AI Workforce Development – Operationalizing AI: From Ambition to Architecture

Event Highlights:

• High-impact, half day session focused on accelerating your AI architecture journey.
• Key Takeaway: AI Agent Scaling Decision Tree.
• Based on foundational AI content from Info-Tech’s AI Workforce Development Program.
• Connect with fellow participants at a lunch reception after the training.
• Register for IGNITE Texas by August 31st, 2026, and receive complimentary admission to this event.  

Program Overview

This interactive session establishes a shared foundation for understanding LLMs, tools, and agentic behavior by clarifying how these systems operate beyond the user interface and by providing a framework for interpretation and implementation. It examines practical design patterns used within organizations to show how agents are applied to real tasks with appropriate technical grounding. We will address key risks and the mechanisms required to manage them, including access control, observability, and logging, along with the relevant regulatory and organizational context. The outcome is a structured understanding of how AI agents function, how they can be used safely, and how organizations can support their use through appropriate controls and governance practices.

Program Outcomes

• Explain how agents and tools operate beyond the interface in real systems.
• Understand practical agent design patterns and business use cases within real organizations.
• Demonstrate core tools required for building reliable agentic systems and PoCs at scale.
• Identify and monitor risks through appropriate governance processes and controls.
• Align AI usage with regulatory and organizational requirements across enterprise environments and teams.
• Info-Tech-endorsed CPE qualifying credit hours.

Meet Your Facilitator

Jai Hebel, Research Director

Jai completed his M.Eng. in bioengineering and biomedical engineering at McGill University in 2020, where he studied neuroimaging and neurosurgical navigation. For his thesis, Jai specialized in deep learning for medical imaging, where he researched convolutional encoder-decoders for glioblastoma segmentation in multimodal MR images. After graduation, Jai was selected for an AI fellowship with Insight Data Science and further honed his AI expertise in the San Francisco Bay Area, building models for fast-paced biotech startups and biological research projects at the Chan-Zuckerberg Biohub. In 2024 Jai joined Info-Tech Research Group as an instructor in artificial intelligence, where he leverages his experience as a developer and an educator to translate rapid developments in AI for industry professionals. 

Event Location:
Hyatt Regency Austin
208 Barton Springs Rd, Austin, TX 78704, United States