Read what ships.

01GitLab · tutorial

PHP2Shell: GitLab helps find and remediate critical PHP flaws

Critical remote code execution vulnerabilities known as PHP2Shell affect the PHP engine across multiple versions, requiring immediate runtime updates to fixed versions or patched distribution packages. The team utilized platform features like container scanning, code search, and automated agent workflows to locate PHP projects and remediate vulnerabilities. Operators must also check logs and environments for signs of compromise as framework updates and input validations cannot prevent these engine-level flaws.

DEPTH ■■■■■10 min read3 days ago

ArchitectureSecurity

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02Meta · architecture

The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Do

Meta engineers reduced hallucinations and improved reliability in their data pipeline agents by replacing a single heavyweight LLM orchestrator with a thin deterministic router and fourteen specialized subagents. The thin orchestrator handles routing and reliability checks through a fixed protocol, while isolated subagents execute domain reasoning. This architecture reduced configuration preparation time from a day to under an hour.

DEPTH ■■■■■7 min read6 days ago

Machine Learning

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03Meta · architecture

Inside Prometheus: Meta’s Journey to a Gigawatt-Scale Supercluster

Meta built Prometheus, a gigawatt-scale AI supercluster designed to scale up to one million GPUs using multi-generation NVIDIA hardware and specialized backend Ethernet networks. The team achieved high goodput and significantly reduced system interruptions by implementing an in-rack sparing strategy, parallelism-aware fault tolerance, and close co-engineering with vendors. These infrastructure advancements allowed the team to successfully train frontier foundational models like Muse Wonder.

DEPTH ■■■■■17 min read6 days ago

InfrastructureMachine Learning

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04GitLab · scaling

Make every AI credit count: See, cap, and reduce agent spend

Uncontrolled AI agent spending can be mitigated by combining open-weight models, centralized context graphs to reduce retries, and usage analytics with credit caps. GitLab introduced these capabilities in its Duo Agent Platform to help platform teams trace, limit, and optimize AI credit consumption. The resulting architecture matches specific tasks to lower-cost models while maintaining task completion quality.

DEPTH ■■■■■6 min read12 days ago

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05Meta · practice

How Meta Built Forum With AI-Native Engineering

Meta engineers built the Forum app using a human-on-the-loop AI agent workflow that automated planning, building, testing, and verification. By shifting focus from code generation to automated verification, tooling improvements, and architectural legibility, the team reached feature parity in eight weeks while catching systemic memory issues early.

DEPTH ■■■■■8 min read10 days ago

FrontendMobile

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06Meta · architecture

Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI

Meta developed GEM, a unified recommendation foundation model using an LLM-style architecture called Kunlun to handle heterogeneous ads data across multiple surfaces. The team implemented block attention, custom low-precision kernels, and post-training intelligence transfer techniques like LoopFM and Solaris to scale training efficiency and bypass real-time serving latency bottlenecks. The resulting system delivered an 18.9% conversion improvement and a 12% click-through rate increase across Meta ads surfaces.

DEPTH ■■■■■15 min read12 days ago

Machine Learning

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07Meta · architecture

OCP Summit 2026: Powering AI with Open Innovations in Scale-Up, Scale-Out, and Scale-Across Networks

Meta shared its next-generation open networking infrastructure for AI at the OCP Summit 2026, including liquid-cooled 102.4T switch platforms, multiplane scale-out fabrics, and Ethernet-based scale-up solutions. The team also highlighted collaborative industry standards like ESUN and OSPA to unify hardware and transport layers. These open innovations aim to support massive gigawatt-scale AI clusters across diverse data center environments.

DEPTH ■■■■■12 min read13 days ago

Machine Learning

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08Heroku · architecture

Front-End Web Deep Dive: Runtime Config

Front-end web applications traditionally bake environment variables into build artifacts, requiring a full rebuild to change configurations across environments. To solve this, a new approach injects runtime environment variables directly into the HTML document's head element as data attributes via a Cloud Native Buildpack. This enables zero-rebuild configuration changes while remaining compatible with browser security standards like CSP.

DEPTH ■■■■■3 min read10 days ago

Frontend

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09Meta · architecture

GenRecs Tokenization: Transforming Ads Recommendation at Meta with Stable Model Vocabulary

Meta implemented GenRecs Tokenization to replace dedicated item IDs with a stable semantic vocabulary for ads recommendation. Using a three-stage encoding and quantization pipeline, the system enables language models to reason about ad content and user preferences simultaneously. This approach resulted in a +0.35% lift in conversions and improved cold-start performance for new entities.

DEPTH ■■■■■6 min read6 days ago

Machine Learning

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10Meta · scaling

2026 World Cup: Breaking Records, Spiky Charts and Reliability at Scale

Meta's infrastructure handled record-breaking traffic during the 2026 World Cup, including 30 million messages per second on WhatsApp, by relying on automated load balancing, capacity buffers, and targeted pre-builds. Traffic patterns revealed that surges occurred primarily during breaks rather than gameplay, requiring region-specific forecasting rather than cross-region load shifting. The systems maintained full reliability and allowed normal continuous deployment schedules to continue without manual intervention or system freezes.

DEPTH ■■■■■5 min read10 days ago

Infrastructure

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11Meta · migration

Shipping Media Over QUIC at Meta Scale for Instagram Live Ingest

Meta deployed the emerging Media over QUIC (MoQ) protocol for Instagram Live ingest on iOS and Android to replace their legacy RUSH protocol. By using edge translation to avoid backend rewrites and a phased rollout strategy, the team achieved metric parity with the old protocol without regressions. This deployment establishes a foundation to extend MoQ across Meta's applications for lower-latency and more resilient video streaming.

DEPTH ■■■■■8 min read13 days ago

FrontendMobile

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12GitLab · tutorial

Three developer tasks worth handing to an agent

The post explains how to use GitLab Duo Agent Platform features such as automated code reviews, CI/CD pipeline failure diagnosis, and cross-project chat. It provides setup instructions for configuration and outlines a consumption-based pricing model using credits. The features aim to automate routine developer workflows using broader project context than standard IDE assistants.

DEPTH ■■■■■4 min read6 days ago

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