Agentic AI with No-Code Tools

Agentic AI with No-Code Tools is about building intelligent, automated systems (AI agents) that can perform tasks, make decisions, and interact with users — all without writing traditional code.

(Installment Options Available)

Duration: 3 Months

50,000 PKR

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Starting Date

30 Oct, 2025

Introduction

Agentic AI with No-Code Tools is about building intelligent, automated systems (AI agents) that can perform tasks, make decisions, and interact with users — all without writing traditional code. Using no-code platforms like n8n, creators can design workflows visually, connect APIs, add memory and reasoning capabilities, and integrate AI models such as OpenAI or Gemini. This approach empowers non-developers to build powerful, customized AI-driven automations — like chatbots, research assistants, or business process agents — combining AI reasoning with automation, data connections, and user interaction.

Sr. No.	Contents
1	Foundations — What is Agentic AI, No-Code Tools & Terminology What’s an “agent” vs a workflow vs automation vs chatbot Key components: goal, task, tools/APIs, memory, branching/decision making, input/output Introduction to no-code tools: overview of n8n (cloud / hosted), exploring the UI Walkthrough of “Build an AI chat agent with n8n” tutorial: basic workflow, agent node, memory, chat Assignment: sign up for n8n, build a very simple agent: respond to a fixed prompt (“What’s the weather today?”) using a test model
2	Learning Prompting, Model Selection & Memory Writing good prompts: clarity, context, roles, giving examples (few-shot) Choice of AI model providers: OpenAI, Google Gemini etc, trade-offs Using memory: how to store prior messages, context so conversations “remember” previous questions. Lab: Build a chat flow that remembers user’s name and previous preferences; test with multiple inputs.
3	Using Tools / APIs in Workflows What tools are: APIs, HTTP requests, external data sources (news, weather etc), database access How to connect APIs in n8n: HTTP node, webhook, credential setup Example: Use AI Agent + HTTP Request to fetch current data (weather, stock, etc.) and have the agent integrate that in response. Assignment: Build a flow where user asks about “latest news in X topic” → agent fetches news via API → summarizes and replies.
4	Branching & Conditional Logic, Tool Choices Decision nodes / branching: if-then logic in workflows (if user says “help” do this, else that) Handling “unknown” inputs or failure modes (API fails etc) Basic error handling and fallback logic: retry, default response etc Lab: Create workflow with conditional branches; e.g. if user asks for “report”, do one path; if for “summary”, do another; if error, fallback.
5	Persistence & Long-Term Memory What is long-term / persistent memory vs session memory How to store data: Files / databases / spreadsheet / no-code DB (e.g. Airtable, Google Sheets) Fetching the past data and using it in new agent responses Lab: Agent that tracks user’s preferences over time (say favorite topics), stores in a sheet or DB, and personalizes answers accordingly.
6	Creating Multi-Step Workflows / Chaining Agents Multi-step workflows: breaking down tasks (e.g. user asks for research report → agent fetches sources → agent summarises → agent formats) Chaining: having multiple nodes/agents involved in a flow Best practice: clear handoffs, naming, monitoring intermediate results Lab: Build a multi-step flow (source → summarise → format output) using n8n agent + external tool(s).
7	Agent Teams / Multiple Agents (Orchestration) What is multi-agent / agent team: specialized agents (e.g. reporter, verifier, summariser etc) Orchestrator / manager agent: which agent decides which sub-agent to call based on user intent Using separate workflows calling other workflows / using webhooks etc to simulate multiple agents Lab: Build two or more “mini-agents” (e.g. one fetches info, one formats, one checks), and orchestrate via a manager agent or a master workflow in n8n.
8	Safety, Guardrails & Ethical Use Why safety: ensuring responses are appropriate, privacy, abusive user inputs, hallucinations Guardrails: content policy, filters, human approval, moderation nodes Handling sensitive data, GDPR / privacy compliance basics Lab: Add guardrail node: if user requests something sensitive, agent responds with disclaimer or routes to human; test various edge cases.
9	Observability & Testing Logging: capturing user inputs, tool calls, responses; tracing flow execution Metrics: response time, correctness, user feedback etc Testing flows: simulate inputs, check outputs, test edge cases Lab: Instrument one workflow with logs; test with various inputs; produce simple report of “how many tasks succeeded / failed”.
10	Integrations with Business Tools & Automation Integrations: connecting with business tools (CRM, email, spreadsheets, Slack etc) using no-code connectors Automating business workflows: lead generation, notifications, report emailing etc Lab: Build a flow: when new lead comes in (spreadsheet / form), agent processes lead info, sends notification, stores data, maybe summarises lead to email.
11	Deployment, Sharing & Scaling Workflows Deploying workflows / agents: saving, versioning, sharing in n8n Trigger types: webhooks, scheduled flows vs event-driven Handling scale: rate limits, model usage cost, workflow optimization Lab: Publish a workflow/agent, connect to form / webhook, schedule periodic tasks, monitor usage or rate.
12	Final Project & Showcase Pick a capstone no-code project, examples: News Intelligence Agent: collects news, categorizes, sends summary email / Slack Personal Productivity Agent: tracks schedule, reminds, looks up info, formats summary Customer Support Agent: triages queries via form, answers common FAQs, escalates unusual ones to human Multi-agent content creation: research article + summary + formatting + SEO check Build the full agent / workflow — multi-step, integration, memory, safety, testing. Present project: showcase architecture, live demo, challenges, improvement ideas.

Skill Level	Avg Monthly Salary
Junior	75k-100k
Mid-Level	100k - 170k
Advanced	250k- 450k
Freelancer	Earn in millions