BEGIN:VCALENDAR
VERSION:2.0
X-WR-CALNAME:graphqlconf2026
X-WR-CALDESC:Event Calendar
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//Sched.com GraphQLConf 2026//EN
X-WR-TIMEZONE:UTC
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T150000Z
DTEND:20260520T004500Z
SUMMARY:Registration + Badge Pick-up
DESCRIPTION:\n
CATEGORIES:REGISTRATION + BADGE PICK-UP
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:45d129d20ebdf8326d2873d998880466
URL:http://graphqlconf2026.sched.com/event/45d129d20ebdf8326d2873d998880466
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T150000Z
DTEND:20260520T004000Z
SUMMARY:Solutions Showcase
DESCRIPTION:In order to facilitate networking and business relationships at the event\, you may choose to visit a third party’s booth or access sponsored content. You are never required to visit third party booths or to access sponsored content. When visiting a booth or participating in sponsored activities\, the third party will receive some of your registration data. This data includes your first name\, last name\, title\, company\, address\, email\, standard demographics questions (i.e. job function\, industry)\, and details about the sponsored content or resources you interacted with. If you choose to interact with a booth or access sponsored content\, you are explicitly consenting to receipt and use of such data by the third-party recipients\, which will be subject to their own privacy policies.
CATEGORIES:SOLUTIONS SHOWCASE
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:e76e911ccad9bfefd3e762e6e05cf6b2
URL:http://graphqlconf2026.sched.com/event/e76e911ccad9bfefd3e762e6e05cf6b2
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T160000Z
DTEND:20260519T160500Z
SUMMARY:Keynote: Opening Remarks - Janette Cheng\, Software Engineer\, Meta
DESCRIPTION:\n
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:aa8a73420ecf7386cb2a3b52570d338b
URL:http://graphqlconf2026.sched.com/event/aa8a73420ecf7386cb2a3b52570d338b
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T160500Z
DTEND:20260519T161500Z
SUMMARY:Keynote: GraphQL Foundation Update - Lee Byron\, Co-Creator of GraphQL and Director\, GraphQL Foundation
DESCRIPTION:\n
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:3a574de6a65ba152733cbf247ae54d2d
URL:http://graphqlconf2026.sched.com/event/3a574de6a65ba152733cbf247ae54d2d
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T161500Z
DTEND:20260519T162000Z
SUMMARY:Sponsored Keynote: Shaping New GraphQL Patterns from Strong Baselines - Uri Goldshtein\, CEO\, The Guild
DESCRIPTION:\n
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:76fc09beec012a1f43092ba55a295afb
URL:http://graphqlconf2026.sched.com/event/76fc09beec012a1f43092ba55a295afb
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T162500Z
DTEND:20260519T164500Z
SUMMARY:Keynote: Built to Evolve: 13 Years of GraphQL - Elena Bukareva\, Software Engineering Manager & Braxton Bragg\, Senior Product Manager\, Meta
DESCRIPTION:In 2015\, we promised GraphQL would be "easy to learn and use". Ten years\, and hundreds of billions of daily API calls later\, we've learned that not all our hopes and promises turned out to be true. \n \n This keynote is an honest retrospective from inside Meta. We'll share which assumptions didn't survive contact with thousands of engineers\, the complexity traps we fell into\, and what’s driving the new wave of GraphQL adoption and popularity at Meta.\n \n Whether you're GraphQL-curious or GraphQL-exhausted\, this is a rare look behind the curtain and a preview of what re-inventing GraphQL at scale actually looks like.
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:5fa93e5711633f3aca7c3ed8eabd6da5
URL:http://graphqlconf2026.sched.com/event/5fa93e5711633f3aca7c3ed8eabd6da5
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T165000Z
DTEND:20260519T170000Z
SUMMARY:Keynote: Creating a Golden Path for GraphQL - Benjie Gillam\, Maintainer\, Graphile & Kewei Qu\, Software Engineer\, Meta
DESCRIPTION:GraphQL's precise specification gives us incredible interoperability and a rich ecosystem of tooling to be used with any compliant GraphQL service... And yet\, that hasn't led to every adopter of GraphQL having a great experience. Some leave disillusioned with performance pitfalls\, security concerns\, and unforeseen complexity. This can be frustrating for successful GraphQL practitioners since in many cases the solutions to these problems have existed for most of the last decade.\n \n The Golden Path Initiative aims to make it so avoiding common pitfalls becomes the path of least resistance. By encouraging off-the-shelf GraphQL-related software to implement the recommended default behaviours\, we hope that GraphQL adopters will have the greatest chance of being successful even without ingesting the vast amount of information in the ecosystem. The Golden Path is not centred on building the most optimal experience\, instead it is focused on minimizing downsides: making it so users are exploring around the "pit of success"\, and taking them far from the "pit of despair".\n \n But to do this will take a huge\, coordinated community effort! We need successful GraphQL practitioners\; maintainers of key GraphQL libraries\, frameworks and tooling\; and documentation writers to join us over the next 6 months as we lay out the Golden Path\, its recommendations and requirements\; and then next year: time to start implementing it across the ecosystem!
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:0466574bdb1df2c888e087738a0248f8
URL:http://graphqlconf2026.sched.com/event/0466574bdb1df2c888e087738a0248f8
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T170000Z
DTEND:20260519T170500Z
SUMMARY:Keynote: GraphQL in the AI Era - Matt DeBergalis\, CEO and Co-Founder\, Apollo GraphQL
DESCRIPTION:A year ago\, we forecast an important role for GraphQL in an AI future. That prediction has come true\, with GraphQL now serving as the foundation of critical AI initiatives at household brands in retail\, hospitality\, health care and many more. Just as importantly\, GraphQL's declarative entity-based architecture has proven to be an ideal match for modern agentic development.\n \n In this talk\, we'll share a view of where GraphQL now sits in the modern enterprise stack\, recount lessons we've learned putting MCP workloads and agentic software in production with the graph\, our roadmap for an AI-first world\, and a vision of where GraphQL can and must go next.
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:a69fbe0529ffa9b7fb81ab3407e4886c
URL:http://graphqlconf2026.sched.com/event/a69fbe0529ffa9b7fb81ab3407e4886c
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T170500Z
DTEND:20260519T171000Z
SUMMARY:Keynote: Closing Remarks - Janette Cheng\, Software Engineer\, Meta
DESCRIPTION:\n
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:aa9669cf887841fa3ee79abedd6b15d7
URL:http://graphqlconf2026.sched.com/event/aa9669cf887841fa3ee79abedd6b15d7
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T171000Z
DTEND:20260519T173000Z
SUMMARY:Break
DESCRIPTION:\n
CATEGORIES:BREAKS + NETWORKING + SPECIAL EVENTS
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:53f01484ea82315c2e0d259770babcc3
URL:http://graphqlconf2026.sched.com/event/53f01484ea82315c2e0d259770babcc3
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T173000Z
DTEND:20260519T175500Z
SUMMARY:Safely Merging Subgraphs in a Distributed World - Clarice Abreu & Rodrigo Jesus\, Brex
DESCRIPTION:In the rush to "break the monolith" through GraphQL Federation\, organizations can go too far and end up with an explosion of subgraphs. At scale\, this can lead to a different kind of pain: high operational overhead\, reliability issues\, and ultimately\, a degraded graph quality. This session explores how to pivot from "splitting" to "merging" without impacting the customer.\n The presentation will dive into the workflow developed by Brex to consolidate federated subgraphs safely and reliably\, covering:\n •⁠ ⁠The Why: Identifying the tipping point where service fragmentation hurts more than it helps.\n •⁠ ⁠The Strategy: A zero-downtime workflow for merging services covering code migration\, schema composition and traffic shifting\n •⁠ ⁠Reliability: How to ensure schema integrity and 0 customer impact during the transition.\n •⁠ ⁠Outcomes: How the consolidation improved our graph design and simplified our overall architecture.\n \n Attendees will leave with a framework for evaluating when federation boundaries are hurting more than helping and a roadmap for executing a "subgraph smash" in their own federated infrastructure.
CATEGORIES:FEDERATION + DISTRIBUTED SYSTEMS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:ac9ecfab8b88cd2e0787f26ef22d1cef
URL:http://graphqlconf2026.sched.com/event/ac9ecfab8b88cd2e0787f26ef22d1cef
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T173000Z
DTEND:20260519T175500Z
SUMMARY:Sponsored Session: Federation\, Reversed: A Consumer-First Future with Fission - David Stutt\, Wundergraph
DESCRIPTION:GraphQL Federation traditionally takes a bottom-up approach: individual service schemas are defined first\, and the final federated API emerges from the federation algorithm. However\, GraphQL's strength is enabling APIs that are designed around what consumers actually need. A bottom-up model can make it harder to intentionally design the federated API surface. In this talk we introduce Fission\, a new federation algorithm that enables a consumer-first\, design-driven approach to federated GraphQL APIs. We'll show how Fission lets teams start with API design and derive the services therefrom—flipping the traditional federation paradigm on its head. And best yet: we'll explain using cake.
CATEGORIES:FEDERATION + DISTRIBUTED SYSTEMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:c8e90ab44520b08fdf3eb7daf79864c3
URL:http://graphqlconf2026.sched.com/event/c8e90ab44520b08fdf3eb7daf79864c3
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T173000Z
DTEND:20260519T175500Z
SUMMARY:React Server Components Vs. GraphQL - Jordan Eldredge\, Meta
DESCRIPTION:React Server Components (RSC) and GraphQL have considerable overlap in the problems they seek to solve. This makes them competitors in some scenarios.\n \n In this talk we’ll recount the origins of RSCs at Meta as a prototype within the Relay GraphQL client\, discuss how to choose between the two technologies\, and end with an exploration of architectures in which they both might reasonably coexist moving forward.
CATEGORIES:SERVERS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:ac1946c42298b0ddfaed06e7abdf4776
URL:http://graphqlconf2026.sched.com/event/ac1946c42298b0ddfaed06e7abdf4776
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T180500Z
DTEND:20260519T183000Z
SUMMARY:Big Graphs\, Tiny Contexts: Dev Tools for Agents - Stephen Spalding & Kavitha Srinivasan\, Netflix
DESCRIPTION:How do you make one of the world's largest federated graphs accessible to token-constrained LLM minions?\n \n With hundreds of teams contributing to or consuming GraphQL APIs at Netflix\, good tools are critical. Today\, our GraphQL platform supports engineers across the entire dev lifecycle. However\, the nature of developer tooling is rapidly changing.\n \n It’s no longer enough to have a pretty UI if LLMs can’t access it—”agent-friendly” is now table stakes. \n \n In this talk\, we'll discuss how our tools have adapted to expose agent-friendly interfaces\, allowing agents to seamlessly interact with and utilize them for exploring the graph\, building queries\, designing schemas\, and more. \n \n Finally\, how can we leverage the power of AI within the tools themselves? We’ll discuss techniques for superpowering GraphQL tooling via focussed agents with guardrails and feedback loops\, increasing accuracy and trust.
CATEGORIES:AI AND LLMS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:f315e1c9a4e9db5eb0bf9bf0b8fb7a4c
URL:http://graphqlconf2026.sched.com/event/f315e1c9a4e9db5eb0bf9bf0b8fb7a4c
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T180500Z
DTEND:20260519T181500Z
SUMMARY:Lightning Talk: The 40\,000-field Query: Optimizations for Gigantic High-QPS Operations - Gary Zeng\, Meta
DESCRIPTION:Parsing a GraphQL query generally has negligible cost. But what happens your front page query has millions of QPS\, 10s of thousands of fields\, and there are hundreds of versions of the query? At Meta\, we've found that parsing becomes a significant bottle neck under these constraints.\n \n In this talk\, we dive into server-side optimizations we built to handle persisted documents beyond simple LRU caches. We will cover:\n - Lazy fragment parsing. We delay parsing a fragment until the executor encounters a spread that matches the fragment's type\, using offset maps to jump through the document text.\n - Traffic based caching. We cache pre-parsed structures taking into consideration CPU savings and memory cost.\n - Fragment inlining to reduce overhead in the CollectFields step. \n \n Attendees leave with deep understanding of performance considerations of GraphQL execution engines. I hope other GraphQL server implementations can consider adopting similar strategies to better serve a larger variety of traffic patterns.
CATEGORIES:PRODUCTION INSIGHTS - HUGE SCALE
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:e87d74fcfd6a5bf55d7169e394799f63
URL:http://graphqlconf2026.sched.com/event/e87d74fcfd6a5bf55d7169e394799f63
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T180500Z
DTEND:20260519T183000Z
SUMMARY:Service-to-service GraphQL: The New Sweet Spot! - Mark Larah\, Yelp
DESCRIPTION:Using GraphQL for service-to-service communication has historically been....frowned upon. Certainly\, in isolation\, there are compelling alternatives (gRPC\, thrift\, good ol' REST).\n \n But in the age of LLMs and SDUI (Server Driven UI)\, there's lot of data whizzing around microservices. Does GraphQL fit this use case? I'll argue...yes!\n \n You could define your data models with a combination of REST\, gRPC\, GraphQL\; each layer gets a different transport protocol. Or we could consolidate on GraphQL.\n \n This talk lays out why and when this makes sense\, and what patterns are helpful to achieve this.\n \n (ATTN: CFP reviewers -- fwiw the title is referencing https://productionreadygraphql.com/blog/2020-05-14-sweetspot)
CATEGORIES:SERVERS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:518a5297b05f1d7d0807bd1638308a1c
URL:http://graphqlconf2026.sched.com/event/518a5297b05f1d7d0807bd1638308a1c
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T182000Z
DTEND:20260519T183000Z
SUMMARY:Lightning Talk: GraphQL: The Internal Agentic API - Christopher Chedeau\, Meta
DESCRIPTION:How do you expose all the internal tools to the Agents is the question everyone is asking today. Turns out we already expose all the things people can do with our internal tools at Meta through GraphQL and LLM Agents are now able to write GraphQL queries\, so... come to this talk to see how both work wonderfully together!
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:a9f12ca7a20cde46521324c5665fb96b
URL:http://graphqlconf2026.sched.com/event/a9f12ca7a20cde46521324c5665fb96b
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T184000Z
DTEND:20260519T190500Z
SUMMARY:From Query to Conversation: GraphQL as an AI Interface Layer - Hugh Nguyen & Adam Conrad\, Meta
DESCRIPTION:How do you teach AI to navigate GraphQL schemas with thousands of fields? At Meta\, we built an AI system that dynamically discovers and loads subschemas on-demand\, enabling natural language interactions with complex enterprise APIs.\nThis talk shares hard-won lessons from building production AI that performs real-time schema exploration\, manages dynamic subschema composition\, and generates sophisticated GraphQL operations at Meta's scale.\nKey Topics:- Dynamic schema discovery from user intent- On-demand subschema loading architecture (@require_graphql_subschemas directive)- Teaching LLMs GraphQL type relationships and dependencies- Performance optimizations for real-time schema introspection- What failed and why certain approaches don't scale\nLessons from Production:- Schema design principles that work better with AISecurity considerations for AI-driven schema access- Operational challenges and monitoring strategies- Attendees leave with battle-tested patterns for conversational GraphQL systems\, specific techniques for dynamic schema loading\, and honest insights about what didn't work along the way.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:da2cf64328dde7c25f0ca728a21fa034
URL:http://graphqlconf2026.sched.com/event/da2cf64328dde7c25f0ca728a21fa034
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T184000Z
DTEND:20260519T190500Z
SUMMARY:The State of GraphQL Agent Skills - Dale Seo\, Apollo GraphQL
DESCRIPTION:AI coding agents are now a daily reality for GraphQL developers\, yet there's a persistent gap between what agents can do and what they actually know. Without guidance\, they generate anonymous queries\, skip variables\, rely on deprecated patterns\, and miss conventions experienced teams consider obvious. Every conversation starts from zero. Agent Skills are an emerging answer: a lightweight\, open format for encoding expertise that agents can automatically apply. In a short time\, the community has begun building Skills that teach everything from schema usage to client caching\, and the ecosystem is evolving fast. This talk surveys the current state of GraphQL Agent Skills: what they are\, how they're authored\, how they plug into AI tools and workflows\, and how they complement MCP. As the creator and maintainer of Apollo Skills\, I'll share what we've learned building and shipping them. Through real-world examples\, we'll see how Skills help agents design a schema safely\, write the right operations\, and recover from mistakes. We'll examine design trade-offs\, emerging patterns\, and open challenges still ahead. You'll leave knowing how to make your graph work better with AI agents.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:f6c386dc9b66f92219c5f36fc59c5a45
URL:http://graphqlconf2026.sched.com/event/f6c386dc9b66f92219c5f36fc59c5a45
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T184000Z
DTEND:20260519T190500Z
SUMMARY:Shopify's Breadth-First Bet: Rethinking GraphQL Execution - Greg MacWilliam\, Shopify
DESCRIPTION:Pretty much every major GraphQL execution implementation follows the same pattern: depth-first traversal. But the spec doesn’t require this. At Shopify\, we challenged that status quo and rewrote GraphQL execution to run breadth-first.\n \n Here’s how it works: instead of running a field resolver repeatedly across each object in a list during its depth pass\, we execute each field resolver only once per selection with a complete breadth of objects spanning the response. The napkin math is compelling—5 fields resolved across a list of 100 objects running depth-first will produce 500 resolver calls + lazy promises\, while running breadth-first will only produce 5. We’ve seen dramatic results with some large list queries shaving many seconds off their end-to-end response times.\n \n This talk will cover:\n \n * Why depth-first has hidden costs that scale linearly.\n * How breadth-first inverts the cost model.\n * Why dataloaders are a hack.\n * The trade-offs we accepted.\n * How we're incrementally migrating to breadth execution.\n \n If you've ever been concerned that CPU-bound GraphQL performance doesn't scale well\, this talk offers a new perspective—and proof that challenging conventions can pay off.
CATEGORIES:PERFORMANCE
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:d1fc287ccb02b3ea18262565aaded6cf
URL:http://graphqlconf2026.sched.com/event/d1fc287ccb02b3ea18262565aaded6cf
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T191500Z
DTEND:20260519T194000Z
SUMMARY:Sponsored Session: Closing the Loop: How GraphQL Gives Coding Agents Eyes on What Actually Matters - Michael Staib\, Chillicream
DESCRIPTION:Coding agents are reshaping how we build software. Implementing features\, refactoring systems\, and shipping changes at a pace unthinkable 6 months ago. But to be successful with agents you need the right feedback loop. One that guides your agent to success\, not into the spiral of death. Ask Claude to add a review system to your product API. Without knowing what's in use\, it might reshape your types\, move fields\, and break your deployed clients because it is missing a crucial feedback loop of what's in use in your clients. GraphQL changes this. Every client operation explicitly declares the exact fields and types it needs. That gives you something rare: field-level usage data across your entire consumer base. Not endpoint hits\, but actual demand\, broken down to the individual field. When coding agents can access this data\, they stop guessing. Evolve your schema grounded in reality\, not assumptions. This talk shows how GraphQL's inherent usage visibility and the rise of coding agents create a feedback loop that didn't exist before. And why it matters for anyone building APIs that need to evolve fast.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:a45eba5992e9862dfb097c03c0041374
URL:http://graphqlconf2026.sched.com/event/a45eba5992e9862dfb097c03c0041374
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T191500Z
DTEND:20260519T194000Z
SUMMARY:An Alternative To JSON Responses: Argo in WhatsApp - Kevin Gorham\, Meta
DESCRIPTION:Optimizing wire size is in WhatsApp's DNA. In the early days\, we transformed verbose XML into a compact binary protocol (WAP) that helped us serve users worldwide on constrained networks. Now\, as we migrate to GraphQL\, we faced a new challenge: JSON responses were 30% larger than WAP-encoded equivalents. This talk tells the story of how we solved that problem—by leveraging GraphQL's type system to outperform not just JSON\, but WAP and protobufs too. We'll share the technical approach (implementing Argo)\, the results (27-50% smaller responses)\, and why this represents the next evolution in efficient data transfer for Meta's apps.
CATEGORIES:PERFORMANCE
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:da4024be753754cfdcf532eda0bc53fb
URL:http://graphqlconf2026.sched.com/event/da4024be753754cfdcf532eda0bc53fb
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T191500Z
DTEND:20260519T194000Z
SUMMARY:The Internal Lens: GraphQL Gateways From a Different Axis - Angel Svirkov\, trivago
DESCRIPTION:GraphQL is often framed around multiple clients\, external consumers\, and solving over/under-fetching. But what if you have one client\, fragmented internal APIs\, and colleagues as your consumers? This talk explores that different axis—and why GraphQL still matters.\n \n At trivago\, we built a second GraphQL Gateway to unify internal services. What started as admin tooling became something more: a lens that surfaced hidden system relationships\, a catalyst for cross-team collaboration\, and now a foundation for AI-assisted tooling enriched with human-written business context.\n \n This session shares honest lessons from six years of running an internal-facing gateway. You'll hear how we unified services without imposing upstream requirements\, fostered collaboration across previously siloed teams\, and designed audit logging around user intent—not just technical calls. Whether or not this specific approach fits your context\, you'll leave with a broader perspective: there's more to GraphQL than its typical framing suggests.
CATEGORIES:PRODUCTION INSIGHTS - REGULAR SCALE
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:07dd652a752f9eab711c7e87048cb2d6
URL:http://graphqlconf2026.sched.com/event/07dd652a752f9eab711c7e87048cb2d6
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T194000Z
DTEND:20260519T211000Z
SUMMARY:Lunch
DESCRIPTION:\n
CATEGORIES:BREAKS + NETWORKING + SPECIAL EVENTS
LOCATION:Foyer + Bistro 880\, Fremont\, CA\, USA
SEQUENCE:0
UID:9653ba6ecb6fdb9103d2008815483fef
URL:http://graphqlconf2026.sched.com/event/9653ba6ecb6fdb9103d2008815483fef
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T211000Z
DTEND:20260519T212000Z
SUMMARY:Lightning Talk: Schema Composition Without Federation - Matt Mahoney\, Meta
DESCRIPTION:In a world where context is limited\, what do we need from GraphQL to build composable\, type safe products?
CATEGORIES:CLIENTS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:f774597408f7258ec847ab837fac41e9
URL:http://graphqlconf2026.sched.com/event/f774597408f7258ec847ab837fac41e9
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T211000Z
DTEND:20260519T213500Z
SUMMARY:Lower Latency With Streaming GraphQL - Rob Richard\, 1stDibs
DESCRIPTION:Learn how to lower latency in your applications by streaming your GraphQL responses using the @defer and @stream directives. Learn the trade-offs of when to use these new directives and how they differ from GraphQL Subscriptions. \n \n @defer and @stream have been in development for some time now and have gone through many iterations. Learn about the motivation behind these changes and how they will lead to scalable GraphQL servers and efficient clients.
CATEGORIES:PERFORMANCE
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:b3acfcd8ef988b2c4826c1b762ff232a
URL:http://graphqlconf2026.sched.com/event/b3acfcd8ef988b2c4826c1b762ff232a
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T211000Z
DTEND:20260519T213500Z
SUMMARY:Teach Yourself GraphQL in 2026: An Anti-blueprint - Jeff Auriemma\, Apollo
DESCRIPTION:After eleven years as an open source technology\, GraphQL has never had a more favorable learning curve. Clearer mental models\, better educational materials\, and a deeper collective understanding of best practices have transformed the “wild west” of 2015 to a much more manageable landscape today.\n \n You and your team are unique\, so rather than a one-size-fits-all blueprint I thought I’d present a practical guide to teaching yourself GraphQL in 2026. We’ll examine how beginners typically build their first mental model of GraphQL\, the most common misconceptions\, and the key design questions they encounter early. Special attention will be paid to different modalities: schema-first vs. code-first\, schema design principles\, common pitfalls when considering enums\, the proper use of fragments\, and security and performance by default.\n \n Attendees will leave with a conceptual roadmap for self-study\, a recipe book for context engineering in their agent\, and an understanding of the major decision points along the journey ahead.
CATEGORIES:TOOLING + DX + TESTING + DOCUMENTATION
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:09f9a62b715fa18505ba2fca81f82314
URL:http://graphqlconf2026.sched.com/event/09f9a62b715fa18505ba2fca81f82314
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T212500Z
DTEND:20260519T213500Z
SUMMARY:Lightning Talk: Making GraphQL Fun for the Backend Too - Stephen Haberman\, Homebound
DESCRIPTION:GraphQL is a technology well-loved by frontend engineers\, but often leaves backend engineers struggling with boilerplate code and N+1 performance issues. This talk introduces Joist\, a "GraphQL-first" TypeScript ORM that uses codegen\, resolver scaffolding\, and deep dataloader integration to bring Rails-level productivity to Homebound's 500+ table GraphQL/Postgres majestic monolith.
CATEGORIES:TOOLING + DX + TESTING + DOCUMENTATION
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:5004748545abbc5c1dfffd50eeb14b0b
URL:http://graphqlconf2026.sched.com/event/5004748545abbc5c1dfffd50eeb14b0b
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T214500Z
DTEND:20260519T221000Z
SUMMARY:Bringing GraphQL Natively To Relational Databases With AI - Shashank Gugnani\, Oracle
DESCRIPTION:GraphQL offers a popular way for developers to access and interact with data. However\, integrating GraphQL with enterprise databases often requires custom middleware\, complex resolvers\, and maintenance overhead. With Oracle AI Database 26ai\, this changes: developers can now use GraphQL queries natively in the database\, leveraging automated schema inference and built-in parsing with no loss of performance or scalability.\n \n In this session\, we will demonstrate Oracle’s first-class GraphQL integration\, including the new table function that lets you run GraphQL queries as native SQL. We will showcase:\n \n - How to map and query relational data with GraphQL\, with built-in features for joins\, predicates\, ordering\, & calculations.\n - How LLMs can generate valid GraphQL queries from natural language\, making API access approachable\, and why targeting GraphQL via LLMs often delivers safer\, better experiences than translating NL to SQL.\n \n Whether you’re an architect modernizing data APIs or a developer working with complex schemas\, this session will help you take advantage of the best of both relational databases and the GraphQL ecosystem\, with added automation from today’s AI advancements.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:cfb959d4eb1cc2c2a197eebd6cbfd386
URL:http://graphqlconf2026.sched.com/event/cfb959d4eb1cc2c2a197eebd6cbfd386
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T214500Z
DTEND:20260519T215500Z
SUMMARY:Lightning Talk: Resolvers Everywhere: Rethinking Client and Server Boundaries in GraphQL - Janette Cheng\, Meta
DESCRIPTION:In GraphQL\, a resolver is defined as “the internal function for determining the resolved value of a field.” Traditionally\, resolvers live exclusively on the server—but should they? Many teams find themselves either duplicating business logic on the client or pushing client-specific concerns into backend code when trying to treat server models as view models.\n \n This talk explores an alternative: client-side resolvers. With Relay Resolvers\, clients can define fields that combine and transform data locally. We'll walk through how they work and guidance for deciding when logic belongs on the server versus the client.
CATEGORIES:CLIENTS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:a819d5400df8820255e2c10069d82614
URL:http://graphqlconf2026.sched.com/event/a819d5400df8820255e2c10069d82614
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T214500Z
DTEND:20260519T221000Z
SUMMARY:Scaling Real-Time: Building Federated Subscriptions in Rust - Denis Badurina\, The Guild
DESCRIPTION:Our journey implementing federated GraphQL subscriptions in Hive Router\, a high-performance federation gateway written in Rust. Covering the architectural decisions and technical challenges we faced bringing real-time capabilities to a federated environment\, the engineering work required to support the full spectrum of subscription transports (WebSockets\, SSE\, Multipart HTTP and HTTP callbacks)\, and how Rust’s performance characteristics enabled us to handle subscription workloads at scale.
CATEGORIES:FEDERATION + DISTRIBUTED SYSTEMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:a31ba6e2e84a482857ebc4097d93c2aa
URL:http://graphqlconf2026.sched.com/event/a31ba6e2e84a482857ebc4097d93c2aa
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T220000Z
DTEND:20260519T221000Z
SUMMARY:Lightning Talk: Breaking up With Inputs (Without Breaking Your Users) - Laurin Quast\, The Guild
DESCRIPTION:Deprecating fields and removing them in GraphQL is tricky itself\, but tooling can help identifying such based on statically analysing operations or traffic. But\, deprecating inputs is a whole different challenge! Once clients start sending arguments or input object fields\, removing or changing them can break integrations in subtle ways\, as you do not know which fields might be used in the future and which ones might not\, especially if you are running GraphQL at scale. In this lightning talk we will explore possible options for making this whole process more safe in the present\, and dip into how it could look in the future!
CATEGORIES:SCHEMA DESIGN + EVOLUTION + GOVERNANCE
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:a7caf168c70c3f50d1805a1cb9e5119a
URL:http://graphqlconf2026.sched.com/event/a7caf168c70c3f50d1805a1cb9e5119a
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T222000Z
DTEND:20260519T224500Z
SUMMARY:Sponsored Session: Hands Off the Keyboard: An Introduction to Agentic Coding for GraphQL Developers - Erik Bylund\, Apollo GraphQL
DESCRIPTION:Every developer has the same instinct when working with AI: take over. Copy the output\, fix it by hand\, wonder why AI ""doesn't really work."" That instinct is the problem. When AI-generated code is wrong\, the fix isn't editing the code — it's improving the instructions that produced it. This talk teaches that discipline using Agent Skills — open-format markdown workflows — and the GraphQL SDLC as working context. We'll build skills for schema design\, resolvers\, testing\, and docs\, developing intuition for when to refine instructions versus when you've hit a model limitation. You'll leave with transferable techniques\, open-source GraphQL skills\, and the beginnings of your own agentic intuition.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:dded18c303b6caaf7d74b4a0f125cee5
URL:http://graphqlconf2026.sched.com/event/dded18c303b6caaf7d74b4a0f125cee5
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T222000Z
DTEND:20260519T224500Z
SUMMARY:Was It Worth It? Lessons from Implementing Two GraphQL Routers. In JavaScript and Rust - Arda Tanrıkulu\, The Guild
DESCRIPTION:The steps we took at implementing a GraphQL gateway first in JavaScript\, and following those steps in Rust again.Advantages of JavaScript and disadvantage of lack of diversity in the GraphQL Rust ecosystem.Is Rust worth? Is it just performance? How hard was it to rethink everything done in the JavaScript version?
CATEGORIES:FEDERATION + DISTRIBUTED SYSTEMS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:a8e4cd7263cbe0a48113eebf3b0a7606
URL:http://graphqlconf2026.sched.com/event/a8e4cd7263cbe0a48113eebf3b0a7606
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T222000Z
DTEND:20260519T224500Z
SUMMARY:The Invisible Fortress: Embedding Zero-Trust Governance in the Supergraph - Gaurav Singh & Sulbigar Shanawaz\, Capital One
DESCRIPTION:In high-stakes industries\, a GraphQL schema is more than a technical contract—it is a live map of your enterprise’s risk surface. For security teams\, schema modifications are often "black box" events that threaten data integrity. To scale safely\, we must move beyond manual gatekeeping to a Zero-Trust Supergraph where security is an invisible\, automated fortress.\n \n We will present a framework for Embedded Governance to bridge engineering and enterprise risk. Learn how to transform your graph's technical "menu" into a transparent Data Marketplace with radical observability\, ensuring built-in security and compliance.\n \n Attendees will learn to:\n - Navigate the Risk Primer: Translate GraphQL features (types\, fields\, directives) into risk language to build organizational trust.\n - Shift Security Left: Automate security with secure frameworks & replacing manual reviews.\n - Architect for Data Isolation: Use of fine grained access to manage entitlements and prevent unauthorized data exposure.\n - Harden the Control Plane: Reduce attack surface using technical strategies like disabling introspection and enforcing persisted query ownership.
CATEGORIES:SECURITY
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:c1415e7ff525257cfa96ef7daa49a11b
URL:http://graphqlconf2026.sched.com/event/c1415e7ff525257cfa96ef7daa49a11b
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T224500Z
DTEND:20260519T230500Z
SUMMARY:Break
DESCRIPTION:\n
CATEGORIES:BREAKS + NETWORKING + SPECIAL EVENTS
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:78e807e1dbc29c2667c1c12e9a4dfb3b
URL:http://graphqlconf2026.sched.com/event/78e807e1dbc29c2667c1c12e9a4dfb3b
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T230500Z
DTEND:20260519T233000Z
SUMMARY:Simplifying MCP Tool Sprawl With GraphQL - Roy Derks\, IBM
DESCRIPTION:As teams adopt the Model Context Protocol (MCP)\, they often run into a new problem: tool sprawl. Every backend API turns into its own MCP server\, each with separate schemas\, auth\, versioning\, and deployment concerns. What starts as a clean integration quickly becomes hard to manage. In this talk\, I'll show how GraphQL can act as a unifying layer for MCP using GraphQL capabilities like schema introspection and persisted documents. By exposing multiple backend services through a single GraphQL API and connecting it via one MCP server\, LLMs gain access to a rich\, strongly typed interface without an explosion of tools. We’ll walk through a practical architecture and share patterns for keeping MCP systems scalable\, discoverable\, and governable beyond early experiments.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:f297e99f14761e6bb70006c8fe641692
URL:http://graphqlconf2026.sched.com/event/f297e99f14761e6bb70006c8fe641692
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T230500Z
DTEND:20260519T233000Z
SUMMARY:The Case Against __typename - Sabrina Wasserman\, Meta Platforms Inc.
DESCRIPTION:The GraphQL Schema Documentation (https://graphql.org/learn/schema/) defines the __typename field as “a special meta-field that automatically exists on every Object type and resolves to the name of that type\, providing a way to differentiate between data types on the client.” At Meta\, we’ve learned that relying on __typename to delineate type on the client can actually be a foot-gun. Querying __typename for every object is clunky\, increases payload size\, creates backward compatibility issues for older\, unupgradable clients\, and isn’t sufficient for handling complex schema cases like nested abstract types.\n \n In this talk\, I’ll walk through specific scenarios where __typename falls short\, and demonstrate how using a new metadata field\, `is_fulfilled`\, is better-suited to writing more robust GraphQL clients.
CATEGORIES:CLIENTS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:7d3a7e26a24ad1ef28c0c9a913dd69bb
URL:http://graphqlconf2026.sched.com/event/7d3a7e26a24ad1ef28c0c9a913dd69bb
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T230500Z
DTEND:20260519T233000Z
SUMMARY:Caching Deep Dive: The Ultimate Way To Speed up Your GraphQL API - Uri Goldshtein\, The Guild
DESCRIPTION:What we will cover:\n The "All-or-Nothing" Barrier: We'll analyze the limitations of traditional Document Caching in GraphQL. We will explain why a single personalized field or a volatile "live" value can invalidate an entire response\, leading to low cache hit rates and overloaded origin servers.\n \n Partial Query Caching (PQC) Architecture: We will introduce a granular approach to caching. You'll learn how to decompose complex queries into atomic components\, separating static fragments from dynamic ones within the same request to dramatically boost cache efficiency.\n \n The Power of the Edge: We'll discuss the benefits of moving the "split-and-merge" logic to the Edge. We will explain how an intelligent Gateway can manage this complexity close to the user\, saving expensive compute resources at the origin and reducing latency.\n \n The Next Frontier: PQC meets @defer: To wrap up\, we'll demonstrate how combining caching with the GraphQL @defer directive allows us to return cached fragments in milliseconds while streaming the remaining dynamic parts as they resolve.
CATEGORIES:TOOLING + DX + TESTING + DOCUMENTATION
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:76ddf2f65ecfd5036ad78bed7f631061
URL:http://graphqlconf2026.sched.com/event/76ddf2f65ecfd5036ad78bed7f631061
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T234000Z
DTEND:20260520T000500Z
SUMMARY:Shifting Instagram Development Towards Monolith Server Via Federated Schema - Xiao Han\, Chi Chan\, Deepak Singh\, Kristina Kamendova & Anirudh Padmarao\, Meta
DESCRIPTION:Instagram is moving from a Python monolith to a PHP monolith. Come find out how we leverage GraphQL to define a single API across both monoliths to power major product migrations (e.g. Stories\, Reels\, Threads) and facilitate incremental development shifts. \n \n Meta’s architectural philosophy favors federation to support a monolithic architecture over traditional microservices.
CATEGORIES:FEDERATION + DISTRIBUTED SYSTEMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:db3a6a6b83a936623e0ac45938bbb7ef
URL:http://graphqlconf2026.sched.com/event/db3a6a6b83a936623e0ac45938bbb7ef
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T234000Z
DTEND:20260520T000500Z
SUMMARY:Scaling GraphQL on AWS: Production Architecture for High-Volume Data Systems - Aishwarya Tirumala\, Amazon
DESCRIPTION:This presentation explores production-scale GraphQL architecture on AWS\, demonstrating how to handle millions of requests and complex data operations at enterprise scale. Drawing from real-world pricing systems that serve thousands of internal clients\, we'll examine the architectural decisions behind building resilient\, high-performance GraphQL services using AWS AppSync\, Lambda\, and DynamoDB. The session covers critical\n production considerations including query optimization strategies\, caching layers\, connection pooling\, and event-driven architectures that power real-time notifications at scale. Attendees will learn how GraphQL simplifies data access across massive datasets while maintaining performance and reliability. We'll discuss scaling patterns\, monitoring strategies\, and lessons learned from operating GraphQL services that handle billions of daily operations across global marketplaces. This technical deep-dive is designed for engineers interested in understanding how to architect and operate GraphQL systems at huge scale\, with practical insights from Amazon's production environments.
CATEGORIES:PRODUCTION INSIGHTS - HUGE SCALE
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:6e3a9d8b4e0444ae042685debe3d45ff
URL:http://graphqlconf2026.sched.com/event/6e3a9d8b4e0444ae042685debe3d45ff
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260519T234000Z
DTEND:20260520T000500Z
SUMMARY:Inverse Conway Maneuver\, with GraphQL - Sam Deng\, Zillow Group
DESCRIPTION:Left to its own devices\, software companies ship its own team structure (Conway’s Law). Scale leads to data silos\, unclear ownership\, and an incoherent GraphQL schema. Zillow pushes back against this natural entropy.\nOrganizing data post hoc is untenable — trying to keep up with the legions of changing SaaS systems is a losing battle. The schema must be organized at the data producer end. This is the story of Zillow’s journey to bring order to a chaotic GraphQL schema. Starting with its most critical data domains\, listings and customers\, Zillow has built a canonical data schema in its federated graph\, that aligns its multiple business units and streamlines data sharing.
CATEGORIES:SCHEMA DESIGN + EVOLUTION + GOVERNANCE
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:0fc60882958e48a56978dedf3c4b0e17
URL:http://graphqlconf2026.sched.com/event/0fc60882958e48a56978dedf3c4b0e17
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T001500Z
DTEND:20260520T004000Z
SUMMARY:Beyond HTTP 200: Observability With GraphQL - Kamil Kisiela\, The Guild
DESCRIPTION:To run GraphQL in production with confidence\, we need more than just uptime checks and HTTP 200 - we need deep visibility into the graph itself.\n \n In this talk\, we will explore how to implement the three pillars of observability: traces\, metrics\, and logs - specifically for GraphQL. \n \n We'll explore OTel and GraphQL\, allowing you to trace requests from the gateway down to individual Federation subgraphs and deeper.\n \n Finally\, we will look at how to leverage dedicated tooling like Hive Console to make sense of this data.
CATEGORIES:OBSERVABILITY + TELEMETRY + TRACING
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:616a26da6957b595a0bc10905cff2720
URL:http://graphqlconf2026.sched.com/event/616a26da6957b595a0bc10905cff2720
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T001500Z
DTEND:20260520T004000Z
SUMMARY:Understanding Your Graph\, One Hash at a Time - Jens Neuse\, WunderGraph
DESCRIPTION:Have you ever wished you could better understand how the entities in your graph behave over time? Are they cacheable? How often are they updated? How often are they accessed? What is the distribution of keys?\n \n The primitives of GraphQL federation are simple: Entities with keys to uniquely identify them\, distributed across multiple services.\n \n The story they tell? It's a fascinating one\, but nobody talks about it. Until now.\n And it's not even that complicated\, just a couple of hashes and we're able to learn more about your data than you ever thought possible.
CATEGORIES:OBSERVABILITY + TELEMETRY + TRACING
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:a4dacb595dba7239ed2593ba0d6877a6
URL:http://graphqlconf2026.sched.com/event/a4dacb595dba7239ed2593ba0d6877a6
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T001500Z
DTEND:20260520T004000Z
SUMMARY:Incrementally Adopting GraphQL. The Holy Grail? - Robert Balicki\, Pinterest
DESCRIPTION:Incrementally adopting GraphQL is hard. The shape of the data differs between REST and GraphQL. Components that were designed for one don't automatically work with the other. And migrating by making multiple network requests can worsen performance unacceptably. And big bang refactors? Well\, if you believe those will be successful\, I have some oceanfront real estate in Nebraska to sell you. \n \n Is there a better way? Well\, what if instead of contorting our frontends for multiple backends\, we gave our non-GraphQL backend one crucial property: generated queries that fetch exactly the right data. Then\, migrating from one backend to another is as simple (and stress-free) as running an experiment and ramping up a decider!\n \n And Isograph makes that easy! Isograph is an opinionated\, compiler-driven framework that makes it easy to build stable\, performant data-driven apps\, and it generates queries for just the data needed by a given screen. And crucially\, it can generate multiple different versions of the same query: GraphQL\, SQL\, whatever your heart desires.\n \n Finally\, adopting GraphQL can be simple\, stress-free\, and incremental!
CATEGORIES:PRODUCTION INSIGHTS - REGULAR SCALE
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:d015ee04513e8e5aaea699e1b5a46d75
URL:http://graphqlconf2026.sched.com/event/d015ee04513e8e5aaea699e1b5a46d75
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T150000Z
DTEND:20260521T000000Z
SUMMARY:Registration + Badge Pick-up
DESCRIPTION:\n
CATEGORIES:REGISTRATION + BADGE PICK-UP
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:3a5ecfdd174a02096c1b685a29c78958
URL:http://graphqlconf2026.sched.com/event/3a5ecfdd174a02096c1b685a29c78958
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T150000Z
DTEND:20260521T003000Z
SUMMARY:Solutions Showcase
DESCRIPTION:In order to facilitate networking and business relationships at the event\, you may choose to visit a third party’s booth or access sponsored content. You are never required to visit third party booths or to access sponsored content. When visiting a booth or participating in sponsored activities\, the third party will receive some of your registration data. This data includes your first name\, last name\, title\, company\, address\, email\, standard demographics questions (i.e. job function\, industry)\, and details about the sponsored content or resources you interacted with. If you choose to interact with a booth or access sponsored content\, you are explicitly consenting to receipt and use of such data by the third-party recipients\, which will be subject to their own privacy policies.
CATEGORIES:SOLUTIONS SHOWCASE
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:f61ca94d4c5127803f29b6b21c9ef493
URL:http://graphqlconf2026.sched.com/event/f61ca94d4c5127803f29b6b21c9ef493
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T160000Z
DTEND:20260520T170000Z
SUMMARY:GraphQL All Hands Meeting
DESCRIPTION:Help shape the future of GraphQL! Join GraphQL Foundation Board Members\, TSC Members\, and other community leaders for a public meeting about goals and priorities for 2027\, and help us celebrate 2026's wins.
CATEGORIES:ALL HANDS MEETING
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:1ff1e6a99e43cbc79ee48062ea156dfe
URL:http://graphqlconf2026.sched.com/event/1ff1e6a99e43cbc79ee48062ea156dfe
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T170000Z
DTEND:20260520T171500Z
SUMMARY:Break
DESCRIPTION:\n
CATEGORIES:BREAKS + NETWORKING + SPECIAL EVENTS
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:13605eb210a123441a11669fe6b3b546
URL:http://graphqlconf2026.sched.com/event/13605eb210a123441a11669fe6b3b546
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T171500Z
DTEND:20260520T174000Z
SUMMARY:When GraphQL Gets Expensive: Performance & Cost Patterns in Production Serverless Architectures - Harpreet Siddhu\, AWS Community Builder & Shravanth Gowda Venkatesh\, Independent Researcher
DESCRIPTION:GraphQL simplifies client development through flexible\, expressive data queries. However\, in serverless production environments\, that flexibility can quietly increase latency and infrastructure cost.\n \n In AWS-based architectures using Lambda\, DynamoDB\, Aurora Serverless\, and distributed services\, resolver design and query structure directly impact execution time\, cold starts\, and overall spend. Unlike REST\, GraphQL shifts cost dynamics to query complexity and resolver fan-out\, and often in ways teams don’t anticipate until production traffic scales.\n \n This session examines common performance and cost anti-patterns in serverless GraphQL systems\, including N+1 resolver cascades\, unbounded query depth\, over-fetching\, and inefficient resolver fan-out. We’ll explore how these patterns affect Lambda duration\, concurrency\, and downstream data stores.\n \n Attendees will learn practical mitigation strategies such as batching with DataLoader\, caching and persisted queries\, query complexity limits\, schema guardrails\, and observability techniques to detect bottlenecks early.
CATEGORIES:PERFORMANCE
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:0951f42a2162567dc11112fc2930efa6
URL:http://graphqlconf2026.sched.com/event/0951f42a2162567dc11112fc2930efa6
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T171500Z
DTEND:20260520T174000Z
SUMMARY:Screens on Shuffle: How Netflix Scales Server‑Driven\, Ever‑Changing Pages - Sreekanth Ramakrishnan\, Netflix
DESCRIPTION:How do you power a product where every page layout\, module\, and slice of content can change daily—across hundreds of millions of devices—without shipping a new client every time? In this talk\, we’ll dive into how Netflix evolved its GraphQL APIs from traditional “data fetching” into a server‑driven UI platform\, enabling rapid product innovation and page updates without requiring app releases across a massive device ecosystem. We’ll walk through the architecture that lets servers describe dynamic page structure and behavior\, how those contracts scale across many product surfaces and experiments\, and the performance and reliability lessons we learned operating this at Netflix scale. When we built this system\, we found almost no public examples of similar patterns\, so this session is intentionally practical: we’ll share concrete schema patterns\, client rendering strategies\, and tips you can apply to your own feeds\, homepages\, and highly dynamic experiences—whether you’re working at Netflix scale or just starting to stretch GraphQL beyond CRUD.
CATEGORIES:SCHEMA DESIGN + EVOLUTION + GOVERNANCE
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:384700fc44d299d25a6b73b38fa38870
URL:http://graphqlconf2026.sched.com/event/384700fc44d299d25a6b73b38fa38870
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T171500Z
DTEND:20260520T172500Z
SUMMARY:Lightning Talk: GraphQLShield: CWE-Aware Defense in Depth for GraphQL APIs in Go - Ravi Sastry Kadali\, Open Source Contributor
DESCRIPTION:GraphQL APIs face a unique threat landscape: deeply nested queries cause resource exhaustion\, introspection exposes entire schemas\, and mutation variables carry injection payloads past traditional WAFs. Yet most Go-based GraphQL servers ship with zero security middleware between HTTP and resolver execution.\n\nI introduce GraphQLShield\, an open-source Go middleware bringing defense-in-depth to GraphQL APIs through three layers: (1) Static schema analysis detecting cyclic types\, missing depth limits\, and sensitive field exposure before deployment\; (2) Runtime CWE-aware input sanitization catching SQL injection\, XSS\, command injection\, path traversal\, and NoSQL injection in GraphQL variables — bridging go-safeinput’s MITRE CWE Top 25 coverage to GraphQL\; and (3) Resolver code auditing inspired by gosec and cryptoguard-go flagging insecure crypto\, hardcoded secrets\, and missing auth checks.\n\nA quick demo shows GraphQLShield intercepting 7 attack vectors against a gqlgen API\, from SQL injection in mutation variables to depth-based DoS\, while legitimate requests pass cleanly. Attendees leave with a zero-dependency Go library covering 14 CWE vulnerability classes across static and runtime analysis.\n\n
CATEGORIES:SECURITY
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:730a36f1934e8c81b852400070bf08d3
URL:http://graphqlconf2026.sched.com/event/730a36f1934e8c81b852400070bf08d3
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T173000Z
DTEND:20260520T174000Z
SUMMARY:Lightning Talk: The @deprecated Journey: Five Stops From Schema Hint To Gateway Power - Nasser Abouelazm\, Bloomberg
DESCRIPTION:@deprecated is usually treated as a client-facing hint. However\, in federated GraphQL\, it can evolve into a set of patterns that shape governance\, runtime behavior\, observability\, and even gateway planning. In this lightning talk\, I’ll take @deprecated on a five-stop journey across the federation lifecycle — 1) schema hint\, 2) schema shaping\, 3) runtime feedback\, 4) client-aware telemetry\, and 5) gateway power. I’ll close with a brief developer experience bonus — how structured deprecation metadata can feed code-gen/IDE tooling to suggest non-deprecated alternatives while queries are being written. The goal of the talk is to share a practical mental model and guardrails for keeping large federated graphs evolvable\, observable\, and safe.
CATEGORIES:SCHEMA DESIGN + EVOLUTION + GOVERNANCE
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:f211249285d7efe0eaacae39613604fa
URL:http://graphqlconf2026.sched.com/event/f211249285d7efe0eaacae39613604fa
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T175000Z
DTEND:20260520T181500Z
SUMMARY:GraphQL Meets LLMs & Agents: Building Production AI at Starbucks Scale - Sharon Gorla\, Starbucks
DESCRIPTION:GraphQL isn't just an API technology—it's the perfect foundation for AI agents and LLM-powered applications. At Starbucks\, we built GraphQL platforms at massive scale (180M+ queries/day\, 10\,000 stores\, 31M+ app users) before GenAI became mainstream. Now\, as we explore AI integration\, we're discovering that GraphQL provides fundamental advantages for AI that are impossible with REST.\n \n This talk explores the AI systems we're building on our existing GraphQL infrastructure:\n \n In-store AI assistant (planned for Order Engine GraphQL BFF)\n Mobile/web AI platform (exploring on Apollo Supergraph)\n On-call automation using Model Context Protocol (MCP) servers\n You'll learn how GraphQL reduces AI token costs by 75x\, enables zero-configuration AI tool discovery\, provides built-in guardrails through type systems\, and why federation is the perfect architecture for enterprise AI agents. Real demos\, proven patterns\, lessons from building GraphQL at scale.
CATEGORIES:AI AND LLMS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:aa2e1bf3562603a5629f2c7527b40d92
URL:http://graphqlconf2026.sched.com/event/aa2e1bf3562603a5629f2c7527b40d92
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T175000Z
DTEND:20260520T181500Z
SUMMARY:Modern Apollo Client React - Brennen Davis\, Lease End
DESCRIPTION:Use Apollo Client v4 in React with Tanstack Router. \n \n We’ll be using GraphQL code generation from your schema\, preloading data at the router level\, optmistic updates\, and using Apollo’s cache to eliminate unnecessary refetching and rerenders. You’ll see how smart cache usage and colocating queries lets components read data directly where they need it which will reduce prop drilling. The goal is to show how “modern” Apollo Client patterns fit naturally into today’s React architecture to create apps that feel both simpler to reason about and noticeably more performant.
CATEGORIES:CLIENTS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:9796b4572382a080bb79d9e38d49297d
URL:http://graphqlconf2026.sched.com/event/9796b4572382a080bb79d9e38d49297d
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T175000Z
DTEND:20260520T181500Z
SUMMARY:Sponsored Panel Discussion: The GraphQL Production Roundtable - Aileen Chen\, Airbnb; Clarice Abreu\, Brex; Stephen Spalding\, Netflix; Moderated by Jory Burson\, The Linux Foundation
DESCRIPTION:Large engineering organizations now run GraphQL at the center of their product stacks\, serving billions of requests across web\, mobile\, and internal clients. The questions have shifted accordingly. The interesting problems are no longer about whether to adopt GraphQL\, or how to write a resolver. They are about what it takes to operate GraphQL reliably\, evolve it safely\, and scale the humans who work on it.\n\nThis panel brings together engineers from companies running GraphQL in production at large scale to compare notes on the realities of that work. Each panelist has spent years operating a GraphQL gateway or federated graph that fronts hundreds of services and thousands of fields\, owned by dozens of teams. The goal of the session is a candid\, technical conversation about what has worked\, what has not\, and what they would do differently.\n\nThis session is intended for engineers and tech leads who already run GraphQL in production or are planning to\, and who want to hear from peers operating at similar or larger scale. Familiarity with GraphQL fundamentals is assumed. No introductory material will be covered.
CATEGORIES:PRODUCTION INSIGHTS - HUGE SCALE
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:df9f2a79c46a7e7d7cbb8d836152b198
URL:http://graphqlconf2026.sched.com/event/df9f2a79c46a7e7d7cbb8d836152b198
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T182500Z
DTEND:20260520T185000Z
SUMMARY:Semantic Introspection - Pascal Senn\, ChilliCream
DESCRIPTION:GraphQL's rich type system makes it an ideal foundation for agents to explore and work with APIs. \n The SDL provides the structure agents need to reason about capabilities and data. \n Queries let them retrieve information\, while mutations enable them to take action.\n \n In practice\, however\, production GraphQL schemas are often too large to fit in the context window and difficult to understand without additional context.\n So what if agents could interact with any GraphQL API in a generic\, reliable way?\n In this session\, we'll look at the challenges of agentic interactions with GraphQL and how semantic introspection could unlock a new way for agents to navigate the schema and interact with GraphQL APIs more reliably.
CATEGORIES:AI AND LLMS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:c9691dd7eac4e819a180d7fd8dceb9b3
URL:http://graphqlconf2026.sched.com/event/c9691dd7eac4e819a180d7fd8dceb9b3
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T182500Z
DTEND:20260520T185000Z
SUMMARY:How GraphQL Helped Create Scalability and Stability in the Retirement Space. - Cameron Sechrist\, Stax.ai
DESCRIPTION:Retirement data is surprisingly complicated\, from provisions to participant payroll data to plan sponsor's unique needs. This presents a complicated and heavy requirement to fetch data points that provide the value\, and regulatory requirements\, that third party administrators require. GraphQL provides this\, it allows specific data to be fetched at each stage of the plan lifecycle\, without requiring us to fetch all of the data that we have. This allowed our platform to decrease latency by 30%\, load time by 1 second\, and server load by 50%.
CATEGORIES:PRODUCTION INSIGHTS - REGULAR SCALE
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:15844582a2e93253bcc811ddc782ecf5
URL:http://graphqlconf2026.sched.com/event/15844582a2e93253bcc811ddc782ecf5
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T182500Z
DTEND:20260520T185000Z
SUMMARY:Coordinated Access Control with @policy - Huang Minghe\, Booking.com
DESCRIPTION:At a company like Booking.com\, every sensitive field in the GraphQL schema has more than one team with a legitimate claim on it — Security\, Identity\, Legal\, Privacy\, Data Governance\, the Traffic Gateway\, the Federation Platform\, and the hundreds of domain teams that own the data itself. When that many stakeholders need to agree on what "authorized" means for a single field\, you don't have a security problem\; you have a coordination problem. And solving it as security only makes it worse.This talk shares how we turned that coordination problem into a contract using a single federation directive — @policy. Domain teams author rules for the data they own. Privacy and Identity contribute cross-cutting concerns. Other domains compose by reference instead of re-authoring. The router is the only place enforcement happens. One audit trail. No cross-team meetings.\nWhat you'll learn:Why multi-stakeholder access control is a coordination problem\, not a security one How @policy becomes the coordination contract between domain teams\, cross-cutting authorities\, and the federation platform&nbsp\;The single-enforcement-point + bounded-authorship + free-reuse architecture — and how it lets new teams adopt without coordination overhead
CATEGORIES:SECURITY
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:d6f305811f351a89a8f6b6cd506c4d87
URL:http://graphqlconf2026.sched.com/event/d6f305811f351a89a8f6b6cd506c4d87
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T190000Z
DTEND:20260520T192500Z
SUMMARY:GraphQL Embeddings: AI-Powered Dynamic Operations From Schema To IDE - Michael Watson\, Self
DESCRIPTION:What if your GraphQL API could understand what developers need and generate valid operations from plain English? This talk introduces graphql-embedding\, an open-source toolkit that parses GraphQL schemas into vector embeddings\, stores them in a vector store\, and uses a multi-agent LLM pipeline to generate validated GraphQL operations from natural language input.\n \n The architecture is fully modular: swap vector stores between PGLite for local development and PostgreSQL for production\, choose from Ollama\, OpenAI\, or Anthropic as LLM providers\, and extend with your own. A key design decision was bundling a lightweight embedding model directly in the package\, enabling local CPU inference with no external API calls\, cloud dependencies\, or GPU required. The entire pipeline to generate a operation works with small\, efficient models like QWen 2.5 running locally via Ollama.\n \n Everything ships as a VS Code extension called GraphQL Workbench\, putting schema embedding and natural language operation generation directly in the developer's workflow. All packages\, models\, and the extension are fully open source under the MIT license.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:07bc7cda6e90b92a6f217709a0ae1187
URL:http://graphqlconf2026.sched.com/event/07bc7cda6e90b92a6f217709a0ae1187
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T190000Z
DTEND:20260520T192500Z
SUMMARY:Stop Reviewing Schemas: How Intuit Made Developers Faster by Automating Governance - Oleks Bidiuk\, Intuit
DESCRIPTION:Abstract: Schema governance shouldn’t grind development to a halt or burn out graph stewardship teams. As Intuit’s Supergraph ecosystem grew\, our reliance on manual schema reviews created bottlenecks that slowed onboarding and frustrated developers. We knew we needed a better approach — so we built a hybrid governance model that puts Schema Co-Pilot directly into the developer workflow and transformed our "API Jedis" from gatekeepers into enablers.\n \n In this talk\, you’ll learn how we built real-time IDE linting\, AI-powered schema analysis\, and semantic “collision” detection to surface issues before code is even committed. With these tools in place\, onboarding timelines shrank from weeks to days\, and contributors now ship to the graph with speed and confidence.\n \n Who should attend: Platform engineers\, API architects\, and engineering leaders responsible for GraphQL governance and developer experience.\n \n Key takeaway: Governance isn’t about gatekeeping — it’s about building smart tools that help your teams move faster with confidence.
CATEGORIES:SCHEMA DESIGN + EVOLUTION + GOVERNANCE
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:a728ff82aae5134dd4c445ab1a0bc9d4
URL:http://graphqlconf2026.sched.com/event/a728ff82aae5134dd4c445ab1a0bc9d4
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T190000Z
DTEND:20260520T192500Z
SUMMARY:The Biggest Change To GraphQL Codegen in 10 Years - Eddy Nguyen\, The Guild & SEEK & Igor Kusakov\, Yelp
DESCRIPTION:GraphQL Codegen has been the go-to tool for generating types for GraphQL clients for over a decade. But as use cases grew\, so did the friction: excessive generated code\, complex setups\, and growing confusion among users on how to use the output.\n \n In this talk\, we'll explore a new client-focused Codegen setup that rethinks those trade-offs. You'll see how we drastically reduce generated output\, ensure correct and predictable types\, and provide a smooth migration path from existing tools without sacrificing flexibility or safety.\n \n We'll also dive into the story behind the change: a collaboration between Eddy (The Guild) and Igor (Yelp)\, sparked by a single question and shaped by open discussion across time zones. It’s a look at how community feedback\, real-world constraints\, and trust can drive the biggest evolution in Codegen’s history.
CATEGORIES:TOOLING + DX + TESTING + DOCUMENTATION
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:dcd9017f3882e90a2afbdc44893441cd
URL:http://graphqlconf2026.sched.com/event/dcd9017f3882e90a2afbdc44893441cd
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T192500Z
DTEND:20260520T205500Z
SUMMARY:Lunch
DESCRIPTION:\n
CATEGORIES:BREAKS + NETWORKING + SPECIAL EVENTS
LOCATION:Foyer + Bistro 880\, Fremont\, CA\, USA
SEQUENCE:0
UID:764c32b9b598bb29396ae8356bce7a14
URL:http://graphqlconf2026.sched.com/event/764c32b9b598bb29396ae8356bce7a14
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T205500Z
DTEND:20260520T212000Z
SUMMARY:A GraphQL-inspired Orchestration Language for the AI Era - Martijn Walraven\, Apollo
DESCRIPTION:GraphQL and Federation solve real problems: replacing hand-written orchestration with a declarative\, typed contract between clients and backends. That model works. But the landscape is shifting — AI agents are becoming first-class API clients\, and they need to compose across services\, reshape responses\, and build workflows faster than coordinated schema design allows.\n \n The core insight: one graph doesn't have to mean one API. What if the supergraph were less a single schema and more a catalog of data and services? That shift opens up a different kind of client language: one with expressions\, data restructuring\, and the ability to call non-GraphQL APIs directly.\n \n I'll show the result of our explorations: a language that keeps what makes GraphQL powerful — strong typing\, composability\, field-level selection — and extends it with the primitives clients need to work across service boundaries. It should feel familiar and is designed for any client — web\, mobile\, and AI agents alike. I'll explain what we learned from pushing GraphQL and Federation to their limits\, and make the case that breaking the mold doesn't mean starting over.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:b988a55f48a0405a74f9cd9d3bac64f8
URL:http://graphqlconf2026.sched.com/event/b988a55f48a0405a74f9cd9d3bac64f8
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T205500Z
DTEND:20260520T212000Z
SUMMARY:Observability for a Multi-Tenant GraphQL Gateway at Scale - Vickey Yeh\, Airbnb
DESCRIPTION:Viaduct\, Airbnb's unified data access layer\, hosts over 1.5M lines of application code from 500+ tenants\, with 200+ changes merged daily—all operating as a single service. At this scale\, enabling teams to independently monitor and troubleshoot their code is essential. \n This talk describes how we approach observability with multitenancy at the core: \n - Establishing clear ownership of modules and attributing metrics\, spans\, and errors to those owners \n - Providing alerts and dashboards at multiple levels: system\, operation\, tenant\, and field\n - Enabling schema-driven alerting\, where tenants declaratively specify monitoring requirements directly in the schema and the platform implements them automatically\n - Using execution traces to visualize query execution and core-tenant interactions\, tackling challenges like:\n - Representing batched dataloader calls (where N field requests become 1 RPC)\n - Instrumenting downstream service clients across all data-fetching code\n - Managing observability costs via selective sampling and cardinality-aware metrics \n \n Our goal: empower tenants to manage their portion of Viaduct as a standalone service—without bottlenecking on the platform team.
CATEGORIES:OBSERVABILITY + TELEMETRY + TRACING
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:d1bdf1a3eb90cb599c172cbdfa7fdd1c
URL:http://graphqlconf2026.sched.com/event/d1bdf1a3eb90cb599c172cbdfa7fdd1c
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T205500Z
DTEND:20260520T212000Z
SUMMARY:Grafast: A Declarative Solution To GraphQL's Execution Woes - Benjie Gillam\, Graphile
DESCRIPTION:A new approach to GraphQL execution\, enabling engineers to build next-level efficiency into new or existing GraphQL APIs. This declarative approach to execution eliminates the many pitfalls of traditional resolvers and optimizes communications with your business logic. This is achieved through understanding the request's full data requirements and planning the best batched execution strategy before requesting anything from the business logic. This decoupling of data fetching from the GraphQL request shape results in fewer and more efficient operations against your backend services and data sources\, eliminating both over- and under-fetching on the backend along with deduplication of redundant work\, leading to reduced operational costs and delightful user experiences! A passion project of a founding GraphQL TSC member\, this MIT-licensed open source technology has already been in production at a number of companies for over a year!
CATEGORIES:SERVERS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:4173396a76b0052395608ef918aacdbf
URL:http://graphqlconf2026.sched.com/event/4173396a76b0052395608ef918aacdbf
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T213000Z
DTEND:20260520T215500Z
SUMMARY:CANCELLED: Governing the AI-Graph: Observability and Security for LLM-Generated Queries - Rajeshwari Sah\, Apple Inc
DESCRIPTION:When we give AI agents access to our GraphQL APIs\, we introduce a new class of distributed system challenges: non-deterministic queries\, potential N+1 floods\, and authorization bypasses. How do we ensure our "AI-generated" queries are safe and efficient?\n \n This talk bridges the gap between AI Quality Engineering and GraphQL governance. Building on my work designing evaluation frameworks for multi-agent systems\, I will present strategies for monitoring and governing agents that interact with GraphQL endpoints. We will discuss how to implement "Semantic Rate Limiting" (analyzing query complexity vs. user intent) and how to evaluate the accuracy of agent-generated GraphQL syntax using "LLM-as-a-Judge" frameworks.\n \n We will also cover the "Human-in-the-Loop" aspect: using GraphQL subscriptions to stream agent reasoning to human supervisors for real-time validation before a mutation is executed. Attendees will learn how to open their Graphs to AI without compromising on security or performance reliability.
CATEGORIES:AI AND LLMS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:c550128f032ccbaa02e723360ed92f97
URL:http://graphqlconf2026.sched.com/event/c550128f032ccbaa02e723360ed92f97
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T213000Z
DTEND:20260520T215500Z
SUMMARY:Sharding a GraphQL Gateway for Blast Radius Reduction - Linquan Zhang & Cetin Sahin\, Airbnb
DESCRIPTION:At Airbnb\, our GraphQL gateway is a multi-tenant serverless platform hosting 500+ tenants and 1.5M+ lines of application code. Like many large GraphQL systems\, it operated as a "shared fate" architecture. To mitigate this risk\, we embarked on a multi-year journey to implement traffic sharding at different levels of sophistication. We started with shuffle sharding to reduce the blast radius of any single bad operation. We then added targeted sharding to separate online from asynchronous traffic\, to rapidly quarantine misbehaving operations\, and to improve the signal-to-noise ratio for our automated canary analysis. Most recently\, to mitigate the risk posed by tenants that are used by lots of operations (and thus could bring down lots of shards)\, we have been working on tenant-aware sharding that minimizes the blast radius of such tenants.\n\nWe will cover how we architected our sharding solution and how it improved our operational abilities. You will gain a clear understanding of how our implementation tradeoffs have fared over time\, key production insights gathered since rollout\, and strategies to evolve a GraphQL gateway towards greater isolation without fragmenting the API surface.
CATEGORIES:SERVERS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:a2d6aff0874a12a86810f7ffac23d12d
URL:http://graphqlconf2026.sched.com/event/a2d6aff0874a12a86810f7ffac23d12d
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T213000Z
DTEND:20260520T215500Z
SUMMARY:The Easy Way and the Hard Way: Blue-green GraphQL Deployments - Zack Warnimont\, Apollo
DESCRIPTION:Blue-green and canary deploys are table stakes for application code\, but they’re surprisingly hard to get right for GraphQL. Routers often just “pull latest” schema\, rollbacks mean republishing and recomposing\, and it’s nearly impossible to answer a basic incident question: “What schema was this request actually hitting?”. After testing in a staging environment and deploying to production\, we often find edge cases that broke the assumptions we made in the testing phase.\n \n This talk is an engineering case study. I’ll walk through the design journey that led us to a blue-green deployment model for GraphQL built on immutable schema artifacts and explicit rollbacks. We’ll unpack the constraints (federation\, many subgraphs\, multiple environments)\, the dead-ends we hit\, and the principles that finally worked.\n \n You’ll leave with a mental model and concrete patterns you can apply to your own GraphQL infrastructure\, irrespective of tooling: how to structure blue-green router fleets\, how to pin to exact schema versions\, how to do instant rollbacks safely\, and what to log so you can always reconstruct “what was live where” when production gets weird.
CATEGORIES:TOOLING + DX + TESTING + DOCUMENTATION
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:85567715cc1d01d7002aa8db5beb1193
URL:http://graphqlconf2026.sched.com/event/85567715cc1d01d7002aa8db5beb1193
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T220500Z
DTEND:20260520T223000Z
SUMMARY:GraphQL Data Mocking at Scale With LLMs and @generateMock - Michael Rebello\, Airbnb
DESCRIPTION:Producing valid and realistic mock data for prototyping and testing has been an unsolved challenge for years. Mock data is tedious to write and maintain\, but attempts to improve the process such as random value generation and field stubbing fall short as they lack essential domain context to make test data realistic and meaningful.\n In this talk\, I’ll share how we’ve reimagined GraphQL mocking at Airbnb by combining existing GraphQL infrastructure\, rich product and schema context\, and LLMs to generate convincing\, type-safe mock data simply by adding a directive (@generateMock) to a field or operation:\n - How integrating LLMs that are highly contextualized by a schema\, documentation\, and UX design into existing GraphQL tools drives a leap forward in the speed and quality of mock data creation.\n - How a directive-driven approach lets engineers generate production-like\, schema-conformant mock data without writing code.\n - How integrating generated mock data into the GraphQL client runtime can enable engineers to build and test clients before server implementation.\n - How this strategy guarantees that generated mock data is correct\, deterministic\, and stays in-sync with the server schema.
CATEGORIES:AI AND LLMS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:f95ae2cfb0b6a5e2e0dfa5971f531749
URL:http://graphqlconf2026.sched.com/event/f95ae2cfb0b6a5e2e0dfa5971f531749
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T220500Z
DTEND:20260520T223000Z
SUMMARY:Building MCP Apps With GraphQL Patterns You Already Know - Jerel Miller\, Apollo GraphQL
DESCRIPTION:You know how to build client apps—but where do client developers fit in the new world of ChatGPT and MCP? If you've used GraphQL before\, it turns out your knowledge translates directly. This talk demonstrates how to build MCP apps using Apollo's AI apps client and MCP server with patterns you already use:\n 1. Fragment colocation → Tool design: Structure MCP tools like component data requirements\n 2. Query optimization → Tool call patterns: Minimize LLM roundtrips with the same performance thinking\n 3. Type safety → Tool schemas: Apply GraphQL's type discipline to MCP definitions\n A live demo builds an MCP app querying a GraphQL API\, showing how best practices from GraphQL client development apply to OpenAI and MCP apps.
CATEGORIES:CLIENTS
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:404c47275bcd9b6fbceb8676b748321c
URL:http://graphqlconf2026.sched.com/event/404c47275bcd9b6fbceb8676b748321c
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T220500Z
DTEND:20260520T223000Z
SUMMARY:The State of GraphQL Federation - Michael Staib\, ChilliCream
DESCRIPTION:The GraphQL community has come together to standardize how distributed systems can be built with GraphQL as an orchestrator.\n \n In this talk\, I will outline our vision for GraphQL as an orchestration layer and explain how the emerging Composite Schema specification addresses the challenges of composing distributed graphs. We’ll review the progress made since the last GraphQLConf within the Composite Schema Working Group and take a look at early RFCs and experimental prototypes.\n \n The specification builds on the strongest ideas from existing federation approaches in the ecosystem\, distilling them into a vendor-neutral standard. Its goal is to enable interoperability — allowing vendors\, platform teams\, and open-source projects to implement the specification\, or parts of it\, in a way that integrates seamlessly across tools and ecosystems.\n \n This session is a community update on the work happening under the GraphQL Foundation to standardize Federation: the problems we are solving\, the principles guiding the design\, and what comes next.
CATEGORIES:FEDERATION + DISTRIBUTED SYSTEMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:4ff0c6241cf8433672629008d6d10223
URL:http://graphqlconf2026.sched.com/event/4ff0c6241cf8433672629008d6d10223
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T223000Z
DTEND:20260520T225000Z
SUMMARY:Break
DESCRIPTION:\n
CATEGORIES:BREAKS + NETWORKING + SPECIAL EVENTS
LOCATION:Foyer\, Fremont\, CA\, USA
SEQUENCE:0
UID:cff81052328dd520ae4867b729bd18cf
URL:http://graphqlconf2026.sched.com/event/cff81052328dd520ae4867b729bd18cf
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T225000Z
DTEND:20260520T231500Z
SUMMARY:Changing the Game for Trusted Documents — What If Your Whole Platform Natively Supported It? - Laurin Quast & Denis Badurina\, The Guild
DESCRIPTION:Trusted documents (persisted queries) are one of the most powerful tools in the GraphQL security and performance toolkit. By restricting your API to only pre-approved operations\, you eliminate entire classes of attacks\, reduce payload sizes\, and gain full visibility into client behavior. Yet most struggle to adopt them – the tooling is fragmented\, the workflow is manual\, and the deployment story is an afterthought.\n \n What if your entire platform natively supported trusted documents from end to end? In this talk\, I’ll show what becomes possible when persisted queries are first-class citizens of your GraphQL platform – from registration and version through CI/CD validation to production deployment and rollback. But trusted documents aren’t just for GraphQL clients. I’ll explore how they unlock new capabilities: exposing GraphQL operations as simple REST endpoints\, and even powering MCP tools for AI agents – all built on the same foundation of pre-approved\, governed operations.\n \n You’ll leave with a clear picture of what a complete trusted documents platform looks like and practical steps to get there.
CATEGORIES:CLIENTS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:d96e6d2bb0c7badfa5604e2ce8336138
URL:http://graphqlconf2026.sched.com/event/d96e6d2bb0c7badfa5604e2ce8336138
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T225000Z
DTEND:20260520T231500Z
SUMMARY:Brute Force Correctness - James Bellenger\, Airbnb
DESCRIPTION:So you’re a maintainer of a GraphQL system. Whether it’s a federation gateway\, a complex client library\, or a custom executor—how do you know that it’s capital-C Correct?\n \n Your tests are decent\, and they seem to pass\, but what about the test cases that you didn’t think of? Did you remember to handle @skip directives on fragment spreads? What about when those directives use variables? Or when you spread an abstract type in an abstract scope?\n \n Would you trust your system to serve million-dollar transactions?\n \n This session will cover how probabilistic testing can be applied to complex GraphQL systems to find bugs in places we wouldn’t have thought to look. We’ll discuss how Airbnb leveraged this approach to launch a novel GraphQL engine with 0 spec conformance bugs\, and how you can apply these same techniques to build unshakable confidence in your own systems.
CATEGORIES:TOOLING + DX + TESTING + DOCUMENTATION
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:0a67525d56d469af7df6fc4763e3f75e
URL:http://graphqlconf2026.sched.com/event/0a67525d56d469af7df6fc4763e3f75e
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T225000Z
DTEND:20260520T231500Z
SUMMARY:Speed Without Sacrifice: How Wayfair Transforms DevEx With AI and MCP - Maheswari Karlapudi & Muskan Sethi\, Wayfair
DESCRIPTION:Wayfair is embedding AI and MCP into every stage of the developer workflow to unlock speed without compromising quality. From Schema Copilot (inline reviews) to AI Mocking (intelligent test data generation) to AI-Assisted Schema Documentation (auditing and auto-generating descriptions across 200+ subgraphs)\, these purpose-built tools streamline workflows\, reduce friction\, and scale engineering excellence—helping teams ship faster with greater confidence and consistency. Join to learn how AI and MCP cut busywork so Wayfair’s devs can ship faster with confidence.
CATEGORIES:TOOLING + DX + TESTING + DOCUMENTATION
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:73b21b1bb1a0d976eef05c0650c41455
URL:http://graphqlconf2026.sched.com/event/73b21b1bb1a0d976eef05c0650c41455
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T232500Z
DTEND:20260520T235000Z
SUMMARY:@live GraphQL in Practice: Postgres-to-React Realtime Data Sync - Tobbe Lundberg\, Cedar Software AB
DESCRIPTION:We built a real-time system for Postgres→React sync using a `LISTEN/NOTIFY` Postgres trigger\, GraphQL `@live` queries\, a React hook and a custom ORM-inspired GraphQL query builder. Starting from ESP32 microcontroller devices sending MQTT messages and a Node/Postgres backend\, we moved from polling to a stand-alone PoC with Yoga\, Prisma triggers\, and a custom `useLiveQuery` hook. After proving that the PoC was working we integrated with all our existing full-stack apps. So now we have low-latency UI updates\, reusable cross-app logic\, and easier extension for new sensor values. Great UX and excellent DX.\n \n TOC \n \n - Title & minimal intro\n - Goals (What We Needed)\n - Existing System (What We Had)\n - Attempts & Why They Failed\n - Solution Overview \n - Postgres `LISTEN/NOTIFY`\n - `useLiveQuery` React hook\n - Yoga and Apollo `@live` integration\n - GraphQL query builder\n - GraphQL SDL generator\n - GraphQL resolver generator\n - Demo / Results\n - Tradeoffs\, Lessons & Next Steps\n - Q&A
CATEGORIES:PRODUCTION INSIGHTS - REGULAR SCALE
LOCATION:Grand Ballroom I\, Fremont\, CA\, USA
SEQUENCE:0
UID:89470f00e294ad39c964a82f76fe4009
URL:http://graphqlconf2026.sched.com/event/89470f00e294ad39c964a82f76fe4009
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T232500Z
DTEND:20260520T233500Z
SUMMARY:Lightning Talk: DoS Wars: Revenge of the Fragments - Sachin Shinde\, Apollo GraphQL
DESCRIPTION:Fragments—an indispensable tool for modularizing data requirements alongside client code\, but also a denial-of-service attack vector for servers. Security guides will tell you to mitigate by validating queries and performing cost analysis\, usually via field costs and list sizes. However\, this focus on field execution can distract from how fragments affect the rest of the server stack. In this lightning talk\, we explore the attack patterns and mitigation strategies for the fragment-based vulnerabilities at the core of CVE-2025-31496\, CVE-2025-32030\, CVE-2025-32033\, and CVE-2025-32034.
CATEGORIES:SECURITY
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:1658c2b28f55f1f552eb662db054ce45
URL:http://graphqlconf2026.sched.com/event/1658c2b28f55f1f552eb662db054ce45
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T232500Z
DTEND:20260520T235000Z
SUMMARY:Turning San Francisco Into a GraphQL Server - Jean Lucas Lima\, ConfrariaTech
DESCRIPTION:What if a city could run as a GraphQL server?\n \n In this talk\, we model San Francisco as a modular GraphQL runtime powered by Viaduct. Instead of stitching together microservices or configuring external gateways\, we organize zoning\, building permits\, transit\, and census data as domain modules inside a single distributed graph engine.\n \n Using real public datasets from the City of San Francisco and the U.S. Census\, we demonstrate how tenant modules compose into a unified schema\, how execution is coordinated across domain boundaries\, and how teams can evolve parts of the graph without central bottlenecks.\n \n We introduce a lightweight Skills SDK that abstracts runtime configuration and enforces clear ownership rules\, making modular graph design approachable.\n \n Finally\, we connect an AI client to the server to demonstrate structured\, explainable reasoning over live city data.\n \n All demo code and schema modules will be open sourced for attendees to explore and extend.
CATEGORIES:SERVERS
LOCATION:Boardroom\, Fremont\, CA\, USA
SEQUENCE:0
UID:50d245b496fbe7e54087e218e9b4b60d
URL:http://graphqlconf2026.sched.com/event/50d245b496fbe7e54087e218e9b4b60d
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260520T234000Z
DTEND:20260520T235000Z
SUMMARY:Sponsored Lightning Talk: Search and Execute with Code Mode Backed by the Graph - Jens Neuse & Ahmet Soormally\, Wundergraph
DESCRIPTION:\n
CATEGORIES:FEDERATION + DISTRIBUTED SYSTEMS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:273005784066cf9166ef7c08fc5ba686
URL:http://graphqlconf2026.sched.com/event/273005784066cf9166ef7c08fc5ba686
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260521T000000Z
DTEND:20260521T002000Z
SUMMARY:Keynote: GraphQL’s Next Chapter: Progress\, Proposals\, and Participation - Pascal Senn\, COO\, Chillicream & Mark Larah\, Group Tech Lead\, Yelp
DESCRIPTION:GraphQL has always been a community driven project. In this closing keynote\, we will look at what the GraphQL Working Groups have been building and the progress made across the specification and ecosystem. We will also highlight the GraphQL GAP proposal and explore how it can open new opportunities for collaboration. Join us as we reflect on how far GraphQL has come and how the community can help shape what comes next.
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:4f9ef38c5bf114a812996561c38e5455
URL:http://graphqlconf2026.sched.com/event/4f9ef38c5bf114a812996561c38e5455
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260521T002000Z
DTEND:20260521T003000Z
SUMMARY:Keynote: Closing Remarks - Lee Byron\, Co-Creator of GraphQL and Director\, GraphQL Foundation
DESCRIPTION:\n
CATEGORIES:KEYNOTE SESSIONS
LOCATION:Grand Ballroom II - IV\, Fremont\, CA\, USA
SEQUENCE:0
UID:5da75d13f586427954cdf193cbb1d8bd
URL:http://graphqlconf2026.sched.com/event/5da75d13f586427954cdf193cbb1d8bd
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260528T040021Z
DTSTART:20260521T163000Z
DTEND:20260521T233000Z
SUMMARY:WG Day [Invite Only; Pre-Registration Required]
DESCRIPTION:A day for GraphQL working group members and maintainers of key GraphQL open source software to socialize\, strategize\, and build on the momentum of the main conference.&nbsp\;\n\nCapacity is limited\, so invitations will go to regular working group participants first. Additional attendees can join via a waitlist\, with priority for maintainers of GraphQL-related open source software (clients\, servers\, libraries\, frameworks\, tooling\, and documentation)\, plus Foundation board members and GraphQL Ambassadors. \n\nPlease visit the WG Day page for more information and to request to attend.
CATEGORIES:WG DAY
LOCATION:Meta FRE 117\, Fremont\, Fremont\, CA\, USA
SEQUENCE:0
UID:8fba41477c85ead43a5570df29572942
URL:http://graphqlconf2026.sched.com/event/8fba41477c85ead43a5570df29572942
END:VEVENT
END:VCALENDAR