# Wix Engineering Wix Engineering This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## From Autocomplete to Intelligence: How Language Became the Operating System of AI DevFeed: [From Autocomplete to Intelligence: How Language Became the Operating System of AI]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-09-15T10:17:07Z Content type: opinion Language: en Sources: [Wix Engineering]() Topics: [Artificial Intelligence](), [Language models](), [Large Language Model](), [ChatGPT](), [OpenAI]() Tags: [ai](), [article](), [chatgpt](), [language-models](), [large-language-models-llms](), [openai]() ### AI overview This article examines why language is closely tied to intelligence in both humans and artificial intelligence. It argues that AI became significantly more powerful by learning language exceptionally well, then introduces how large language models acquire intelligence through models that represent the world and reduce uncertainty. ### Source excerpt Introduction Every week brings a new AI model, a new coding assistant, a new agent framework. The pace can feel overwhelming. Yet beneath the churn lies a single, surprisingly simple fact - the fact this whole revolution turns on: AI became so powerful because it learned language exceptionally well. In this article I want to step away from the weekly headlines and ask a more basic question: why is language so tightly bound to intelligence - human intelligence in general, and artificial... ## Architecting for 6 Billion Daily Requests: Inside Wix's Media Platform DevFeed: [Architecting for 6 Billion Daily Requests: Inside Wix's Media Platform]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-09-08T08:24:05Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [Caching](), [Go Language](), [Latency](), [Compression](), [data](), [C]() Tags: [c](), [cache](), [caching](), [compression](), [cpu](), [data](), [go](), [latency](), [technical]() ### AI overview Wix describes engineering challenges in its media platform, which processes images, video, and audio at large scale. The supplied text explains how the team used unsafe pointers to reduce Go/C memory-copy overhead for AVIF encoding and a tiered Masters cache to reduce CPU work during image resizing. ### Source excerpt At Wix, "Media" isn't just about storing files. It's about processing streams of information - images, video, and audio - at an immense scale. We host over 300 million websites and serve more than 6 billion media requests every single day. To handle dozens of petabytes of data while keeping costs low and latency minimal, we had to treat media handling as a complex engineering discipline. Below are five specific technical challenges we faced and the architectural solutions we implemented to... ## 5 Billion Records, 10 Terabytes, Four Weeks: A Real Data Migration Playbook DevFeed: [5 Billion Records, 10 Terabytes, Four Weeks: A Real Data Migration Playbook]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-09-02T07:27:50Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [migration](), [data](), [Databases](), [API](), [Logging](), [Tech Debt]() Tags: [api](), [data](), [database](), [logging](), [migration](), [tech-debt]() ### AI overview This Wix engineering article presents a data migration playbook based on lessons from large and complex migrations. It argues that success depends less on changing tooling than on identifying recurring problems before migration begins, especially by auditing inconsistent source data, implementing a read phase, and logging suspicious fields and structures. It also outlines using a V2 API, an API proxy, population-based rollout, change data capture, continued synchronization, and eventual decommissioning of V1. ### Source excerpt By the time you finish reading this, someone at Wix is probably in the middle of a data migration. We've run migrations that lasted anywhere from a few months to two years. More recently, we've completed large and complex migrations in a few weeks. The difference wasn't the tooling, which barely changed. It was that we had finally learned which problems show up in every migration, and started dealing with them before the migration began instead of in the middle of it. Recap: Why We Migrate,... ## From Weeks to Hours: Inside Wix's Autonomous Bug-Fixing System DevFeed: [From Weeks to Hours: Inside Wix's Autonomous Bug-Fixing System]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-08-19T10:17:19Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [bug](), [Code review]() Tags: [architecture](), [autonomous](), [bug](), [code-review](), [context](), [database](), [jira](), [logs](), [pipeline](), [production](), [repo](), [support]() ### AI overview Wix describes the architecture behind Wix Orchestrator, an autonomous bug-fixing system designed to reduce the time from user reports to production fixes. The system automates investigation, context gathering, implementation, and code review, while requiring a human engineer to approve every fix before deployment. ### Source excerpt A user opens a support ticket. Their subscription cancellation stopped working. Somewhere inside a system with thousands of services and millions of users, something broke. Before we built Wix Orchestrator, here's what happened next: the ticket joined a queue. Days later, a support engineer picked it up, tried to reproduce the issue, contacted the customer to gather more context, and opened a Jira ticket routed to R&D. We triaged it, prioritized it against everything else on our plate,... ## How Wix Built a Code Migration Platform to Automate Cross-Team Repository Changes DevFeed: [How Wix Built a Code Migration Platform to Automate Cross-Team Repository Changes]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-07-22T14:10:18Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [migration](), [Code]() Tags: [automatic](), [code](), [developer](), [engineering](), [infrastructure](), [migration](), [organizational](), [platform](), [process](), [projects](), [scale](), [team]() ### AI overview Wix describes building a Code Migration Platform to reduce the coordination burden of large-scale code migrations. The platform is intended to identify affected repositories, apply changes automatically, and track migration work centrally. The article says Wix initiates 50 migrations annually, affects hundreds of repositories per migration, touches 6,000 repositories each year, and spends 25% of organizational developer time on migrations. ### Source excerpt No one wakes up excited to do a code migration. Deprecated libraries, method version upgrades, infra changes - they happen constantly, they affect dozens of teams, and they always arrive at the worst possible moment. A small technical change somehow becomes months of coordination. Slack threads. Priority negotiation. Manual tracking. Reminders. Many google sheets. For years, I managed cross-team projects at Wix, and migrations were always the hardest part. Not because they're technically... ## How AI-Assisted Coding Is Changing the Engineering Role DevFeed: [How AI-Assisted Coding Is Changing the Engineering Role]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-07-19T10:33:35Z Content type: opinion Language: en Sources: [Wix Engineering]() Topics: [Artificial Intelligence](), [Programming](), [Claude Code]() Tags: [2026](), [ai](), [claude-code](), [programming](), [prompting](), [workflow](), [writing-code]() ### AI overview This opinion article examines how AI-assisted coding is changing software engineering. It argues that writing code is increasingly an iterative dialogue involving prompting, evaluation, and pushback, while acknowledging engineers' uncertainty about the future of their work. ### Source excerpt During 2026, I shipped code that I don't fully understand. It was written in a programming language I'm not even fluent in. A year ago, this would have been a fireable offense. There's no way I would have stood on a stage at a Wix Engineering conference, my employers in the crowd, and said that sentence out loud. Last week, it was just another Tuesday. And here's the part that's been keeping me up at night: I was proud of it. That's a paradox, right? If someone else wrote it, I can't be proud... ## A Feedback-Driven Agent Pattern for Self-Repairing AI Workflows DevFeed: [A Feedback-Driven Agent Pattern for Self-Repairing AI Workflows]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-07-16T06:17:34Z Content type: tutorial Language: en Sources: [Wix Engineering]() Topics: [Loop Engineering](), [AI Agent](), [Code](), [context window](), [integrity]() Tags: [agentic-workflows](), [agents](), [ai-agent](), [ai-agents](), [code](), [context-window](), [validation]() ### AI overview This tutorial proposes a Feedback-Driven Agent pattern for building self-repairing AI agent workflows. It separates deterministic structural validation from goal-based assessment: agents produce artifacts, programmatic checks identify failures, and structured error reports route the agent toward repair. ### Source excerpt Every developer building with AI agents eventually hits the same wall. You write a masterpiece of a system prompt, loaded with rules, edge cases, and brand guidelines. It works perfectly... until you add one more rule. Suddenly, the agent gets "context fatigue," ignores half your instructions, and hallucinates a creative but entirely broken solution. We need to stop trying to make agents perfect on the first try. Instead, we suggest a new architectural approach: organizing agentic workflows... ## How Wix Built Context Retrieval for Cross-Service Code Research DevFeed: [How Wix Built Context Retrieval for Cross-Service Code Research]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-07-02T06:58:25Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [MCP](), [MCP Server](), [Code](), [GitHub](), [Tooling](), [bug](), [Server]() Tags: [agent](), [bug](), [code](), [github](), [mcp](), [mcp-server](), [retrieval](), [scale](), [tooling]() ### AI overview Wix describes building OctoCode, an MCP server over GitHub tooling, and Wix Octocode Research to help agents investigate code across repositories, packages, and services. The system was designed to gather context before fixes and to require agents to state their research goal before using tools. ### Source excerpt Ask a naive agent to find a bug in a codebase with thousands of repositories, and it will find the first textual match and stop. It won't ask why. It won't check whether what it found is actually relevant. It won't explore related services. It'll just return something and call it done. We, at Wix, discovered this the hard way. And it's what pushed us to build something more deliberate: a research engine that doesn't just search, but reasons about what it's looking for and why. The Problem:... ## From Co-Pilot to Full Automation: How Wix Is Embedding AI Agents Across an Engineering Org at Scale DevFeed: [From Co-Pilot to Full Automation: How Wix Is Embedding AI Agents Across an Engineering Org at Scale]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-05-20T07:28:09Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [ai-coding](), [agentic-coding](), [monorepo](), [Microservices](), [Claude](), [codex](), [cursor](), [GitHub Copilot](), [OpenClaw]() Tags: [agentic-coding](), [agents](), [ai](), [ai-coding](), [claude-code](), [codex](), [coding-agents](), [cursor](), [github-copilot](), [microservices](), [monorepo](), [openclaw]() ### AI overview Wix describes how agentic coding can be organized across an engineering organization with more than 2,500 microservices, thousands of engineers, strong service boundaries, and a large monorepo. The article presents a three-tier spectrum of cloud agents, coding agents or harnesses, and agents with computer access, identifying the harness tier as the practical sweet spot for software development as of 2025-2026. ### Source excerpt When you have over 2,500 microservices and thousands of engineers working across a massive multi-product platform, "just use AI coding tools" is not a strategy. It's a starting point - and not a particularly useful one. The question we kept coming back to at Wix wasn't whether to adopt AI in our engineering workflow. That ship had sailed. The question was: what does agentic coding actually look like when you have strong domain boundaries between services, a monorepo with years of... ## How We Built a Zero-Downtime Database Migration Service at Wix DevFeed: [How We Built a Zero-Downtime Database Migration Service at Wix]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-05-14T07:19:17Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [Databases](), [migration](), [Data Infrastructure](), [MySQL](), [Scalability]() Tags: [amazon-msk](), [data-infrastructure](), [database](), [database-migration](), [databases](), [db-topology](), [debezium-connector](), [good-tools-doesn-t-fit](), [how-db-mover-works](), [infrastructure](), [migration](), [mysql](), [scalability](), [summary-6-key-focal-points](), [the-challenge](), [the-python-service](), [the-result]() ### AI overview Wix describes DB Mover, an internal service for transparent, zero-downtime database migrations between shared and dedicated MySQL clusters. The article explains the operational risks of shared clusters, migration requirements, and the topology managed by Wix's Data Infrastructure team. ### Source excerpt The Challenge At Wix, multiple applications share the same DB cluster. The reasons vary: consolidating apps from the same domain, grouping several small apps that don't justify a dedicated cluster, or simply optimizing cost and operational overhead. However, this setup comes with a significant risk: every application on the cluster has the potential to impact all the others. One real example: we had a critical service related to user authentication sharing a DB cluster with several other... ## Wix compares AI agent performance using skills, standard documentation, and AI-optimized documentation DevFeed: [Wix compares AI agent performance using skills, standard documentation, and AI-optimized documentation]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-05-06T11:16:26Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [AI Agent](), [Documentation](), [Developer experience](), [Command-line interface]() Tags: [agents](), [ai-agent](), [developer-experience](), [docs](), [documentation](), [evals]() ### AI overview Wix describes 250 controlled evaluations comparing AI agents using standard documentation, AI-optimized documentation, and purpose-built skills. The article reports that stale skills can become a liability and questions whether manually maintained skills consistently outperform documentation. ### Source excerpt The industry has a new obsession: AI skills. The logic seems bulletproof: if you want an AI agent to use your platform, you shouldn't just give it raw documentation. You should give it a "skill", a curated, condensed, and optimized guide. This will allow the agent to perform tasks on your platform better than if they have to trawl through your docs. Skills are intuitive and trendy, but do they really provide agents with an edge over just using the docs and, if so, in what cases? At Wix, we... ## Wix Migrated Its MySQL EC2 Fleet from Intel CPUs to Graviton DevFeed: [Wix Migrated Its MySQL EC2 Fleet from Intel CPUs to Graviton]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-03-23T11:27:39Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [Graviton](), [MySQL](), [Ansible](), [awx](), [Amazon EC2](), [intel](), [Databases](), [DevOps](), [Replication](), [Server](), [Linux]() Tags: [amazon](), [ansible](), [awx](), [devops](), [ec2](), [graviton](), [infra](), [intel](), [linux](), [mysql](), [rdbms](), [replication]() ### AI overview Wix's DB Infra team migrated more than 1,000 MySQL EC2 servers across over 160 clusters from Intel-based CPUs to Graviton in one month, ahead of the original three-month timeline. The project also enabled a move to Amazon Linux 2023 and away from CentOS 7.0, using AWX workflows and Wix's Dev Portal to automate the process while accounting for replication and cluster reliability concerns. ### Source excerpt Last January, the DB Infra team at Wix embarked on a strategic and very important mission: Migrating all of our MySQL EC2 servers from Intel based CPUs to the new shiny Graviton ones. Not only will this allow us to work on better CPUs, saving us money and improving our databases, we'll be able to move to Amazon Linux 2023 OS and move from the EOL CentOS 7.0. That sounds simple enough, until you realize that we're dealing with over 1K servers spread over 160+ MySQL clusters. The initial... ## The xEngineer: A New Blueprint for Software Engineering in the AI Era DevFeed: [The xEngineer: A New Blueprint for Software Engineering in the AI Era]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-03-16T09:25:50Z Content type: opinion Language: en Sources: [Wix Engineering]() Topics: [Software Engineering](), [AI-assisted coding](), [Artificial Intelligence](), [Claude Code](), [codex](), [cursor]() Tags: [ai](), [ai-tools](), [code](), [debugging](), [development-process](), [event](), [legacy](), [software-engineering](), [testing]() ### AI overview A Wix article presents the xEngineer as an emerging model of software engineering in the AI era. It argues that as coding assistants make code production more routine, engineers increasingly focus on defining problems, designing systems, orchestrating intelligent tools, and applying AI across the engineering lifecycle. ### Source excerpt Aviran Mordo, Yaniv Event Haim, Asaf Yonay For decades, the role of the software engineer seemed straightforward: identify a problem and solve it by writing code. But the rise of powerful AI models is beginning to reshape that definition. With systems like Claude Code, Codex, Cursor and other advanced coding assistants, something important has become clear across the industry: writing code itself is gradually becoming a commodity. This does not mean software engineering is becoming less... ## Data-to-Production: Bridging the Gap Between Iceberg and Live Microservices DevFeed: [Data-to-Production: Bridging the Gap Between Iceberg and Live Microservices]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-02-17T11:04:08Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [Apache Iceberg](), [data observability](), [Microservice](), [clickhouse](), [Amazon S3](), [Architecture & Design](), [Apache Spark](), [airflow](), [Back end](), [API]() Tags: [airflow](), [amazon-s3](), [apache-iceberg](), [api](), [architecture](), [clickhouse](), [data](), [data-engineering](), [json](), [microservices](), [spark]() ### AI overview Wix describes Data-to-Production, a platform that activates data from Amazon S3 and Apache Iceberg for backend microservices. The system ingests Iceberg data into ClickHouse and serves it through a type-safe JSON API, using metadata governance and an Airflow and Python ingestion engine. ### Source excerpt At Wix, our Data Warehouse (DWH) is a massive repository of insights. Built on Amazon S3 using Apache Iceberg table formats, and populated by Trino and Spark jobs, it houses petabytes of data--from user segmentation and logs to AI chat analytics. However, storage is only half the battle. The real challenge--and the "holy grail" for many data engineering teams--is Activation : taking that petabyte-scale data and exposing it to backend microservices with millisecond latency, high availability, and... ## Wix's AirBot: An AI-Powered Slack Agent for Investigating Data Pipeline Failures DevFeed: [Wix's AirBot: An AI-Powered Slack Agent for Investigating Data Pipeline Failures]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-01-15T07:30:31Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [airflow](), [AI, ML & Data Engineering](), [data-engineering](), [Cloud](), [Slack]() Tags: [agent](), [ai](), [airflow](), [automation](), [bugs](), [data-engineering](), [engineering](), [http](), [process](), [processes](), [slack]() ### AI overview The article describes Wix's engineering environment, where thousands of Apache Airflow pipelines operate across a large cloud-based data platform. It presents AirBot, an AI-powered Slack agent intended to help engineers investigate pipeline failures across Airflow, Spark, Kubernetes, and related services. ### Source excerpt 1. Introduction: The Challenge Understanding the engineering need for AirBot starts with recognizing the scale of the ecosystem it operates within. Wix operates a massive cloud-based development platform serving 250 million users. This generates over 4 billion HTTP transactions daily, feeding a data lake that currently holds 7 petabytes of data. To manage this volume, Wix Data Engineering maintains over 3,500 Apache Airflow pipelines (DAGs) . These pipelines handle everything from ETL... ## From Syntax Checker to Critical Reviewer: How We Convinced AI to Catch Real API Quality Issues DevFeed: [From Syntax Checker to Critical Reviewer: How We Convinced AI to Catch Real API Quality Issues]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-01-07T10:09:21Z Content type: opinion Language: en Sources: [Wix Engineering]() Topics: [API](), [Artificial Intelligence](), [Developer experience](), [Usability]() Tags: [ai](), [api](), [api-design](), [developer-experience](), [mental-models](), [technical](), [usability]() ### AI overview The article examines how an AI tool reviewing API designs focused on measurable issues such as naming, formatting, and typos while missing developer-experience problems involving workflows, hidden rules, mental models, and usability. It describes this as a recurring bias and explains how the tool was adjusted to produce more critical reviews. ### Source excerpt Building an AI tool to review API design taught us something fundamental about how AI approaches quality: it confidently optimizes for the least important parts. Instead of flagging the quality issues that actually hurt developers, like confusing workflows, hidden rules, or inconsistent mental models, it focused on the safe, measurable stuff: naming patterns, formatting mistakes, even typos. Developer experience issues just didn't get caught, even though in our case, we specifically asked for... ## Why I Stop Prompting and Start Logging: The Design-Log Methodology DevFeed: [Why I Stop Prompting and Start Logging: The Design-Log Methodology]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2026-01-05T07:29:38Z Content type: tutorial Language: en Sources: [Wix Engineering]() Topics: [ai-coding](), [context](), [Code](), [coding](), [Documentation](), [Git](), [Markdown](), [Pull Request](), [TypeScript]() Tags: [ai-coding](), [code](), [coding](), [context](), [documentation](), [git](), [markdown](), [pull-request](), [typescript]() ### AI overview The article presents the Design-Log Methodology for AI-assisted software development. It recommends keeping version-controlled Markdown records of design decisions, project patterns, questions, implementation details, and outcomes so an AI coding tool can use project context before modifying code. A Jay Framework server-actions example illustrates the workflow, which the author says produced a tested pull request in two days. ### Source excerpt If you use AI to code, you've felt the "Context Wall." You start a project, things go great, but as the codebase grows, the AI starts making suggestions that conflict with previous decisions. You spend more time correcting the model than writing code To solve this, I developed the Design-Log Methodology. It started as a way for me to remember my own decisions in large projects, but it has become the single most important tool in my AI-coding workflow. The AI is no longer just a "coder"; it is... ## The Wix Engineering 2025 Review: AI, Platforms, Data, and Deep Technical Lessons-Learned DevFeed: [The Wix Engineering 2025 Review: AI, Platforms, Data, and Deep Technical Lessons-Learned]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2025-12-28T18:29:04Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [Artificial Intelligence](), [Platform Engineering](), [Software Engineering](), [data](), [Production Engineering](), [Large Language Model](), [Retrieval Augmented Generation (RAG)](), [Testing]() Tags: [2025](), [ai](), [architecture](), [article](), [best-practices](), [blog](), [data](), [developers](), [engineering](), [llm](), [platforms](), [rag](), [scale](), [software](), [software-engineering](), [technical]() ### AI overview Wix Engineering's 2025 review curates lessons from building and operating large-scale web systems, covering AI adoption and production systems, platform engineering, data systems, reliability, and software engineering practices. ### Source excerpt A Year of Building at Scale: Inside Wix Engineering During 2025, Wix Engineering shared deep dives, playbooks, and real-world lessons from building and operating one of the largest web platforms in the world. These stories don't start as content. They start as engineering challenges - some of the most complex, high-scale, and unforgiving challenges modern software teams face. Problems that emerge only when thousands of developers, hundreds of teams, and hundreds of millions of users meet... ## Platform Engineering Extends DevOps by Treating the Internal Developer Platform as a Product DevFeed: [Platform Engineering Extends DevOps by Treating the Internal Developer Platform as a Product]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2025-12-21T09:12:39Z Content type: opinion Language: en Sources: [Wix Engineering]() Topics: [Platform Engineering](), [DevOps](), [internal developer platform](), [Kubernetes](), [workflow automation](), [Deployment Strategies](), [GitHub Actions](), [GitLab](), [networking](), [Security]() Tags: [automation](), [deployment-strategies](), [devops](), [github](), [gitlab](), [internal-developer-platform](), [kubernetes](), [networking](), [pipelines](), [platform-engineering](), [policy](), [workflow-automation]() ### AI overview The article argues that platform engineering is a distinct discipline from DevOps. It focuses on treating an internal developer platform as a product and providing reusable, self-service systems that reduce infrastructure friction and operational complexity for developers. ### Source excerpt Imagine starting your day as a senior engineering manager at a fast growing tech company. You're barely through your first coffee when your phone lights up with a critical ticket. The Kubernetes environments don't match across stages. DevOps is in place. CI/CD, automation, monitoring, on-call rotations. And still, developers spend more time fighting infrastructure than building products. This is the moment many organizations mistakenly try to "add more DevOps." In reality, this is the moment... ## How Wix Used Context Engineering for an AI Scheduling Assistant DevFeed: [How Wix Used Context Engineering for an AI Scheduling Assistant]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2025-12-09T08:38:23Z Content type: article Language: en Sources: [Wix Engineering]() Topics: [context](), [Artificial Intelligence](), [AI Agent](), [Large Language Model](), [Development]() Tags: [agent](), [ai](), [context-engineering](), [data](), [llm](), [prompt-engineering]() ### AI overview Wix describes using context engineering to prepare, structure, and optimize data before sending it to an LLM for an AI scheduling assistant. The article explains how this preprocessing approach supports ranked candidate matching and enables use of the faster, lower-cost Gemini Flash 2.0 model. ### Source excerpt Intro: The Limits of Prompt Engineering In modern AI agent development, many teams, including ours at Wix , start with an intense focus on prompt engineering , carefully crafting instructions for the LLM. We iterated endlessly on system messages and instruction sets to solve a core problem: our AI scheduling assistant was struggling with vague requests, such as "Schedule a meeting with Jake." This simple sentence triggers a surprisingly complex challenge. The system must identify which... ## 40% Faster Interaction: How Wix Solved React's Hydration Problem with Selective Hydration and Suspense DevFeed: [40% Faster Interaction: How Wix Solved React's Hydration Problem with Selective Hydration and Suspense]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2025-11-09T12:58:45Z Content type: tutorial Language: en Sources: [Wix Engineering]() Topics: [React](), [Server-side rendering](), [Core Web Vitals]() Tags: [cdn](), [core-web-vitals](), [javascript](), [mobile](), [performance](), [react](), [ssr]() ### AI overview This Wix engineering article explains how React hydration can delay interactivity in server-rendered sites, particularly on mobile devices and slow networks. It introduces Selective Hydration, enabled by React 18's Suspense API, as an approach to preserve SSR benefits while improving interaction performance. ### Source excerpt Introduction For years, one of React's most persistent performance pain points has been hydration. At Wix, where we render hundreds of millions of websites using React and SSR, we've experienced this problem at scale. SSR initially gave us everything we wanted - instant paint, great SEO, and full-site CDN caching. Our pages loaded faster than ever. But as sites grew richer and heavier with content, hydration became a tax we could no longer ignore. The more components a page had, the longer it...