Build a customer service AI agent from scratch — no CS degree needed
Learn to design, build, and deploy custom AI agents that handle real customer service workloads — without a computer science degree. Go from zero to a fully functional, business-ready agent in days, not months.
"I'll never teach you a concept I can't immediately tie to a working result in your business — that's the only standard that matters here."— Sherrie K Licon
What you'll learn
What you'll be able to do
- Design a custom AI agent architecture tailored to a specific customer service workflow
- Integrate a large language model (LLM) with your own knowledge base, FAQs, and product data
- Build escalation logic so the agent hands off complex tickets to human agents seamlessly
- Connect your agent to live channels — website chat, email, or WhatsApp — using APIs and webhooks
- Evaluate and improve agent performance using real conversation logs and quality metrics
- Deploy and monitor a production-ready agent with cost controls and safety guardrails in place
How it works
A school that adapts to you
This isn't a set of static videos. Every lesson is generated live and tuned to where you actually are.
We learn your level
A quick placement check tailors your starting point so you're never bored or lost.
Lessons adapt as you go
Each lesson is written for your pace and your goal, adjusting as your skills grow.
Your AI coach keeps you moving
Checkpoints, feedback, and gentle nudges turn progress into a real result.
The curriculum
What's inside your school
6 modules · 18 lessons
Customer Service AI Fundamentals & Agent Blueprint
Establish the conceptual and strategic foundation before writing a single line of code. Students learn how AI agents differ from simple chatbots, why workflow mapping must precede architecture decisions, and how to produce a concrete agent blueprint they will build on throughout the course.
- 1.1How AI Agents Actually Work (No CS Degree Required)Included
- 1.2Mapping Your Customer Service Workflow Before You BuildIncluded
- 1.3Designing Your Agent ArchitectureIncluded
Building Your Knowledge Base & Connecting the LLM
Turn raw company content — FAQs, product docs, policies, past tickets — into a structured, searchable knowledge base, then wire it to an LLM using Retrieval-Augmented Generation (RAG). Students finish this module with a working prototype that can answer domain-specific questions.
- 2.1Collecting & Structuring Your Knowledge BaseIncluded
- 2.2Setting Up Retrieval-Augmented Generation (RAG)Included
- 2.3Prompt Engineering for Customer Service AgentsIncluded
Escalation Logic & Human Handoff
Define when — and how — the agent should stop trying to resolve an issue and route it to a human. Students build rule-based and confidence-score-based escalation triggers and implement a handoff mechanism that passes full context to the receiving agent, ensuring no customer has to repeat themselves.
- 3.1Designing Escalation Rules That Actually WorkIncluded
- 3.2Building Seamless Human HandoffIncluded
Connecting to Live Channels via APIs & Webhooks
Move the agent out of the notebook and into the channels customers actually use. Students learn just enough API and webhook mechanics to deploy confidently, then wire their agent to at least one live channel and handle real-time message events correctly.
- 4.1APIs & Webhooks Crash Course for Non-EngineersIncluded
- 4.2Deploying to Website ChatIncluded
- 4.3Connecting to Email or WhatsAppIncluded
Evaluating & Improving Agent Performance
Close the feedback loop. Students define meaningful quality metrics, build a lightweight evaluation pipeline using real conversation logs, and establish a structured weekly review ritual that turns raw data into actionable improvements — making the agent measurably better over time.
- 5.1Defining the Right Metrics for Your AgentIncluded
- 5.2Analyzing Conversation Logs to Find Failure PatternsIncluded
- 5.3Continuous Improvement: Building a Weekly Review RitualIncluded
Deploying, Monitoring & Governing a Production Agent
Ship a production-ready agent responsibly. Students add cost controls, safety guardrails, and a monitoring stack before go-live, then practice incident response using simulated production failures. The module closes with a capstone in which students launch their complete agent and present it for peer review.
- 6.1Cost Controls & Token ManagementIncluded
- 6.2Safety Guardrails & Content ModerationIncluded
- 6.3Monitoring, Alerting & Incident ResponseIncluded
- 6.4Capstone: Launch Your Production-Ready AgentIncluded
Who it's for
Is this you?
Startup founders
You're fielding support tickets yourself and need an AI agent that actually handles volume — not another tool that creates more work to manage.
Customer success leads
You own the customer experience and want to deploy AI that escalates intelligently, so your human team focuses on the conversations that actually need them.
Product managers
You can map a workflow and own a roadmap — this course gives you the technical fluency to build the agent yourself instead of waiting on an engineering sprint.
E-commerce operators
Your order, refund, and shipping FAQs are eating your team alive — you need an agent connected to your real product data that can answer them without human intervention.
Technical business owners
You're comfortable in a dashboard and can read an API doc, and you're ready to stop paying for black-box chatbots and build something you fully understand and control.
Operations managers
You're responsible for support efficiency and want a production-ready agent with proper monitoring, guardrails, and cost controls — not a proof-of-concept that collapses under load.
Questions
Frequently asked
Your teacher
A note from your teacher
Sherrie K Licon
If you're reading this, I'm guessing you've already sat in a few too many support-queue reviews where the answer is always "we need more people." You know AI should be part of the solution — but every course you've found either talks down to you with surface-level demos, or assumes you have a machine learning team standing by. Neither describes you, and neither was built for what you're actually trying to do.
I built Agent Builders Academy for the person who owns the customer service problem and is ready to solve it directly. Not to hand a requirements doc to an engineering team. Not to buy a black-box chatbot and hope for the best. But to actually design and ship an AI agent that handles real tickets, routes the hard ones to humans, and runs in production without you babysitting it every hour.
Every module in this course follows the same discipline: here's the concept, here's why it matters to your business, here's the working result you'll have by the end of this lesson. When we cover Retrieval-Augmented Generation, you won't just understand what RAG is — you'll have connected it to your own knowledge base and watched your agent pull a real answer from your real product data. When we cover escalation logic, you'll have rules running that actually route the right tickets to the right humans. No "we'll revisit this later." No loose ends.
I also take the parts most courses skip seriously: cost controls so a traffic spike doesn't blow your budget, safety guardrails so your agent doesn't go off-script in a damaging way, and a monitoring setup so you know what's happening in production before your customers tell you something broke. And the weekly review ritual in Module 5 isn't a nice-to-have — it's the habit that separates agents that drift and degrade from agents that quietly get better every week.
You don't need a computer science degree to do any of this. You need a clear blueprint, the right sequence of steps, and examples grounded in actual customer service workflows. That's what this course is. Come build something real.
— Sherrie K Licon
Start your journey today
Join get instant access — learn at your own pace with an AI coach in your corner.
- 6 modules, 18 lessons
- AI-adaptive lessons tuned to your level
- Quizzes & checkpoints to lock in progress
- Your own AI learning coach
- Learn on any device, at your pace
- Full access for as long as you're subscribed