AI Is Becoming Infrastructure: Why Context Engineering and Platforms Will Define the Next Decade
by Lyndon Carlson | at Minnebar20
Everyone is talking about models, prompts, and agents.
That’s not where the real shift is happening.
AI is rapidly becoming infrastructure; embedded into how software is built, how decisions are made, and how companies operate. But most teams are still treating it like a tool, and that’s why so many AI initiatives stall out.
In this session, we’ll cut through the hype and focus on what actually matters:
- Why AI projects get stuck between demo and production
- Why model choice matters less than you think—and context matters more
- What “context engineering” really is (and why it’s becoming a core discipline)
- How companies are quietly becoming AI platform builders, often without realizing it
This is a mental model reset.
If you’re a builder, leader, or just trying to make sense of where AI is headed, this session will give you a clearer picture of what’s actually changing and what to do about it.
Come ready to challenge assumptions, ask questions, and share what you’re seeing.
Lyndon Carlson
Lyndon Carlson is an AI platform leader and founding CTO focused on building and aligning production-grade AI systems. His work spans training domain-specific models, applying reinforcement learning for alignment, and deploying agentic systems that operate reliably in real-world environments.
He currently leads AI initiatives at Trissential and is the founding CTO of ChatLPO, where he has built scalable AI platforms used by thousands of users. He has also led greenfield AI initiatives in partnership with AWS, including model development, alignment, and system deployment, with an emphasis on safety, governance, and enterprise scale.
Lyndon’s work focuses on bridging the gap between AI capability and real-world impact, turning advanced models into systems that organizations can actually trust and use.
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