Register
Enterprise AI doesn’t fail because of models or frameworks , it fails because of architecture.
In this talk, we’ll explore how agentic compute, a layer for orchestrating and building compound AI systems, solves the integration, scalability, and adaptability challenges that plague enterprise AI deployments.
Drawing on real-world experiences from multi-country Agentic PaaS deployments
- Why retrofitting green field compound AI Systems crumble in the face of heterogeneous data, political resistance, and changing business requirements.
- The personas that need to be enabled by the architecture and why systems alone is not enough
- The agentic compute architecture has core layers, lifecycle management, and fault isolation patterns. While enabling the existing teams within an enterprise
- Open source components you can use to bootstrap your own agentic systems.
Whether you’re dealing with legacy systems, multinational data sources, or complex organizational politics, you’ll leave with architecture patterns and a reference design to build AI that actually works in the messy real world.
Interview:
What is your session about, and why is it important for senior software developers?
It’s about shifting from cobbling AI tools together to treating AI as a real computing platform. Most teams are forced today to build piecemeal: a model here, a tool there, brittle integrations everywhere. That approach collapses in messy enterprises. What’s needed is a foundation , a system view , that makes AI reliable, scalable, and usable in the real world.
Why should attendees prioritize your session?
Because you’ll leave with patterns for building AI systems that don’t collapse under enterprise complexity. This isn’t about demos. It’s about how to think in terms of platforms instead of patchwork.
What are the common challenges developers and architects face in this area?
The tooling is exploding. Every week there’s a new model, framework, or library. Teams try to stitch them together, but end up with brittle, piecemeal systems buried in complexity. What we need isn’t more tools it’s less. A platform view of computing, not a toolbox view.
What's one thing you hope attendees will implement immediately after your talk?
Stop thinking about “adding AI features.” Start designing around an agentic compute layer , a foundation that turns models into systems that last.
What makes InfoQ Dev Summit stand out as a conference for senior software professionals?
It’s where builders who’ve carried systems into production meet. Less hype, more scars and patterns. That’s what makes it valuable.
What does being part of InfoQ Dev Summit mean to you?
A chance to share what we learned building one of the first multi-country agentic platforms , and to help others avoid the dead ends of piecemeal AI.
Speaker
Arun Joseph
Founder @Rhizome Foundry GmbH | Co-Founder @Masaic AI (AgC™, Agentic Compute) | Envisioned & Lead @Eclipse LMOS | Former Head of AI Engineering, Deutsche Telekom AG
Arun Joseph is now building the next-generation infrastructure for agentic compute. He previously led the Architecture and Engineering teams at Deutsche Telekom's AI Competence Center, driving the development and deployment of cutting-edge Generative AI (GenAI) solutions group wide across Europe. As a thought leader in applied AI, Arun has spearheaded the creation of an enterprise-grade agents computing platform, which now powers Deutsche Telekom’s LLM powered AI applications, including the award-winning service bot, Frag Magenta.
Arun is deeply passionate about the potential of GenAI solutions and the engineering design that heralds a new era of computing. His commitment to building world-class digital products and systems is matched by his dedication to nurturing top-tier teams. He is also an advocate for open source development; under his leadership, his teams have open source agents development frameworks.
Outside of work, Arun is a staunch advocate for the ethical deployment of technology, particularly AI. He champions the concept of the "Right to AI", striving for a more equitable world where access to AI is justly and ethically enabled for all.
