Two days, built for engineers.
Sessions, keynotes, and breaks across every stage. Released day by day as the lineup locks in.
Where to be, and when.
- 10:30 – 11:15SeattleNo Framework, No Server: Making AI Agents Collaborate in One TerminalAI Engineering & DataLech Kalinowski
- 10:30 – 11:15CupertinoSecuring AI Agents on Kubernetes: Identity, Sandboxes, and Policy EnforcementAI Engineering & DataRoland Huß
- 10:30 – 11:15Los GatosHow will we prompt AGI? A History of Harness Hacks.AI Engineering & DataIvan Charapanau
- 11:30 – 12:15Los GatosSame Bug Twice: What Happens When AI Writes Your Code And Your TestsSoftware Architecture & Engineering ExcellenceMourjo Sen
- 11:30 – 12:15SeattleAgents Propose, Git DisposesCloud, DevOps & Platform EngineeringJaroslaw Gajewski
- 11:30 – 12:15CupertinoAI Tokenomics: Principles for Cost-Efficient GenAIAI Engineering & DataGrzegorz Wasilewski
- 12:30 – 14:00Silicon ValleyPrivate AI with Docker and UpCloudCloud, DevOps & Platform EngineeringPaweł Piwosz
- 12:30 – 13:15RedmondTerraform, day 1001Cloud, DevOps & Platform EngineeringPiotr Trębacz
- 12:30 – 13:15Palo AltoI packaged my application in a container image, and now what?Cloud, DevOps & Platform EngineeringAurélie Vache
- 13:30 – 14:15Cupertino(MCP Security) - How Your Friendly MCP Tool Might Betray YouCybersecurityDaniel Ostrovsky
- 13:30 – 14:15Palo AltoBeyond Coding Assistants: Orchestrating the Entire SDLCAI Engineering & DataIllia Slepau
- 13:30 – 14:15RedmondFrom GenAI Training to Production. Lessons learned from Building AI Agents for Financial Services ClientsAI Engineering & DataAnna Żółtańska
- 14:30 – 15:15CupertinoAgents are easy, enterprises are where they breakAI Engineering & DataKonrad Bujak
- 14:30 – 15:15Palo AltoSourcecode translation as a step in Legacy ModernizationSoftware Architecture & Engineering ExcellenceLeszek Włodarski
- 14:30 – 15:15Los GatosDesign Systems That Explain ThemselvesSoftware Architecture & Engineering ExcellenceSzymon Chudy
- 15:30 – 16:15CupertinoBuilding the next generation of AI developer toolsAI Engineering & DataKrzysztof Cieślak
- 15:30 – 16:15Los GatosPlatforms That Don't Suck - Creating tools that teams might actually loveCloud, DevOps & Platform EngineeringKarolina Ochlik
- 15:30 – 17:00Silicon ValleySecuring AI Agents with Fine Grained AuthorizationCybersecuritySohan Maheshwar
- 16:00 – 16:45Palo AltoMFA? Game over! Watch your protection collapse – liveCybersecurityChristoph Menzel
- 16:30 – 17:15CupertinoGitHub Actions moves to CosmosDB: data migration at internet scaleSoftware Architecture & Engineering ExcellenceBassem Dghaidi
- 16:30 – 17:15Los GatosForensic DDD: Reverse-Engineering the Domain Your Legacy System Never DocumentedSoftware Architecture & Engineering ExcellenceRaj Navakoti
- 16:30 – 17:15RedmondAgile isn't dead, you're just doing it wrongEngineering careersKarolina Ochlik
Design Systems That Explain Themselves
Szymon Chudy
You don't know a design system until you have to change it. The components are the easy part. What gets you is everything they assume you already know: the API that looks consistent until you extend it, the token whose name only makes sense if someone explains its history. Hawkins, Netflix's design system, runs across thousands of applications and is used by 2k+ engineers. A major new version ships this year. At that scale, preparing a release is mostly archaeology. Before you change anything, you have to uncover what the system does, why it does it, and which assumptions have accumulated over a decade. AI raises the price of that gap. An agent reading your system can't walk over and ask a teammate. Whatever the code and docs leave unsaid, it has to guess. And more documentation alone won't save you. Consistent APIs, token names that carry their meaning, accessibility built into the primitives - that's what lets a system explain itself. I'll use the Hawkins redesign throughout: evolving a ten-year-old system without breaking the applications standing on it. You'll leave knowing how to find where your own system depends on knowledge nobody wrote down, and how to turn that knowledge into constraints, conventions, components, tokens, and documentation that both humans and agents can understand.
Save your seat before it fills.
Early pricing runs while the programme is still being finalised.