Tutorials ASP.NET Core with Agentic AI Tutorial

AI Automation Platforms — Complete Guide

AI Automation Platforms — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ASP.NET Core with Agentic AI Tutorial on Toolliyo Academy.

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ASP.NET Core with Agentic AI Tutorial · Lesson 75 of 100

AI Automation Platforms

AI basics ✓Agents

Agents · 2 — Build · ~10 min · Module 8: AI SaaS and Enterprise Systems

What is this?

AI automation platforms combine triggers, agents, integrations, and human approval into configurable flows. AgentNest exposes workflow definitions CRM and ERP admins can enable without redeploying code.

Why should you care?

Ops teams want if-new-lead-then-enrich-and-assign without opening Visual Studio for each customer playbook.

See it live — copy this example

Paste into an ASP.NET Core 8+ / AgentNest project, then run with dotnet run (set your API keys in user-secrets).

// AgentNest.Automation/WorkflowDefinition.cs
public sealed record WorkflowDefinition(
    string Id, string Trigger, IReadOnlyList<string> Steps, bool RequiresApproval);

public sealed class AutomationRegistry
{
    readonly Dictionary<string, WorkflowDefinition> _defs = new()
    {
        ["crm.new-lead"] = new("crm.new-lead", "crm.lead.created",
            ["EnrichLead", "ScoreLead", "AssignOwner"], false)
    };
    public WorkflowDefinition Get(string id) => _defs[id];
}

What happened?

  • AutomationRegistry maps trigger crm.lead.created to ordered agent steps stored as data-driven workflow definitions.
  • Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

  1. Emit domain events crm.lead.created to Service Bus.
  2. AutomationWorker loads WorkflowDefinition and runs steps.
  3. Admin UI CRUD on definitions stored in SQL JSON column.
  4. Add JSON schema validation on workflow definition uploads.
  5. Simulate workflow dry-run without side effects.

Remember

Automation platforms store triggers and agent steps as data. AgentNest registry drives workers from domain events. Expose admin configuration for tenant playbooks.

Custom lead routing

Enterprise CRM customer adds ScoreLead threshold in admin UI.

Outcome: Updated WorkflowDefinition routes hot leads without code deploy.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed
Explain Concepts in the context of ASP.NET Core with Agentic AI.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Concepts…
Mid Detailed
What are common mistakes teams make with LLMs when using ASP.NET Core with Agentic AI?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define LLMs in p…
Senior Detailed
How would you debug a production issue related to RAG in a ASP.NET Core with Agentic AI application?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define RAG in pl…
Junior Detailed
Describe a real-world scenario where Production mattered in a ASP.NET Core with Agentic AI project.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Productio…
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ASP.NET Core with Agentic AI Tutorial
Course syllabus

ASP.NET Core with Agentic AI Tutorial

Module 1: AI and Agentic AI Foundations
Module 2: ASP.NET Core AI Fundamentals
Module 3: Semantic Kernel
Module 4: AI Agents and Multi-Agent Systems
Module 5: RAG and Vector Databases
Module 6: AI Security and Observability
Module 7: Cloud-Native AI and DevOps
Module 8: AI SaaS and Enterprise Systems
Module 9: AI System Design and Architecture
Module 10: Enterprise AI Projects
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