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
Agents are easy, enterprises are where they break
Konrad Bujak
You already built the agent, probably wrapped it in a harness, added evals, connected observability, and it still falls the moment it uses company data. Building agents was never hard since tools calling has released in 2023 and then MCP standardized it. Now anyone can build an agent in an afternoon. The hard part is the thing that makes software like Palantir worth millions of dollar, and it isn’t LLMs. It’s everything around it, orchestration, RAG, knowledge graphs, master data management, semantic layer, ontologies and in short what company’s data means. Most failures happen in the boring layers like isolation, data quality, context across systems, and the data model itself. Let me tell you why skipping them turns a “Palantir for X” into “Accenture for X.”
Save your seat before it fills.
Early pricing runs while the programme is still being finalised.