Yina Arenas presents essential design patterns and best practices for building agentic AI systems with Azure AI Foundry, explaining how organizations can drive automation beyond conventional chatbots and copilots.

Agent Factory: The New Era of Agentic AI—Common Use Cases and Design Patterns

Author: Yina Arenas

Agentic AI is transforming how enterprises approach automation. Rather than simply providing information, AI agents now reason, act, and collaborate—delivering outcomes that bridge the gap between knowledge and real-world impact. This post, the first in a six-part “Agent Factory” series, introduces core concepts, patterns, and tools for building agentic AI using Microsoft’s Azure AI Foundry.

From Knowledge Retrieval to Agentic Action

Enterprise AI adoption began with solutions like retrieval-augmented generation (RAG): chatbots and copilots that surface rapid insights. Yet many business processes demand more than answers—they require agents able to execute multi-step actions (like submitting forms or orchestrating workflows) across complex systems. Traditional automation methods struggle to keep pace with enterprise needs at scale. Agentic AI offers a way forward.

Core Patterns for Agentic AI in Enterprises

This post highlights five foundational design patterns enabling robust agentic automation:

1. Tool Use Pattern

Agents go beyond providing advice—they interact directly with APIs, trigger workflows, and complete transactions.
Real-world example: Fujitsu’s sales proposal process uses specialized agents for data analysis, market research, and document assembly, reducing production time by 67%.

2. Reflection Pattern

Agents assess and refine their outputs autonomously, minimizing errors.
Particularly important in compliance and finance scenarios.
Even code assistants like GitHub Copilot leverage internal review loops prior to output.

3. Planning Pattern

Planning agents break complex goals into actionable tasks, adapting as requirements change.
Example: ContraForce automates security incident response with agents decomposing each incident into phases and dynamically progressing through them, automating 80% of incident workflows.

4. Multi-Agent Pattern

Enterprises benefit from networks of specialized agents, orchestrated to operate in parallel or sequence.
BAQA Genie, deployed by JM Family, uses multiple agents (for requirements, coding, QA) coordinated by an orchestrator, speeding product development lifecycle and QA by up to 60%.

5. ReAct (Reason + Act) Pattern

Enables adaptive, real-time problem solving where agents alternate between reasoning and acting, adjusting strategies dynamically.
Useful in IT support scenarios for real-time diagnostics and escalation.

These patterns can be combined, building automation solutions that are agile, auditable, and ready for real-world complexities.

The Value of a Unified Agent Platform

Building agents for production involves real engineering challenges: chaining steps, securing data access, ensuring observability, and orchestrating at scale. Teams often develop custom scaffolding for these needs—slowing outcomes and increasing risk.

Azure AI Foundry: A Cohesive Platform for Agentic AI

Microsoft’s Azure AI Foundry addresses these gaps with an end-to-end platform:

Prototype locally, deploy at scale: Seamless migration from local experimentation to cloud runtime.
Flexible model access: Unified API for Azure OpenAI, xAI Grok, Mistral, Meta, and 10,000+ open models, with dynamic model routing and leaderboards.
Modular agent architectures: Compose and connect specialized agents and patterns, replicating successful structures across teams.
Enterprise connectivity: 1,400+ built-in connectors support integration with systems like SharePoint, Bing, SaaS, and business apps.
Open protocols: Support for Agent-to-Agent (A2A) and the Model Context Protocol (MCP) enables interoperability across clouds and partners.
Enterprise-grade security: Managed Entra Agent IDs, role-based access control, “on behalf of” authentication, and rigorous policy enforcement.
Deep visibility: Advanced observability with step-level tracing, Azure Monitor integration, and automated evaluation—supporting compliance needs and continuous improvement.

Agent Factory: Enterprise Patterns and Best Practices for Agentic AI with Azure AI Foundry