Platform Engineers Milano

Agents in your SDLC are more expensive than they need to be. When agents connect to MCPs, they waste tokens reasoning to find answers, increasing cost.

But what if the context is structured around the questions agents ask the most? Port ran an experiment and measured the cost.

In this session, you’ll learn about the research findings and how to build a context lake that reduces agent cost at scale.

Join us to find out:

• Why AI agent token costs are structurally high, and why switching models doesn't fix it
• What the research found after running 1200 queries across four context conditions and three models, totaling 1,200 runs
• How to build a context lake that works in practice: which properties to pre-join, how to model data around your agents' actual query patterns, and what catalog hygiene looks like once you're running at scale.

Speaker: Matar Peles
Field CTO @ Port
Matar is Field CTO at Port, connecting product and market in the field. He works closely with customers and internal teams to translate real-world needs into product direction, focusing on productivity and developer experience at scale.

Speaker: Aaron Taylor
Program Manager @ Port
Aaron is a program manager at Port where he researches how engineering teams actually use AI, and translates the findings into clear, practical guidance for the people building with it.

AI has made developers faster, but it's also made security vulnerabilities appear faster, governance harder, and production incidents more frequent. The 2026 State of Infrastructure Automation report surveys 406 infrastructure teams to find out where AI readiness and platform maturity actually stand.

This session covers the data, the gap between what teams say and what their workflows reveal, and what separates the organizations pulling ahead from those falling behind.

Join Dimitri and learn:

1. How your peers are actually managing AI and governance in production today, what the data says about confidence vs. reality, and where most teams have a blind spot they don't yet know about.
2. A behavioral framework for assessing your own AI readiness across five dimensions: AI integration depth, governance maturity, automation coverage, risk exposure, and platform readiness.
3. What Pioneer organizations did differently before AI arrived, why that discipline is now the single biggest predictor of production stability, and the specific steps still available to close the gap before agentic AI removes the margin for error.

Speaker: Dimitri Vlachos
CMO @ Spacelift
Dimitri is a proven marketing leader with over 20 years of experience in technology. Prior to being the CMO of Spacelift, Dimitri served as CMO at venture-backed technology companies including Brinqa and Devo. He has also held leadership roles in marketing and product at Riverbed Technology, Mazu Networks, and Cisco Systems.

Speaker: Faisal Afzal
Principal, Platform Engineering @ AHEAD
Faisal Afzal is a CNCF and Platform Engineering Ambassador and Principal Technical Consultant Lead at AHEAD specializing in cloud and platform engineering. He organizes Cloud Native LA, co-organizes Cloud Native Days Los Angeles, and volunteers at SCaLE, helping socialize and make cloud-native technologies accessible to the broader community.

Platform engineering has crossed the adoption threshold. But the platforms most teams built weren't designed for AI workloads, autonomous agents, or a multi-persona organisation. In this session, Pankaj Gupta (Broadcom) and Sam Barlien (Platform Engineering) walk through the five pillars that define Platform Engineering 2.0: AI-native platform, multi-persona experience, embedded FinOps, security shifting down, and composable architecture. This is evolution, not revolution. But are you ready for it?

Join the discussion to learn:

1. Why today's IDPs have hit a structural ceiling and what the five forces driving that pressure are: AI-driven coding acceleration, autonomous agents, cloud and AI cost pressure, multi-persona organisations, and sovereignty regulation.
2. What each of the five pillars of Platform Engineering 2.0 requires in practice: AI-native infrastructure, embedded FinOps, security shifting into the platform layer, multi-persona experience, and composable architecture.
3. How to prioritise the evolution: which pillar to start with based on your most urgent pressure, and the 12-month milestone that matters most for AI readiness.

Speaker: Pankaj Gupta
Senior Director, Product Management @ Broadcom
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Speaker: Sam Barlien
Head of Ecosystem @ Platform Engineering