From Hours to Minutes: Your First Steps into Building AI Agents and Automations

The world of Generative AI is exploding. Every week, a new model, framework, or tool promises to change the game. But how much of this groundbreaking technology actually makes it into our daily workflows? Less than 5% of these updates reach real-world application. This creates a massive gap between what AI can do and what we are doing with it.

The Problem with ChatGPT: Why We Need AI Agents

We’ve all used ChatGPT. It’s brilliant for generating content, answering questions, and even helping with code. But it has its limits. Can ChatGPT replace your job? The workshop attendees overwhelmingly said no.

Here’s why:

• It’s Passive: LLMs like ChatGPT are instruction-based. You have to guide them at every step.

• It Lacks Real-Time Knowledge: Most models have a "knowledge cutoff date." Ask about a recent event, and they'll draw a blank.

• It Can’t Connect to the World: By default, LLMs can't browse the internet, access your databases, or interact with other applications. They are brains in a jar.

This is where AI Agents come in. An AI Agent is more than just an LLM; it's an LLM that can think and do. It’s a goal-based system that can plan, self-critique, and, most importantly, connect to external tools to execute tasks.

Part 1: Your First AI Automation - The Smart Email Assistant

Imagine you’ve just hosted a webinar with hundreds of attendees. You want to send each person a personalized follow-up email. Doing this manually would take hours. With AI automation, it takes minutes.

Using a no-code platform like Make.com, you can build an intelligent email generator from scratch.

The Workflow:

1. The Trigger: The automation starts by "watching" a Google Sheet. When a new row with an attendee's name, company, and job title is added, the process kicks off.

2. The AI Brain (OpenAI/ChatGPT): The information from the new row is sent to ChatGPT with a carefully crafted prompt. The prompt tells the AI who it is (e.g., "I am Satvik, founder of Build Fast with AI") and what it needs to do ("Write a personalized email to this person, referencing their role at their company, about our 8-week Generative AI course").

3. The Action: The AI-generated email is then automatically populated back into the Google Sheet in a new column. From there, it can be easily connected to a Gmail module to create a draft or even send the email directly.

This simple, drag-and-drop process saves an incredible amount of time, turning a 10-hour task into a 5-minute setup.

Build Your First AI Agent: A Beginner’s Guide

Artificial Intelligence is no longer just a buzzword—it’s a toolkit that anyone can use to build real solutions. Whether you’re a student, professional, or entrepreneur, creating your own AI Agent can give you a competitive edge. The best part? You don’t need to be a hardcore coder to get started.

In this blog, we’ll walk through what AI agents are, why they matter, and how you can build your first one today. Plus, we’ll give you ready-to-use prompts so you can immediately put AI into action.

🤖 What is an AI Agent?

An AI Agent is like your personal assistant—except it never sleeps. It can:

• Research topics on the internet.

• Summarize complex documents.

• Generate reports, content, or insights.

• Automate repetitive workflows.

Think of it as combining the power of ChatGPT or Gemini with the ability to take actions—like sending emails, updating spreadsheets, or analyzing data.

Why You Should Build One

Here’s why building your own AI agent is a game-changer:

• Boost Productivity: Automate boring tasks.

• Save Time: Get answers and summaries instantly.

• Learn by Doing: Building one helps you understand AI deeply.

• Career Edge: AI skills are in huge demand.

How to Build Your First AI Agent

1. Pick Your Platform: Start with tools like Make.com, n8n, or Python if you’re technical.

2. Choose an AI Model: Gemini, GPT-4o, or Claude can power your agent.

3. Define the Task: Research, automation, or customer support?

4. Test and Iterate: Run small experiments, then expand.

Pro Tip: Don’t aim for perfection. Ship a simple MVP (minimum viable product) and improve as you go.

Example Use Cases

• A Market Research Agent that builds customer personas.

• A Stock Market Agent that tracks companies and generates investor profiles.

• A Research Agent that pulls detailed information on any person or topic.

These are not just ideas—you can build them today.

Practical AI Prompts You Can Try Today

Here are some copy-paste prompts to plug into your AI agent setup. They’ll help you unlock instant value:

📊 Market Research Prompt

Generate a detailed buyer persona for our [Product/Service]. Include demographics like age, gender, income level, education, and location. Detail psychographic elements such as interests, lifestyle, and values. Analyze purchasing habits, including preferred shopping channels, frequency, and factors influencing their buying decisions. Highlight their key challenges and pain points. Explain how our product can resolve these issues, aligning with their values and lifestyle.

📈 Stock Market Prompt

Generate a focused investment profile for [Stock/Company Name]:

Investor Demographics: Typical age, risk appetite, location, and investment experience of investors interested in this stock.
Key Motivations & Values: Growth, income, stability, innovation, or sustainability focus.
Investment Behaviors: Common research methods, holding periods, and main factors that influence buy/sell decisions.
Main Challenges & Risks: Highlight the top risks and concerns for a 5-year investment horizon—business, industry, or external factors.
How This Stock Addresses Them: Summarize what makes [Company] attractive for long-term investors and how it aligns with their values or solves their concerns.
End with a brief objective view of the stock’s long-term prospects.

🔍 Research on Anyone Prompt

Do intensive research on {Person} and give me a massive report on everything you find.

Part 2: Building Your First AI Agent - The Deep Research Assistant

While automation handles repetitive tasks, agents can tackle complex, multi-step problems. The simplest form of an agent is an LLM connected to the internet.

When asked "Who won the recent IPL trophy?", a standard LLM might fail, citing its old knowledge base. But an agent, recognizing the need for current information, will:

• Think: "I don't have this information. I need to search the web."

• Act: It performs a Google search for "IPL trophy winner 2025."

• Synthesize: It reads the search results and provides an accurate, up-to-date answer.

Taking it a Step Further: Market Research in Minutes

Advanced research agents using tools like Grok and Gemini’s Deep Search can conduct a full market analysis for a new startup: "Indian Handcrafted Leather Shoes by Local Artisans."

The AI agent didn’t just give a simple answer. It executed a complex plan:

• It Planned: Breaking down the request into sub-tasks: demographic analysis, psychographic profiling, competitor analysis, and identifying market challenges.

• It Acted: In under a minute, it browsed over 80 different websites, reading market reports, articles, and forums.

• It Delivered: A comprehensive, multi-page report complete with target audience profiles, purchasing habits, and key insights—all with citations linking back to the original sources.

A task that would take a team of human analysts two to four weeks was completed in less than two minutes.

You can even build a custom agent yourself. Using a tool like n8n, you can visually connect components: a chat input, an agent module, an LLM like Gemini, and tools like a SERP API for Google Search or even a calculator. For those comfortable with a little code, a powerful agent can even be built with just five lines of Python, proving that this technology is more accessible than ever.

Bonus: A Sneak Peek into the Future of AI

To cap it all off, the workshop included a glimpse of a confidential Google tool that allows for incredible AI-powered image editing. With a simple prompt, a casual photo was instantly transformed into a professional headshot with a suit and tie. Another prompt realistically aged the photo by ten years. These are the kinds of tools that will soon be at our fingertips.

Your Journey Starts Now

The session made one thing clear: AI is not just a tool for developers. It's a force multiplier for everyone. Whether you're a product manager, a founder, or a student, understanding how to build and leverage AI agents and automations is becoming an essential skill. By starting with simple, practical projects, you can begin to close the gap and harness the true power of this transformative technology.

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⚙️ Automation Tools

• Email Automation: Make

• Internet Agent: n8n

• Data Analysis: Claude

🧠 Agents

• Grok DeepResearch: grok.com

• Gemini: gemini.google.com

• Code: Google Colab Notebook

🔑 Get Your API Keys

• OpenAI API Key

• Google AI Studio

• Serp API (Google Search)