The gap isn't AI capability. It's AI infrastructure.

Equal Experts helps engineering teams move from individual productivity to systemic delivery.

AI is changing how software gets built—but many organizations are still struggling to scale beyond individual use cases. Explore practical ideas for enterprise AI adoption, including Andy Vays’ AI4 session on the AI Hub, plus additional insights on modern software delivery, agentic workflows, and AI at scale.

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AI-Native Engineering at Scale: Infrastructure, Workflows, and the AI Hub Pattern

Every enterprise engineering org has rolled out AI tools by now. Few have built the infrastructure to make AI-native engineering actually work at scale. During this session, we’ll share the AI Hub — a pattern we’ve built across enterprise clients — for building the infrastructure and ways of working that make AI-native engineering possible at scale, and you’ll leave with a concrete pattern you can take back to your organization. You’ll learn:
  • Why most enterprise AI adoption stalls before it reaches org-wide scale
  • The AI Hub pattern we’re building with enterprise clients
  • The infrastructure that lets context and governance scale across teams
  • Practical ways of working for agentic delivery

Wednesday, August 5 @ 12:10 PM | Palazzo Ballroom M

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About the speaker

Andy Vays, Technical Principal

Andy Vays is a Technical Principal at Equal Experts, focused on applying AI pragmatically across the software development lifecycle to drive real delivery impact. With over 15 years of experience spanning software engineering, enterprise architecture, and large-scale digital transformation, he has led complex CRM, billing, data, and cloud modernization programs for both high-growth and enterprise organizations. Before joining Equal Experts, Andy led major platform transformations at Rent.com and co-founded an AI-focused startup aimed at accelerating digital transformation. Today his work centers on agent-driven delivery approaches that help teams move faster, reduce risk, and improve quality — grounded in an execution-first mindset that turns AI from experiment into repeatable, real-world outcomes.

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Being AI-enabled means every developer has a tool. Being AI-native means the infrastructure, the governance, and the way teams work are actually built for AI, not bolted onto whatever you had before. That’s the difference that determines whether AI stays a handful of individual wins or actually scales across the organization. Most companies are stuck at the first stage without realizing it.

Andy Vays
Technical Principal, North America , Equal Experts

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Find out where your organization actually stands on the path from individual AI tools to AI-native delivery.

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