, debugging reactive streams — deserve their own discussion
3. Scaling ArchUnit with Nebula ArchRules
Published: 2026-05-08 15:55
Summary:
The archRules will contain rules specific to the usage of that library That is because the ArchRules Runner Plugin will be able to automatically detect these rules and run them in only the source sets that use this library as a dependency In the following example, we have a Project which uses a test helper library as a testImplementation dependency, and also adds a standalone rules library to the archRules configuration
Stripe Engineering
1. Solo founding is at an all-time high: Top performers have these traits in common
URL: https://stripe.com/blog/top-solo-founder-traits
Published: 2026-05-28 00:00
Summary:
In 2025, solo founders in the top decile generated 61 times the revenue of the median solo founder in their first six months We analyzed the data to understand what drives that gap.
2. Expanding Stripe Radar to protect more of your business
URL: https://stripe.com/blog/expanding-stripe-radar-to-protect-more-of-your-business
Published: 2026-05-27 00:00
Summary:
Radar now blocks high-risk transactions across all supported payment methods; defends against new fraud types like multi-account abuse and pay-as-you-go abuse, regardless of which payment processor you use; and gives platforms new tools to evaluate and mitigate merchant risk on and off Stripe.
3. Five vertical SaaS insights from Sessions 2026
URL: https://stripe.com/blog/vertical-saas-insights-sessions-2026
Published: 2026-05-11 00:00
Summary:
AI is forcing platforms to expand beyond pure software See how vertical SaaS platforms are using payments, financial services, and agentic commerce to build more durable businesses.
Generated on 2026-06-02 12:38:52