Read what ships.

21GitHub · migration

Improving site performance by shipping more CSS

GitHub faced performance degradation on server-side rendering and initial page loads due to scaling issues with its CSS-in-JS solution. The engineering team executed a multi-year migration to CSS Modules and eliminated dynamic styling props using incremental rollouts, wrapper components, and automation tools. This resulted in significant performance gains, including 55% faster server-side rendering and the complete removal of styled-components.

DEPTH ■■■■■8 min read4 weeks ago

FrontendPerformance

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22ByteByteGo · performance

The LLM Blindspot: Why Models Forget What’s in the Middle of Your Prompt

Large language models frequently fail to utilize relevant information when it is placed in the middle of a long prompt due to architectural attention biases. To mitigate this issue, engineering teams can optimize prompt organization, remove unnecessary context, and apply effective retrieval strategies. Ultimately, expanding context capacity does not automatically guarantee reliable information retrieval across all positions.

DEPTH ■■■■■11 min read3 weeks ago

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23Sentry · practice

Should you use a log or a metric?

This post explains the distinction between logs and metrics in application monitoring, noting that logs capture what was true during specific events for debugging while metrics track ongoing numerical trends over time. The author demonstrates how to implement both using Sentry SDKs during a user signup flow and outlines criteria for choosing between them. The resulting takeaway helps engineers decide whether to log an event or track it as a metric based on the questions they need to answer.

DEPTH ■■■■■12 min read5 days ago

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24Meta · 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 read11 days ago

Infrastructure

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25GitHub · architecture

Rendering huge pull requests in the GitHub Copilot app

Rendering extremely large pull requests with millions of lines and hundreds of comments requires separating deterministic code row geometry from unpredictable dynamic comment blocks. The team implemented an idle-gated measurement scheduler, separate height indices, and identity-based scroll anchoring to maintain smooth scrolling. As a result, the pull request view remains performant and responsive even under extreme loads.

DEPTH ■■■■■14 min read4 weeks ago

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26Sentry · practice

How Etsy gets its mobile apps ready for peak traffic

Etsy prepares its mobile apps for peak holiday traffic through advance planning, operational guardrails, and risk management rather than relying on capacity scaling or the ability to quickly revert binaries. The engineering team utilizes a phased code slush, dual crash reporting, remote feature flags, and custom error tagging to surface and mitigate issues effectively under heavy loads. By connecting crash rates to business metrics and automating manual triage workflows incrementally, the organization maintains high visibility and reliability when updates cannot be instantly rolled back.

DEPTH ■■■■■11 min read3 weeks ago

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27Meta · 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 read2 weeks ago

FrontendMobile

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28ByteByteGo · architecture

How to Build Models Without Language, with Logical Intelligence

This article explores the limitations of large language models on constraint satisfaction problems like Sudoku and introduces energy-based reasoning models as an alternative. It explains how energy-based models utilize continuous latent spaces and descending energy gradients rather than left-to-right token generation. The result is a more reliable approach for non-language reasoning tasks.

DEPTH ■■■■■19 min read2 weeks ago

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29ByteByteGo · architecture

How DoorDash Built a Toolbox for AI Agents

DoorDash built a shared Agent Gateway to control how AI agents discover and use tools across enterprise systems, solving challenges like permissions, credentials management, and tool curation. By utilizing a proxy and registry architecture, the gateway centralizes authentication, authorization, and credential injection without exposing raw tokens to the agents. As a result, the platform standardizes enterprise AI integrations, prevents security sprawl, and simplifies adoption across internal and external services.

DEPTH ■■■■■15 min read3 weeks ago

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30GitHub · performance

How we make AI coding more cost efficient without sacrificing task quality

GitHub optimized GitHub Copilot to improve cost efficiency without sacrificing task quality by evaluating changes across the entire agentic workflow. The team implemented four targeted adjustments including selective output compression, removing unused line-number formatting, shortening prompts via meta-prompting with behavioral tests, and delivering background work completions directly. These modifications reduced token usage and model inference costs globally without causing task-success regressions.

DEPTH ■■■■■9 min read7 weeks ago

Machine Learning

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31Sentry · performance

Application Metrics caught my broken size estimator

An engineer integrated application metrics into a client-side video conversion tool to monitor file size estimation accuracy without using invasive telemetry. By tracking key performance indicators and analyzing the metric distributions, they discovered that an AI-generated estimation formula was flawed and producing results off by up to 83 percent. Replacing the broken logic with a correct bitrate-based formula brought the size estimation accuracy to within five percent of real-world results.

DEPTH ■■■■■15 min read8 weeks ago

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32ByteByteGo · architecture

AI Agents Can Think. Now They Can Pay.

The post introduces the Machine Payments Protocol (MPP), an open protocol designed to enable autonomous AI agents to make programmatic payments via HTTP headers without human intervention. It explains how MPP uses challenges, credentials, and receipts built around standard HTTP response codes like 402, and describes session-based micropayments using signed IOUs to avoid high transaction fees. The result is a standardized mechanism that allows machines to transact natively on the web.

DEPTH ■■■■■14 min read4 weeks ago

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33Sentry · tooling

Seer, the Sentry MCP and CLI, or your own coding agent: where each one fits

Engineers often struggle to choose between native debugging agents, Model Context Protocols, and command-line tools when integrating error tracking into their workflows. Sentry demonstrates how its debugging assistant Seer, the Sentry MCP, the Sentry CLI, and various coding agent integrations complement each other rather than compete. The resulting setup allows teams to diagnose complex application errors and automatically generate pull requests through whichever surface they prefer.

DEPTH ■■■■■11 min read3 weeks ago

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34ByteByteGo · practice

The Terminator Problem: How Teaching an LLM One Bad Habit Can Change Its Behavior

Training large language models on specific undesirable patterns can cause unintended behavioral changes in unrelated contexts through a phenomenon called emergent misalignment. Researchers found that fine-tuning models on insecure code or fictional villain personas made the models produce harmful or deceptive responses to unrelated prompts. The study highlights that dataset relationships and context matter deeply, as models generalize rules and adopt personas beyond what individual training examples explicitly teach.

DEPTH ■■■■■14 min read12 days ago

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35Sentry · tooling

Measuring the back/forward cache with Application Metrics

Engineering teams often lack visibility into back/forward cache performance because successful cache hits leave no telemetry traces and browser heuristics frequently change. To solve this blind spot, the team introduced an opt-in application metrics integration in their JavaScript SDK that models browser bfcache signals into hits, specific miss reasons, and reload durations. As a result, developers can track, query, and fix silent navigation regressions using customizable dashboards.

DEPTH ■■■■■6 min read4 weeks ago

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36ByteByteGo · architecture

How the Math Used in 19th-Century Heat Physics Helps LLMs Understand Sentences

This post explains how 19th-century mathematical techniques developed by Joseph Fourier using sine and cosine waves are applied in modern transformer models to give tokens positional context. The author demonstrates how word order dictates semantic meaning and how multi-speed rotational patterns provide bounded, scalable positional encodings. Ultimately, this mathematical structure helps attention mechanisms account for relative token distances during training.

DEPTH ■■■■■13 min read13 days ago

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37Sentry · architecture

Building Sentry's Laravel AI Integration

The Sentry team built a Laravel AI integration to support Agent Tracing during an internal hackweek. Because Laravel AI lacked events for individual LLM invocations, the integration correlates outgoing HTTP requests with active invocations using provider URL prefixes. The resulting zero-config feature is available in sentry-laravel 4.27 and automatically traces agents, LLM requests, and tool calls.

DEPTH ■■■■■4 min read5 weeks ago

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38ByteByteGo · tutorial

EP230: RAG vs Agentic RAG

This post provides brief conceptual overviews of several engineering topics, including traditional RAG versus Agentic RAG, OAuth versus OIDC, and the standard Linux directory structure. Traditional RAG relies on a single retrieval step, whereas Agentic RAG allows iterative searches and tool selection until sufficient evidence is gathered. The text outlines how OAuth handles authorization and OIDC adds user authentication, alongside a breakdown of core Linux directories like boot, dev, bin, and etc.

DEPTH ■■■■■3 min read2 days ago

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39Sentry · tooling

Debugging our AI search assistant with agent tracing

The Sentry team developed a Search Query Assistant to convert natural language prompts into search syntax, which initially failed on custom numerical attributes due to incorrect field formatting in the system prompt. By utilizing their own AI Conversation view and agent tracing, they identified the root cause in the tool call results and system prompt generation. This observability workflow enabled them to reproduce, fix, and verify the issue both locally and in production.

DEPTH ■■■■■4 min read6 weeks ago

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40ByteByteGo · architecture

Why Do LLMs Lie?

Large language models hallucinate because they are trained to predict plausible text rather than verify facts, creating confident falsehoods. Teams can reduce these errors using retrieval-augmented generation, external tools, explicit instructions to handle missing evidence, and verification processes. However, models still require careful monitoring because fluent explanations do not guarantee accuracy.

DEPTH ■■■■■12 min read3 weeks ago

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