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
No Framework, No Server: Making AI Agents Collaborate in One Terminal
Lech Kalinowski
AI coding agents are powerful, but they usually work in isolation. One agent analyzes the code, another writes tests, and a third reviews the result—while the developer manually copies context between them. I built Agents Commander to explore a simpler alternative. Inspired by the classic Norton Commander interface, it places multiple agentic CLIs—such as Claude, Codex, and Gemini—side by side in a single terminal. More importantly, it allows those agents to communicate directly. At the center of the project is the Commander Protocol: a minimal, text-based communication format implemented through output observation and input injection. An agent can analyze a problem, delegate a task to another agent, receive the result, and continue working without a central orchestration server, complex API integration, or heavyweight multi-agent framework. Through live demonstrations, I will show agents delegating engineering work, exchanging findings, challenging one another, and refining their conclusions. I will also examine what happens when communication becomes part of the system being tested: messages are misunderstood, context is lost, agents disagree, and unexpected collaboration patterns emerge. Attendees will leave with a practical understanding of multi-agent communication, lightweight orchestration, and how visible agent-to-agent workflows can make AI-assisted engineering easier to inspect, debug, and control.
Save your seat before it fills.
Early pricing runs while the programme is still being finalised.