From Prompt Engineering to Agent Engineering (Udemy.com)

MASTER PROMPT ENGINEERING AND BUILD INTELLIGENT AI AGENTS FOR MARKETING, BUSINESS, AND BEYOND

This course contains the use of artificial intelligence.

The future of work is here — and it's powered by artificial intelligence. In today's world, mastering the shift from prompt engineering to agent engineering is no longer just a trend — it's a critical skill that separates forward‑thinking professionals from those left behind.

If you've ever wondered how AI goes beyond static prompts to operate autonomously — making decisions, executing multi‑step workflows, and generating highly relevant outcomes on its own — this is the definitive course for you.

Led by AI educator and digital marketing expert Anton Voroniuk, this Udemy program takes you through a complete, three‑part journey — from your very first prompt to deploying and managing a fleet of production‑grade AI agents. Across 430+ lectures, you'll go from crafting precise prompts for today's leading models — ChatGPT, Claude, Gemini, DeepSeek, and Copilot — to building fully functional AI agents on the platforms real businesses are using right now, and finally to orchestrating those agents responsibly at scale.

Today, knowing how to use AI tools is no longer enough. To stand out, you need to know how to design AI agents that operate autonomously across platforms — and how to run them safely once they're live. This course gives you that edge, one part at a time.

A COURSE BUILT IN THREE PARTS

Part 1 — Prompt Engineering. Build the foundation: how to think like an AI collaborator, the frameworks that make your prompts reliable (RACE, ReAct, Tree‑of‑Thought, Self‑Ask, and more), and advanced tactics like prompt chaining and self‑refinement. Then put it all to work in a full applied workflow — SEO, content, and outreach — that turns into a repeatable content production system your whole team can run.

Part 2 — The Basics of Agent Engineering. Make the pivot from prompting to agents: what an AI agent actually is, how it's architected, the different types you'll build, where agents create real value across marketing, sales, support, finance, and legal, and an honest look at what agents can't do yet. You'll close this part with your first hands‑on agent builds — a customer support agent and a booking agent — before the deep platform tour begins.

Part 3 — Detailed Tools Walkthrough. The heart of the course: a hands‑on, platform‑by‑platform build across everywhere businesses are actually deploying agents today — ChatGPT (MyGPTs and Workspace Agents), Claude (Projects, Skills, and Cowork), Manus, Make, Digital First, Microsoft Foundry, ElevenLabs and VoiceGenie for voice agents, and N8N. From there you'll go deeper — agent memory, context rot, autonomy, running agents locally — and finish by orchestrating a full fleet of agents in production with Trinity, plus AI ethics and career growth.

WHAT YOU WILL LEARN

Part 1: Prompt Engineering Skills & Frameworks

• Best practices for creating prompts that reliably produce accurate, high‑quality responses, and why prompts fail — with the fixes for each common mistake

• Core frameworks for precision and consistency: the RCTC prompt anatomy (Role‑Context‑Task‑Constraint), the RACE Framework, and the Business Context Method

• Advanced reasoning frameworks — ReAct, Tree‑of‑Thought, and Self‑Ask prompting — for tackling complex, multi‑step tasks

• Advanced tactics: self‑consistency, step‑back prompting, contrastive examples, prompt chaining, meta‑prompting, directional stimulus, self‑refine, multi‑persona debate, and automatic prompt engineering

• How to evaluate AI responses for accuracy, relevance, and context, and fix errors before they reach a client or a team

• Applying all of it end to end in one real workflow: SEO strategy, keyword research, content creation, outreach campaigns, and a competitor tracker — then packaging it into a content production system with briefs, brand voice, and review standards

Part 2: The Basics of Agent Engineering

• The evolution from prompts to agents: what an AI agent actually is, how it's architected, and the different types of agents — from simple to complex

• Chatbots vs. agents: the real difference, and how to tell which one a task actually needs

• A survey of the agent tools landscape — browser & enterprise agents, no‑code/low‑code builders, and code‑first frameworks — so you know which category fits before you commit to a specific platform

• Agent use cases across marketing, sales, customer support, finance, legal, and operations

• Setting realistic expectations: what agents can (and can't) do today, and the most common myths about them

• Your first hands‑on agent builds — a customer support agent and an appointment‑booking agent — using tools like Elsa for early business insights

Part 3: Detailed Tools Walkthrough

• Hands‑on agent builds inside ChatGPT (MyGPTs and Workspace Agents — including scheduling, CRM automation, analytics agents, and credit‑based budgeting) and Claude (Projects, Artifacts, Claude Code, reusable Skills, and Cowork for background file, research, and reporting automation)

• Browser and platform agents, including ChatGPT Agent Mode and a deep, practical dive into Manus for marketing, content, and workflow automation

• No‑code and low‑code agent building with Make (triggers, actions, AI automations, and full agent builds) and N8N (nodes, memory, tools, and MCP integrations)

• Purpose‑built agent platforms: Digital First for marketing agencies, Microsoft Foundry for enterprise multi‑agent workflows, and ElevenLabs and VoiceGenie for voice AI agents in sales and support

• Advanced agent engineering: giving agents memory with Supabase and pgvector, the "vibe coding" workflow with Cursor IDE and MCP servers, understanding context rot in large language models, and the shift toward autonomous agents

• Running agents locally, then orchestrating a full fleet of them in production with Trinity — deployment, security, governance, and scaling

• AI ethics and responsible use — copyright, bias, privacy, and human oversight — and how to turn everything you've learned into career growth

WHAT YOU'LL ACHIEVE AFTER THIS TRAINING

• Write prompts that reliably produce accurate, high‑quality results across every major AI model

• Build and operate AI agents that work autonomously — from a single MyGPT to a coordinated fleet in Trinity