Agentic AI for 2026: Key Concepts and Best Practices for Real Solutions

Agentic AI: Foundations, Workflows, and Practical Design

Everyone is talking about it, but very few leaders have a clear view of what must be in place before these systems deliver real value.

We just released a new whitepaper that explains how Agentic AI actually works in data and analytics environments and what teams need to prepare.

This guide covers the core pieces of agentic design, from planning and execution flows to how tools, context, and orchestration tie together. It also walks through the patterns Lumi has developed over years of building these systems for operational analytics.

You will learn

• What makes agentic AI different from basic LLM prompting
• How planning, execution and observation work together
• Common architecture patterns, including supervising and worker agents
• How tools, context, and orchestration shape outcomes
• Practical design choices that improve accuracy and reduce model drift
• Ways to shorten feedback loops and avoid unnecessary model calls
• When to rely on rules instead of more AI

For teams exploring agentic AI or preparing longer term plans, this whitepaper offers a clear overview of the concepts and the decisions that matter most.