The code change wasn’t the hard part. Executing it safely ✅ across 6,000 repositories was.

At Wix, large-scale code migrations can 🚩 consume an estimated 25% of developer time every year. So instead of treating every migration as a new cross-company project - we built infrastructure to run them at scale.

Dana Avital shares how we built a Code Migration Platform that detects affected code, generates changes across thousands of repositories, validates them, creates and tracks PRs, and automates the path to merge.

📊 The result: 650 developer-days saved in one quarter, with 88% of generated PRs merged without manual changes.

Read how we turned code migrations into scalable infrastructure

@WixEng ⚡️

[☄️ Newsletter] From autonomous bug fixing and code migrations across 6,000 repositories to faster checkout, 2.5M+ daily E2E tests, developer focus, and hands-on agentic development:

Explore the latest engineering challenges, solutions, and lessons in our Wix Engineering newsletter.

Read it here:
https://wix.engineering/so/f1Q0tpRE3

@WixEng ⚡️

Calling an LLM is easy. Building an AI agent system that actually works in production 🚩 is not.

When we set out to turn a simple prompt into a production-ready Wix CLI application, we had to solve the hard parts: orchestrating multiple agents, managing complex dependencies, running workflows in parallel, and supporting continuous user changes - without taking control away from developers.

In this talk, Miri Volozhinsky breaks down the 🏗️ architecture behind Devibe and shares what the team learned while building a real-world AI app builder - from the first idea to production.

Watch to learn what it really takes to move from an impressive AI demo to a reliable developer product:

https://youtu.be/7HNaxSUPUTA?si=P2yBmLHxh4lDLelA

@WixEng ⚡️

Vilnius 🇱🇹 this one is for you! AI is changing engineering - and juniors may be the ones most ready for it: curious, adaptable, AI-native, and unafraid of change.

That’s why Wix Grow is returning to Vilnius for its 5th (!) season!

We're selecting 20 interns for a six-month paid program where they'll train as AI-native xEngineers, receive mentorship, join real engineering teams, and build products used by more than 300 million people.

This isn’t an internship where you watch from the sidelines. It's the real thing.

Applications are now open 👇

https://wix-grow.com

@WixEng ⚡️

5 billion records. 10 terabytes. Four weeks. 🚩

How do you migrate data at this scale without disrupting a live system - while millions of new changes keep arriving every day?

In their new article, Avraham Rosenzweig and Roy Noyman share the lessons behind one of Wix’s largest data migrations. Read and learn how to:

✅ Uncover corrupted legacy data before it breaks the migration

✅ Detect parity gaps between V1 and V2

✅ Prevent one failed record from blocking the entire pipeline

✅ Calculate the throughput needed to actually finish

A practical playbook for anyone building or migrating large-scale production systems:

https://www.wix.engineering/post/5-billion-records-10-terabytes-four-weeks-a-real-data-migration-playbook

@WixEng ⚡️

What do you do when you lose an AirPod and can't access Apple's Find My app?

If you're Denys Dovhan, you build your own solution.

Denys used Claude and the Bleak Python library to create a lightweight macOS utility that scans nearby Bluetooth devices and tracks their signal strength.

About 20 minutes and 20 lines of code later, he just walked around his home with his MacBook and found the missing AirPod in a shorts pocket.

A great example of how AI can help engineers turn a small everyday problem into a working solution in minutes. Read on dev ua:

https://dev.ua/en/news/inzhener-wix-znaishov-zahublenyi-airpods-za-dopomohoiu-claude-1788356817

@WixEng ⚡️

Millions of users. Critical 🚩 production databases. Zero downtime. No room for mistakes.

At Wix, shared database clusters posed a serious reliability challenge: one problematic application could impact many others.

The solution? 🚩

Move databases between clusters - without interrupting the applications using them.

Bar Shauli shares how she and the Wix Data Infrastructure team built an internal migration service using Kafka and ProxySQL on top of MySQL to make these moves safely, transparently, and fully online at massive scale.

From streaming data and handling partitioning challenges to cutting over live traffic - here's the engineering behind database migrations that users never notice:

https://www.linkedin.com/feed/update/urn:li:activity:7502672084792406016

@WixEng ⚡️

"Resize an image 🎨. How hard can it be?"

Now do it across 300M+ websites and 6B+ media requests. Every day.

Suddenly, every memory copy slows you down. Every cache miss repeats expensive work. Every resize burns CPU. And an encoder upgrade can break your tests - even when the image still looks perfect.

In his new post, Tomer Salton reveals how Wix Media Platform handles this scale:

✅ Making real-time AVIF encoding work across Go and C
✅ Cutting resize costs with intermediate “Master” images
✅ Turning different URLs with identical outputs into one cache hit
✅ Testing visual quality with SSIM and VMAF
✅ Serving previews and paid originals securely from the same asset

Read the full story here:
https://www.wix.engineering/post/architecting-for-6-billion-daily-requests-inside-wix-s-media-platform

@WixEng ⚡️

Most AI failures aren’t model failures. They’re context failures. 🚩

In this Wix Engineering Conference 2026 talk, Maya Halevy explains why bigger context windows don’t automatically lead to better results, what really happens inside LLMs when context gets messy, and how to structure prompts, instructions, examples, and retrieved data to build more accurate, efficient, and reliable AI systems.

Watch:
https://youtu.be/fwI4p9l8ncs?si=mJPLj9MdfCFIfvr0

@WixEng ⚡️

AI can write code, use tools, and power autonomous agents. Yet at its core, it does one surprisingly simple thing: predict 🔮 the next word.

So how did autocomplete become intelligence?

In his new article, Gilad Barkan cuts through the weekly noise of new models and frameworks to explain why language became the operating system of AI.

Learn how LLMs actually acquire intelligence, why Transformers and scale changed everything, and where today’s models still fall short:

https://www.wix.engineering/post/from-autocomplete-to-intelligence-how-language-became-the-operating-system-of-ai

@WixEng ⚡️

If AI generates code faster than your team can review it, you haven't accelerated engineering. You've accelerated technical debt.

At scale, the critical AI coding layer isn't generation. It's the infrastructure that gives agents context, guardrails and a reliable review loop. Read here:

From Co-Pilot to Full Automation: How Wix Is Embedding AI Agents Across an Engineering Org at Scale

@WixEng ⚡️