Reading room.
Engineering blogs & AI research
A reading room from engineering teams and AI labs: titles, short feed excerpts, and links to the originals. For my own essays, explore the writing archive.
- 1359 articles tracked
- 37 sources
- Refresh scheduled daily
Sources
The next developer interface is ambient intelligence
AI, agents, voice, and physical controls are shifting software development from operating tools to expressing intent—and helping developers stay focused on building. The post The next developer interface is ambient intel…
Unblock agentic software delivery with governed code review
AI agents have changed how much code a team can produce in a day. Review queues haven’t kept up, and delivery stalls while changes wait for a closer look. The usual workarounds (reminders, reviewer rotations, assigning a…
Connect your agents to your software lifecycle with the GitLab MCP server
Agents are working across your team s software development lifecycle, but most still operate as separate tools, leaving the context, handoffs, and permissions for your team to stitch together. When your agents use APIs f…
Get every merge request in front of the right reviewer, faster
The code is written. Now who reviews it? The volume of code has never been greater, but delivery hasn’t kept pace. At Meta, code changes on internal platforms grew 220% year over year, while changes that reached users as…
GitLab Secrets Manager: Govern secrets like your code
Credentials often start in an engineer s local dev environments, then get copied into unscoped CI/CD variables to keep pipelines running. Stored there as a raw value rather than a reference to a scoped secret, a signing…
GitLab 19.5 released
Welcome FLUX.3 Image Klein in Diffusers
Granite Switch 4.1: Chat, Decisions, and Speech from One Endpoint
Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta
Apertus 1.5 Release Notes
Sapienz Receives ISSTA 2026 Impact Paper Award
Ke Mao, Mark Harman, and Yue Jia have been recognized with the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2026 Most Influential Paper Award for their 2016 research, “Sapienz: multi-objec…
How Meta Built Forum With AI-Native Engineering
Meta s newest app, Forum, is for anyone who wants to go deeper into the conversations in their Facebook groups. To build Forum, Meta engineers adopted a whole new way of working by bringing an AI agent into the developme…
2026 World Cup: Breaking Records, Spiky Charts and Reliability at Scale
Every four years, the World Cup becomes the largest planned stress test of our infrastructure. This year it also set an all-time record! There are a few moments throughout the year, like New Years Eve, that really let us…
Timestral: Mistral's time-series foundation models
Proof-based general-purpose computing with Magnetar
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains,…
NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning
Always-on agents are taking on longer, more complex enterprise workflows. A single request can involve reading a document, checking information across sources,...
Scale Agentic Coding Workflows with Meta’s Muse Spark Open on NVIDIA GB300 NVL72
Meta launches Muse Spark Open, a coding-optimized 816B mixture-of-experts (MoE) model with 42B active parameters and a 1M token context window. Trained on...
Sync real-time Stripe data to Postgres with Stripe Data Pipeline
Applications rely on current Stripe data to fulfill orders, update customer accounts, and manage access to paid features. Until now, developers have had to build and maintain custom integrations to keep application datab…
Preparing for the 2026 US midterms
Singapore office and government MOU
Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Models
Code-switching (CS), the alternation between languages within an utterance, is common in multilingual speech but underrepresented in pretraining corpora. Increasing CS coverage requires finding relevant utterances in lar…
The Design Space of Tri-Modal Masked Diffusion Models
Discrete diffusion models have emerged as strong alternatives to autoregressive language models, with recent work initializing and finetuning a base unimodal model for bi-modal generation. Diverging from previous approac…
Amazon S3 is now available on the Vercel Marketplace and v0 by Vercel
Amazon Simple Storage Service (Amazon S3), including Amazon S3 Tables and Amazon S3 Vectors, is natively available on the Vercel Marketplace and v0 by Vercel.
Inside Hyperdrive: How we solved a rare Hyperdrive MySQL caching bug
While adding MySQL support to Hyperdrive, we found a subtle protocol bug when caching query results. Here is how we tracked down a 0.001% rate error and made Hyperdrive MySQL generally available.
Yandex outage: Data shows that instead of going dark, malicious bots went on the move
When strikes hit Yandex data centers, many assumed Russian bot operations went dark. Cloudflare data reveals that while search crawling stopped, malicious bots simply migrated to other networks.
Scaling agent teams: reach the frontier at 30% of the cost
Google DeepMind and Singapore Government collaborate to build fine-tuned AI model for scam detection
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
From 2,500 requests to 24: Rebuilding star history without the stargazers
Our new repo star history API now provides trends without returning individual identities or requiring unbounded database work. These are the engineering tradeoffs we made. The post From 2,500 requests to 24: Rebuilding…
GitHub availability report: September 2026
In September, we experienced two incidents that resulted in degraded performance across GitHub services. The post GitHub availability report: September 2026 appeared first on The GitHub Blog .
Gemini 4 Argon on GitLab: Built for long-running agentic work
As AI models take on longer, multi-step work, the challenge is putting that power to use across the software lifecycle without adding risk or cost. Teams need to be able to move faster, within enterprise controls and gua…
HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost
Behind the Scenes: Evolving Netflix’s Ads Event Pipeline for Live — Part II
By Yogesh Nagarur Introduction In Part 1 of this series , we shared how Netflix built the Ads Event pipeline and approached it as a system design problem: replacing fragmented pipelines with a centralized collection, enr…
DataJunction as Netflix’s answer to the missing piece of the modern data stack
by Olek Gorajek , Samuel Redai , Yian Shang Intro Our Netflix journey from data to dashboards, particularly within the space of the experimentation platform, always presented a unique set of challenges. This blog post ai…
Integrating Netflix’s Foundation Model into Personalization applications
Authors: Divya Gadde , Ko-Jen Hsiao , Dhaval Patel and Moumita Bhattacharya The motivation for building the Netflix Foundation Model for personalization was laid out in this previous blog post. The Netflix homepage is po…
Measuring the Impact of Personalized Recommendations
By Kevin Zielnicki, Guy Aridor, Aurélien Bibaut, Allen Tran, Winston Chou, and Nathan Kallus Introduction Personalization is everywhere on the internet. It shapes the products we discover, the stories we read, the music…
Netflix Conductor: The Next Chapter
Netflix Conductor : The Next Chapter by Aravindan Ramkumar on behalf of the Conductor team Conductor is the workflow orchestration engine Netflix uses to stitch micro-services into reliable, observable business processes…
Netflix Stratum Media Processing: Automated Container Right-Sizing
By Violetta Pidvolotska and Naveen Mareddy Stratum is Netflix’s internal serverless media processing platform, shaped by over a decade of experience developing large-scale distributed systems. It powers a wide range of m…
Reliable GPU compute for large training & inference jobs
How we detect failing GPUs and network fabric, remediate machines automatically, and let long-running jobs survive hardware loss. Authors: Nick Rutigliano , Argha C , Samartha Chandrashekar Open Netflix, and the home scr…
Running Apache Spark experiments in my sleep (and on a plane)
By Prashanth Gedde Narayanaswamy As one of Netflix’s largest and critical data pipelines, member-sessionizer consolidates tens of billions of hourly client events, encompassing user taps, playbacks, and engagement signal…
The Lifecycle of LLM-as-a-Judge: Building, Aligning, and Monitoring at scale
By Emma Yanyang Kong , JJ Tan , Ishan Gupta , Lars Olds , Claire Campbell , David Fagnan , Ratna Kavuri , Rohan Gosain , Veli Balin , Minsu Jang , Louis Garcia Introduction Any team generating text with an LLM at scale h…
TimeSeries Tiered Storage Journey: Kafka/Flink Streams to Native Cassandra Cold Reads
By Oleksii Tkachuk , Rajiv Shringi , Chris Lohfink , Abe Ratnofsky , Kartik Sathyanarayanan Introduction In an earlier post , we introduced the TimeSeries Abstraction, our high-throughput, low-latency platform designed t…
Optimizing Agent Reliability and Tool Calling Efficiency for Chip Design Using NVIDIA NeMo Gym
AI agents offer remarkable productivity gains in complex chip design workflows, but their tendency to generate plausible yet incorrect artifacts makes...
CASTLE: training natural language search before the first real query
How we addressed the cold-start problem for Airbnb’s natural language search by jointly generating synthetic training data — queries and relevance labels — from de-identified booking and search signals. By : Wendy Ran We…
Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings
For most languages of the world, language model pre-training operates in a data-constrained regime where models must repeat their training data many times, degrading generalization. Two remedies exist: aggressive hyperpa…
AWS Weekly Roundup: Prime Day 2026 by the numbers, Claude Haiku 5.5, Amazon Nova 2.5 Sonic, and more (October 13, 2026)
Some numbers are hard to picture until you sit with them for a moment. Last week we published the Prime Day 2026 metrics, and the one that stuck with me is 2.3 quadrillion: the daily requests Amazon ElastiCache peaked at…
Under the hood, off the hot path: How D1 scales to millions of databases
A deep dive into how D1 architected its control plane to scale and manage millions of databases, while keeping data plane query operations at the edge. We share guiding principles on how to build on the Developer Platfor…
Rewinding the exponential: How we keep hardware usage down
Our strategies to optimize our data pipeline throughput without compromising data quality.