73: Mobile GraphQL at Meta in 2025

Join Pascal and Sabrina on the latest Meta Tech Podcast episode as they discuss the evolution and future of GraphQL. From client-side consistency to innovative APIs, learn how GraphQL is making developers' lives easier and enhancing user experiences. Discover surprising insights into the challenges of building a mobile GraphQL platform and how it's transforming product development at Meta.  Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host Pascal (https://mastodon.social/@passy, https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links GraphQL: https://graphql.org/  Relay: https://relay.dev/  Sabrina at GraphQL Conf 2024: https://www.youtube.com/watch?v=PGBC-0E-kco  Timestamps Intro 0:06 Introduction Sabrina 1:42 Sabrina's team 2:47 What's GraphQL? 3:18 Relay and Mobile GraphQL Clients 4:01 GraphQL Consistency Engine 4:54 Pando Mobile GraphQL Client 7:16 Interfacing with Pando 8:03 Code generation 9:14 Inventing new features 10:43 The hidden complexity behind pagination 11:52 Working inside the GraphQL spec 16:00 Complexity tradeoffs 18:30 State of GraphQL at Meta 21:16 Measuring success 24:58 Optimistic Mutations 27:31 Collaboration model 31:42 Preventing early adoption 34:43 The challenge of migrating FBApp 37:10 What's next for mobile GraphQL? 40:22 Outro 41:54  

In this episode of the Meta Tech Podcast, host Pascal sits down with Shane, a research scientist at Meta, to explore the cutting-edge research behind Ray-Ban Meta glasses. Shane shares insights from his seven-year journey at Meta, where he focuses on computer vision and multimodal AI within the Wearables AI organization. Tune in to learn how Shane's team is pioneering foundational models for Ray-Ban Meta glasses, tackling unique challenges, and pushing the boundaries of AI-driven innovation. Discover how multimodal AI is transforming user experiences and get a glimpse into the future of wearable technology. Whether you're an engineer, a tech enthusiast, or simply curious about the latest advancements, there is something for everyone in this episode.  Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host Pascal (https://mastodon.social/@passy, https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model - https://arxiv.org/abs/2309.16058  Be My Eyes Programme: https://www.forbes.com/sites/stevenaquino/2024/10/11/inside-the-be-my-eyes-meta-collaboration-and-the-allure-to--impact-humanity/  Meta Open Source on Threads: https://www.threads.net/@metaopensource  CacheLib: https://cachelib.org/  Meta’s AI-Powered Ray-Bans Are Life-Enhancing for the Blind - Wall Street Journal: https://www.wsj.com/tech/ai/metas-ai-powered-ray-bans-are-life-enhancing-for-the-blind-3ae38026  Timestamps Intro 0:06 OSS News 0:56 Introduction Shane 1:30 The role of research scientist over time 3:03 What's Multimodal AI? 5:45 Applying Multimodal AI in Meta's products 7:21 Acoustic modalities beyond speech 9:17 AnyMAL 12:23 Encoder zoos 13:53 0-shot performance 16:25 Iterating on models 17:28 LLM parameter size 19:29 How do we process a request from the glasses? 21:53 Processing moving images 23:44 Scaling to billions of users 26:01 Where lies the optimisation potential? 28:12 Incorporating feedback 29:08 Open-source influence 31:30 Be My Eyes Programme 33:57 Working with industry experts at Meta 36:18 Outro 38:55

How do you translate roughly ten million lines of Java code to Kotlin? Clicking in your the IDE gets pretty repetitive after a while and doesn’t work if you have custom APIs and requirements for null safety. Eve and Jocelyn, two software engineers on the Mobile Infra Codebases Team have taken on this challenge and talk host Pascal through the unexpected difficulties when embarking on the journey to (close to) 100% Kotlin in our Android codebase. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host Pascal (https://mastodon.social/@passy, https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Meta Engineering Blog - Translating Java to Kotlin at Scale: https://engineering.fb.com/2024/12/18/android/translating-java-to-kotlin-at-scale/  Open-source transformations: https://github.com/fbsamples/kotlin_ast_tools  Mobile @Scale Conference recordings: https://www.youtube.com/watch?v=L7xSnbrk4CI Timestamps Intro 0:06 Introduction Eve 1:11 Introduction Jocelyn 2:15 Team mission 2:44 The scale of Meta's codebase 3:40 Why is there so much code? 4:34 Why migrate to Kotlin? 5:45 Isn't Kotlin slow to compile? 7:51 Why not use Android Studio's converter? 8:28 Nullability differences 10:04 Meta Codemod Service 14:50 Kotlin codemod stages 17:07 Headless J2K 20:14 Open-source transformations 23:14 Java Nullsafe 24:47 Leveraging Linters 26:01 Fixing build errors 27:24 Unexpected challenges 29:33 State of the union 33:44 Outro 36:10 Outtakes 37:08

Introducing a new Android UI Framework like Jetpack Compose into an existing app is easy right? Import some AARs and code away. But what if your app has specific performance goals to meet, has existing design components, integrations with navigation and logging frameworks? That is where Summer and her team come in who handle large-scale migrations for Instagram. They aim to provide developers with the best possible experience when working on our code bases, even if that requires some temporary pain on the side of infrastructure teams that have to maintain multiple implementations at once. Why Summer thinks it is worth it, how they approach the rollout of a new framework and so much more is all discussed in episode 70. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host Pascal (https://mastodon.social/@passy, https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Jetpack Compose: https://developer.android.com/compose Litho: https://fblitho.com/ Google Showcase: Meta built threads in only 5 months using Jetpack Compose: https://android-developers.googleblog.com/2023/10/meta-built-threads-in-only-5-months-using-jetpack-compose.html Flipper: https://fbflipper.com/ Timestamps Intro 0:06 Intro Summer 1:29 Notable differences moving from FB to IG 2:26 The Instagram Data & UI Architecture team 2:58 Why modernise? 3:44 Where has the risk paid off? 6:08 What does Compose look like? 7:49 Compose v Litho 11:15 Where does Litho still have the upper hand? 14:53 Meta contributions to Compose 16:38 Compose pitfalls 19:10 Rolling Compose out across the company 20:13 Design systems 22:12 Downsides of establishing another UI framework? 24:22 Rollout stages 28:43 Experimentation stage 32:32 Closed enrollment phase 38:15 Graduation criteria 39:38 Outro 42:20 Bants 44:04

Do types actually make you more productive or is it just more typing for you to do on the keyboard? That's just one of the questions we managed to answer at least on a small scale with Diff Authoring Time or DAT, here at Meta. Want to know how we leverage metrics to run experiments on productivity in our internal codebase? Tune in to episode 69. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Hack language: https://hacklang.org/  Timestamps Intro 0:06 Henri Intro 1:45 Ian Intro 3:13 Moritz Re-Intro 3:28 DAT Recap 3:48 What is Hack? 4:20 Inner and outer loop 14:13 Experimenting with language features 17:47 Code sharing frameworks at Meta 27:43 Measuring framework productivity 29:01 Will we see more experiments? 34:23 Time savings from code sharing 37:28 Outro 39:03 Blooper 39:52

How do you build your own mixed reality headset from sketch to scale? That's exactly what Alfred Jones, VP of hardware engineering at Meta Reality Labs, discussed with host Pascal. From choosing the right display technology, battery, thermal budget and of course hitting the right price point. How he manages to not fall victim to choice paralysis and so much more in episode 68. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod) or Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host Pascal (https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Caddy: https://engineering.fb.com/2024/07/18/virtual-reality/caddy-cad-mixed-reality-mr-meta/ Timestamps Intro 0:06 Alfred Introduction 1:40 Who do you work with? 3:23 Decision making frameworks 5:20 Is MR the final destination? 7:19 What makes good passthrough such a challenge? 10:18 How to build your own MR headset 13:51 Hardware design constraints 19:00 Prototype phases 22:34 Durability testing 26:23 Dogfooding at Meta 28:55 Magic wand for technical limitations 31:56 Outro 34:26

At Meta, engineers are our biggest asset which is why we have an entire org tasked with making them as productive as possible. But how do you know if your projects for improving developer experience are actually successful? For any other product, you would run an A/B test but that requires metrics and how do you measure developer productivity? Sarita and Moritz have been working on exactly that with Diff Authoring Time which measures how long it took to submit a change to our codebase. Host Pascal talks to them about the way this is implemented, the challenges and abilities this unlocks. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy, https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. You can follow our guest Moritz on X (https://x.com/Inventitech) or check out his website on inventitech.com. Links Meta Connect 2024: https://www.meta.com/en-gb/connect/ Timestamps Episode intro 0:05 Sarita Intro 2:33 Moritz Intro 3:44 DevInfra as an Engineer 4:25 DevInfra as a Data Scientist 5:12 Why DevEx Metrics? 6:04 Average Diff Authoring Time at Meta 9:55 Events for calculating DAT 10:55 Edge cases 13:15 DAT for Performance Evaluation? 20:29 Analyses on DAT data 22:29 Onboarding to DAT 23:23 Stat-sig data 25:06 Validating the metric 26:34 Versioning metrics 28:09 Detecting and handling biases 29:19 Diff coverage 30:30 Do we need DevX metrics in an AI software engineering world? 31:23 Measuring the impact of AI tools 32:23 What's next for DAT? 33:40 Outtakes 36:22

Bento is Meta’s internal distribution of Jupyter Notebooks, an open-source web-based computing platform. Host Pascal is joined by Steve who worked with his team on building many features on top of Jupyter, including scheduled notebooks, sharing with colleagues and running notebooks without a remote server component by leveraging Webassembly in the browser. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy, https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Scheduling Jupyter Notebooks at Meta: https://engineering.fb.com/2023/08/29/security/scheduling-jupyter-notebooks-meta/ Serverless Jupyter Notebooks at Meta: https://engineering.fb.com/2024/06/10/data-infrastructure/serverless-jupyter-notebooks-bento-meta/ Jupyter Notebooks: https://jupyter.org/  Timestamps Intro 0:06 Who is Steve? 1:49 What are Jupyter and Bento? 2:48 Who is Bento for? 3:40 Internal-only Bento features 4:42 Scheduled notebooks 11:39 Integrating with existing batch jobs 17:10 The case for serverless notebooks 20:59 Enter wasm 24:29 Upgrade paths from serverless to server 26:29 Bringing more Python libraries to the browser 30:21 Adding magick(s) 31:52 DataFrame magic and AI 36:41 What's next? 38:29 Outro 43:17

We don’t know when but at some point in the future we will face what researchers call a "Quantum Apocalypse". This is when quantum computers will be able to break many of our existing encryption algorithms. To keep Meta’a users safe even from attacks that don’t even exist today, Sheran and Rafael are working on post-quantum-ready encryption. Tune in to learn about the various challenges and trade offs that this work brings with it.   Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy, https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Post-quantum readiness for TLS at Meta: https://engineering.fb.com/2024/05/22/security/post-quantum-readiness-tls-pqr-meta/  Fizz TLS implementation: https://github.com/facebookincubator/fizz  liboqs: https://github.com/open-quantum-safe/liboqs  NIST Post-Quantum Cryptography Submissions: https://csrc.nist.gov/Projects/post-quantum-cryptography/post-quantum-cryptography-standardization/round-3-submissions    Timestamps Intro 0:06 Meta Open Source 101 1:10 Intros 1:49 Sheran Intro 2:31 Rafael Intro 3:37 Then Quantum Apocalypse 5:24 Why symmetric and asymmetric algos behave differently 8:10 Why invest in tomorrow's problems? 9:21 First deployment target 14:17 Choosing an algorithm 18:06 Choosing the right parameters 19:51 Performance costs and wins 21:28 Stack 23:33 Challenges 25:26 What's next for PQC? 30:38 Working with NIST 32:59 Outro 34:30 Outtakes 35:43

After sitting in one too many Zoom meetings looking at flat images of 3D models, mechanical engineers Ed, Jason, Fan, and Raghavan decided that they could do better, taught themselves how to code and started to build Caddy - a CAD app for mixed reality. Tune in to episode 64 to hear their story. Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy, https://mastodon.social/@passy, and https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/. Links Caddy video: https://heycaddy.net/ Caddy on the Quest Store: https://www.meta.com/en-gb/experiences/24212682218375897/  @Scale conference on YouTube: https://www.youtube.com/channel/UCd9I8ZkgoR1d7GeSj_wi_LQ  MLow @Scale talk: https://www.youtube.com/watch?v=3ypsZUNRjI4 MLow blog post: https://engineering.fb.com/2024/06/13/web/mlow-metas-low-bitrate-audio-codec/  Faster Incident Response with GenAI @Scale talk: https://www.youtube.com/watch?v=rpe7eAR90Ko Llama 3: https://llama.meta.com/llama3/ Meta Unity SDKs: https://developer.oculus.com/documentation/unity/ Prisms VR: https://www.prismsvr.com/  Timestamps Intro 0:06 Ed Intro 2:12 Raghavan Intro 3:15 Fan Intro 3:44 Jason Intro 4:16 What is Caddy? 4:49 Why build Caddy? 6:52 Discovery of hand-based interactions 11:46 Supported import formats 14:09 Learning to code 18:09 Time to Caddy MVP 27:48 Off-the-shelf components 29:04 Outgrowing the initial vision 32:48 AI in Caddy 43:25 Challenges building Caddy 52:38 What's next? 55:40 How to get in touch? 56:56 Excitement in MR 57:38 Outro 1:03:35