Why it matters: This article details how Meta built and scaled a massive LLM-inspired foundation model for ads, showcasing innovations in architecture, training, and knowledge transfer for significant performance gains. It offers insights into building large-scale recommendation systems.
- •Meta's Generative Ads Model (GEM) is a new LLM-inspired foundation model enhancing ad recommendation performance and advertiser ROI.
- •Its novel architecture allows efficient scaling and precise predictions, leveraging thousands of GPUs for training.
- •GEM propagates learnings across Meta's ad model fleet through advanced post-training and knowledge transfer techniques.
- •It has already delivered significant increases in ad conversions on Instagram (5%) and Facebook (3%).
- •GEM achieves 4x efficiency in performance gains, 2x knowledge transfer effectiveness, and a 23x increase in training FLOPS.
Why it matters: This enables Python developers to build robust, long-running, multi-step applications on Cloudflare Workflows, simplifying complex orchestrations for AI/ML, data pipelines, and task automation. It leverages Python's ecosystem and Cloudflare's durable execution.
- •Cloudflare Workflows now support Python, enabling developers to orchestrate long-running, multi-step applications using their preferred language, addressing previous TypeScript-only limitations.
- •This expands Cloudflare's Python support, building on earlier integrations like CPython and Pyodide packages in Workers.
- •Python Workflows are ideal for automating complex processes such as LLM training, data pipelines, and AI agent development, simplifying architecture and improving reliability.
- •The implementation leverages Cloudflare Workers' direct Python runtime support and Pyodide's Foreign Function Interface for seamless interoperability with JavaScript-based durable execution APIs.
- •Workflows provide built-in error handling, retry behavior, and state persistence, crucial for idempotent operations.
Why it matters: The developer workflow is rapidly evolving towards faster iteration and continuous delivery. Understanding these shifts in practices, tools like feature flags and CI/CD, and communication styles is crucial for engineers to remain effective and competitive.
- •Developer workflows are rapidly shifting towards continuous iteration, favoring smaller, more frequent commits over large, infrequent releases.
- •Modern software delivery heavily relies on feature flags for safely deploying incomplete work and automated CI/CD pipelines for testing, building, and deployment.
- •The industry is moving towards smaller, focused pull requests, which are easier and faster to review, thereby reducing mental overhead and risk.
- •Comprehensive automated testing, including unit, integration, and end-to-end tests, is becoming increasingly essential to maintain quality and momentum in accelerated development cycles.
- •Team communication and hiring practices are evolving to support faster shipping, emphasizing async updates, issue-based status, and clear communication skills.
Why it matters: This matters because it automates a complex, insecure, and time-consuming BYOIP onboarding process using RPKI, significantly improving routing security and operational efficiency for engineers managing IP address space in the cloud. It offers greater control and faster deployment.
- •Cloudflare introduced a self-serve BYOIP API, automating the 4-6 week manual process for customers to onboard IP prefixes.
- •The new system leverages Resource Public Key Infrastructure (RPKI) for robust routing security and automated ownership validation, replacing manual LOA reviews.
- •Self-serve generates LOAs on customers' behalf, ensuring route acceptance and enhancing security through RPKI ROA and IRR/rDNS checks.
- •Initial scope is limited to BYOIP prefixes from Cloudflare's AS 13335, utilizing widely available Route Origin Authorization (ROA) objects.
- •This advancement provides customers with greater control and configurability over their IP space, improving IP address management on Cloudflare's network.
Why it matters: This tool significantly boosts developer productivity by integrating AI directly into the terminal, reducing context switching and automating complex tasks. It empowers engineers to work faster and more efficiently within their preferred command-line environment.
- •GitHub Copilot CLI integrates AI capabilities directly into the command-line interface, enabling users to generate, explain, and execute commands without leaving the terminal.
- •It streamlines developer workflows by allowing natural language interaction to create scripts, refactor code, and manage environments, enhancing precision and control.
- •The CLI operates in both interactive and programmatic modes, consistently requiring user confirmation before modifying or executing files for enhanced safety.
- •Users can extend Copilot CLI's functionality by connecting to custom MCP servers, integrating domain-specific tools and contextual data for improved suggestions.
- •The tool aims to automate repetitive tasks, facilitate learning new tools, and significantly reduce context switching for developers who prefer working in the terminal.
Why it matters: Automating routine maintenance at scale reduces developer toil and technical debt. Spotify's success with 1,500+ merged PRs proves that AI agents can reliably handle complex code modifications, allowing engineers to focus on innovation rather than manual upkeep.
- •Spotify developed an AI-driven background coding agent to automate large-scale software maintenance tasks.
- •The agent has successfully merged over 1,500 pull requests, proving the scalability of AI-generated code changes.
- •It focuses on reducing developer toil by handling repetitive tasks like dependency updates and migrations.
- •The system operates autonomously to identify and resolve technical debt across a massive codebase.
- •This initiative shifts the engineering focus from routine upkeep to high-value feature development.
Why it matters: This update to Azure Ultra Disk offers significant latency reductions and cost optimization through granular control, crucial for engineers managing high-performance, mission-critical cloud applications.
- •Azure Ultra Disk has received a transformative update, enhancing speed, resilience, and cost efficiency for mission-critical workloads.
- •Platform enhancements deliver an 80% reduction in P99.9 and outlier latency, alongside a 30% improvement in average latency, making it ideal for I/O-intensive applications.
- •The new provisioning model offers greater granular control over capacity and performance, allowing for significant cost savings (up to 50% for small disks, 25% for large disks).
- •Key changes include 1 GiB capacity billing, increased maximum IOPS per GiB (1,000), and lower minimum IOPS/MB/s per disk.
- •Ultra Disk, combined with Azure Boost, now enables a new class of high-performance workloads, exemplified by the Mbv3 VM supporting up to 550,000 IOPS.
Why it matters: TypeScript's journey from a pragmatic fix to GitHub's most-used language underscores its value in building scalable, maintainable systems. Its type safety and tooling are now essential for modern frontend development and increasingly vital for reliable AI-assisted coding.
- •TypeScript, created by Anders Hejlsberg, addressed JavaScript's scalability challenges for large codebases by adding static typing and tooling.
- •It became GitHub's most-used language in 2025, demonstrating significant adoption and a 66% increase in contributors.
- •Its 'superpowers' of type safety, improved IDE support, and refactorability made it the default for major frontend frameworks.
- •The compiler was rewritten in Go, achieving a 10X performance boost while preserving functional compatibility.
- •TypeScript's open-source evolution on GitHub provides a transparent history of its development.
- •Its typed nature is crucial for the AI era, making AI-assisted coding more reliable and maintainable.
Why it matters: This article demonstrates how applying core software engineering principles like caching and parallelization to build systems can drastically improve developer experience and delivery speed, transforming slow pipelines into agile ones.
- •Slack reduced 60-minute build times for Quip and Slack Canvas backend by applying software engineering principles to their build pipeline.
- •They leveraged modern tooling like Bazel and modeled builds as directed acyclic graphs (DAGs) to identify optimization opportunities.
- •Key strategies included caching (doing less work) and parallelization (sharing the load) to improve build performance.
- •Effective caching relies on hermetic, idempotent units of work and granular cache keys for high hit rates.
- •Parallelization requires well-defined inputs/outputs and robust handling of work completion/failure across compute boundaries.
Why it matters: Engineers can now efficiently process video content for audio-specific tasks, saving significant computational resources and simplifying AI/ML and content moderation workflows. This streamlines development and reduces infrastructure costs.
- •Cloudflare Stream now enables efficient audio extraction from videos, reducing processing costs and complexity for audio-centric workflows.
- •This feature is crucial for AI/ML applications like transcription, translation, and speech recognition, as well as content moderation.
- •Audio can be extracted on-the-fly using Media Transformations by adding "mode=audio" to the URL, allowing for clipping specific sections.
- •Users can also download persistent M4A audio files directly from Stream-managed content.
- •A Workers AI example demonstrates transcribing audio with Whisper and translating it with M2M100.
- •The implementation involved extending Cloudflare's existing Video-on-Demand (VOD) and On-the-Fly-Encoding (OTFE) pipelines.