Agents: Thinking Fast and Slow

Learn how agents dynamically retrieve and structure context, use iterative and ontology‑guided reasoning, and orchestrate complex SaaS workflows without fixed integrations.

Overview

For AI agents to operate seamlessly across diverse applications, they must dynamically expand context to retrieve relevant information and converge on the right actions without relying on predefined workflows. This talk explores how we enable agents to adapt to new environments, effectively acting as the UI for AI to navigate and interact with software systems.

We’ll cover:

Context Expansion: Dynamically retrieving and structuring relevant knowledge for better decision-making.
Convergence on Demand: Iterative reasoning strategies that refine actions through multi-step execution.
Ontology-Guided Reasoning: Leveraging structured knowledge to improve accuracy and decision reliability.
Real-World Applications: How these techniques allow agents to orchestrate complex workflows, break API limitations, and drive automation across SaaS tools.
By combining structured retrieval with adaptive reasoning, we move beyond static integrations—unlocking AI agents that can truly think in motion and execute with precision.

Tech stack