Tutorials ASP.NET Core with Agentic AI Tutorial

AI Workflow Automation Platform — Complete Guide

AI Workflow Automation Platform — 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 96 of 100

AI Workflow Automation Platform

AI basics ✓Agents

Agents · 2 — Build · ~10 min · Module 10: Enterprise AI Projects

What is this?

AI Workflow Automation Platform is the union of Workflow Studio, AutomationRegistry, queues, and agents — customers automate end-to-end CRM and ERP playbooks visually.

Why should you care?

Platform SKU upsell moves customers from single copilot to orchestrated automation with measurable throughput gains.

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/Platform/WorkflowExecutionHost.cs
public sealed class WorkflowExecutionHost(
    AutomationRegistry registry, JsonWorkflowRunner runner, IAiAuditWriter audit)
{
    public async Task ExecuteTriggerAsync(string trigger, JsonDocument payload, string tenantId, CancellationToken ct)
    {
        var def = registry.FindByTrigger(trigger, tenantId);
        await audit.WriteAsync(new AiAuditEntry(tenantId, "system", "workflow", def.Id, []), ct);
        await runner.ExecuteAsync(def.ToJson(), payload, ct);
    }
}

What happened?

  • WorkflowExecutionHost maps incoming trigger to tenant workflow definition, audits start, and runs JsonWorkflowRunner graph.
  • Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

  1. Connect CRM webhooks to ExecuteTriggerAsync with HMAC verify.
  2. Ship Workflow Studio MVP with publish to SQL.
  3. Meter automation runs in AiUsageDaily feature automation.run.
  4. Add workflow simulation API returning step trace without side effects.
  5. Export workflow metrics to analytics platform briefs.

Remember

Automation platform executes registry workflows from triggers. Audit every run; secure webhooks with HMAC. Combine Studio UI, JSON runner, and agent steps.

Enterprise automation SKU

Customer upgrades from CRM copilot to automation platform.

Outcome: Fifteen custom lead workflows run 40k agent steps/month with full audit.

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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