🔍 What Are AI Agents?
Definition
| Type | Description |
|---|---|
| Non-Agentic Workflow | One-shot prompting (e.g., “Write an essay on topic X.”) |
| Agentic Workflow | Task broken into steps, revisited iteratively |
| Fully Autonomous Agent | Determines steps, tools, revises itself, executes end-to-end |
Key Insight
- AI agents go beyond static prompts. They reflect, iterate, plan, and can use tools.
- Most current systems are not fully autonomous — they rely on structured agentic workflows.
🎨 Agentic Design Patterns
Mnemonic: Red Turtles Paint Murals
| Pattern | Description |
|---|---|
| Reflection | AI reviews and improves its own output (e.g. checking code for bugs) |
| Tool Use | AI uses web search, code execution, calendar access, etc. |
| Planning | AI figures out steps, tools, and sequencing for a task |
| Multi-Agent | Multiple AIs collaborate, specialize in roles, and interact to solve tasks |
🤖 Multi-Agent Architectures
1. Single AI Agent (Building Block)
Mnemonic: Tired Alpacas Make Tea
| Component | Description |
|---|---|
| Task | What the agent is supposed to do |
| Answer | The expected output |
| Model | The LLM or AI model used |
| Tools | APIs, calculators, or search tools used by the agent |
Example:
A travel planner agent that books a Tokyo trip using Google Maps, Skyscanner, and booking APIs.
2. Common Multi-Agent Patterns
| Pattern | Structure | Example |
|---|---|---|
| Sequential | Assembly-line (Agent A → B → C) | Document processing: extract → summarize → actions → store |
| Hierarchical | Manager agent delegates to specialized sub-agents | Business reporting: market trends, sentiment, metrics, all rolled up into one decision |
| Hybrid | Mix of sequential and hierarchical with feedback loops | Autonomous vehicles: route planner + real-time sensors |
| Parallel | Agents handle different subtasks simultaneously | Large-scale data analysis: chunks processed independently |
| Asynchronous | Independent agents work at different times; great for uncertainty and monitoring | Cybersecurity: real-time traffic, pattern detection, anomaly response |
| Floats (Meta) | Systems of systems; combine all patterns | Complex, decentralized AI ecosystems like those in large orgs or real-time responsive bots |
🛠️ No-Code AI Agent with n8n
Toolstack
- n8n: Workflow automation
- Telegram: Messaging UI
- OpenAI / LLM of choice: Core agent
- Google Calendar: External tool
Example Workflow: “InkyBot”
| Step | Action |
|---|---|
| 1 | Telegram triggers message input |
| 2 | Detects input type (text or voice) |
| 3 | Voice → Transcribed via Whisper |
| 4 | Sends query to agent (GPT-4, Claude, Llama, etc.) |
| 5 | Agent uses tools to read and create Google Calendar events |
| 6 | Responds with prioritized list and updated calendar |
- Flexible: Easily extendable to multiple agents.
- No-code: Built entirely in GUI environment.
💡 AI Agent Business Opportunities
Key Insight from Y Combinator
“For every SaaS company today, there will be a corresponding AI agent company.”
Idea Generator
| SaaS Company | AI Agent Version Example |
|---|---|
| Salesforce | AI CRM Assistant that manages leads and sends emails |
| Canva | AI Graphic Designer that takes prompts and brand kits |
| Notion | AI Workspace Assistant that summarizes notes and plans weekly tasks |
| Shopify | AI Store Manager that runs product ops, inventory, and analytics |
✅ Assessment Questions
- What is an AI agent? How is it different from one-shot prompting?
- What are the four agentic design patterns? (Mnemonic: Red Turtles Paint Murals)
- What does “Tired Alpacas Make Tea” stand for?
- Name three multi-agent architecture patterns and explain them.
- What is the difference between agentic and autonomous AI systems?
- Describe how you might build an AI agent version of a SaaS company.
- What are the advantages of multi-agent vs. single-agent systems?