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The Ultimate Guide on Incorporating AI into your SMB operations

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Vitaliy Mikhailov

06.10.2025

Who’s this guide for?

As Google defines it in its course ‘Introduction to Generative AI’, Generative AI is a discipline in deep learning. It uses artificial neural networks to process both labeled and unlabeled data, using supervised, unsupervised and semi-supervised methods. Sounds too difficult, huh? Well, to put it in simpler terms, GenAi creates new content by learning from existing data in response to prompts. GenAI creates what looks and sounds convincingly human-made.

If you’ve been somewhat tuned in to the latest hype around AI, you are sure to have seen click-bait Linkedin postsI, from ‘ChatGPT is your copywriter’ to ‘AI leads us to a downfall’. None of it is true, although ChatGPT can help you optimize manual work and free up time for more creative, high-stakes processes that contribute to business growth.

Does it take a genius (or a DevOps geek) to introduce AI to your daily work? Hardly so. This guide breaks down the concept, explains what AI really boils down to and shares quality prompts for daily business tasks. If you feel innovative, then the bonus section will walk you through the available AI solutions for SEO, content generation and content repurposing.

If you are a business owner excited to go AI-first—or at least AI-adaptable—the guide is for you. While AI may seem scary or require some tech-savvy background, it is in fact tamable. This guide will help you understand how to introduce AI to your business and operations so it has real impact and drives your business forward.

Section 1. What is Generative AI?

Generative AI represents the most visible and exciting aspect of today’s AI landscape. The most compelling proof is the recent September 2025 report by OpenAI and Harvard ‘How people use ChatGPT’ revealing that ChatGPT reached over 700 million active users by 2025, which represents nearly 10% of the world’s adult population. Its intellectual capability goes beyond analyzing or compiling available information—it is now able to create new, original content. Head over to ChatGPT right now and ask it to draft an email template for new users — there you go, Generative AI sets in motion right before your eyes.

For small businesses, this creative super-power of pretty much free AI is beyond invaluable. To a large extent, most otherwise manual but creative tasks, like writing blog posts, customer service responses, social media posting and even design ideas, can now be safely delegated to AI. Turn any AI tool into an AI agent to have a creative partner for every one of your business operations. It hurts to say, but—well, AI exceeds human abilities when it comes to speed. Its calculating and analytic powers allow it to make up drafts in seconds for any purpose, Yomu AI found in its experiment where they summarized 50 research papers in an hour. A human talent steps in as a refiner and a humanizer who corrects the tone of voice and removes openly artificial bits and pieces.

The foundation of today’s AI conversation centers around Large Language Models or LLMs. An LLM is essentially a sophisticated computer program trained on enormous amounts of text—all that has ever been published to the internet, from books to websites to tweets. A language model learns to put words in a sentence from analyzing trillions of text lines. In other words, it recognizes patterns and predicts what should come next in a sentence, thus mimicking human speech.

What makes LLMs “large” is versatility. Previously, an AI tool was built for a specific task (think of DeepDream by Google for photo editing—no prompting, no ‘think with me’ stuff, just image augmentation). Modern LLMs are far more ambidextrous. Stanford University’s article ‘AI Demystified: Introduction to large language models’ explains that they can perform a wide range of language-based activities: writing from scratch, summarizing, analyzing, composing answers and even generating code.

Does it end with text, though? Today’s AI landscape includes specialized models designed for different types of content creation. Diffusion models back up popular image generators like DALL-E, Midjourney, and Stable Diffusion. These systems learn to create images by starting with random noise and gradually refining it into coherent visuals based on text descriptions.

Generative Adversarial Networks (GANs) represent another approach to creative AI, often used for high-quality image generation and video creation. Meanwhile, specialized audio models can generate music, sound effects, and even realistic speech synthesis. Some newer models are multimodal, meaning they can work across different content types—understanding both text and images, or creating videos with synchronized audio.

Section 2. Generative AI Agents in action

So you got an image to prepare and a project mockup to build and tons of tasks you’d love to delegate to someone. Where do you go, beyond the popular ChatGPT? These models have become household names in today’s AI-driven world.

ChatGPT

ChatGPT (developed by OpenAI) was the breakthrough that brought AI to mainstream attention. Built on the GPT series of LLMs, it excels at conversational interactions and is known for being approachable and creative. ChatGPT can browse the web, generate images through integration with DALL-E, and handle a wide variety of tasks, making it a popular choice for users who want an all-in-one AI tool.

Free Plan: $0 for basic features and regular limits.
ChatGPT Go: ~$4.55/month for increased daily limits, but only in certain regions.
ChatGPT Plus: $20/month for advanced models, priority access and more features.
ChatGPT Team: $25–$30/user/month for small teams with more collaborative features.
ChatGPT Pro: $200/month for unlimited use of advanced models, perfect for heavy users and researchers.
ChatGPT Enterprise: Custom pricing (reported ~$60/user/month) for enterprise-level features and controls.

Claude

Claude (created by Anthropic) produces more natural, nuanced writing and is, as generally agreed, excellent at complex analytical tasks. Many users find Claude’s responses feel more human and require less editing, particularly for business writing and research tasks. Claude can handle very long documents and conversations, making it valuable for in-depth work.

Free Plan: $0 for basic access with usage limits.
Claude Pro: $20/month (or $17/month if billed annually) for priority access and all models including Claude 3 Opus.
Claude Max: $100/month (5x Pro usage) or $200/month (20x Pro usage) for heaviest users and enterprises.
Team Plan: $30/user/month (min. 5 users) for collaboration tools, higher limits.
Enterprise Plan: Custom pricing for maximum capacity, security, advanced admin and support.

Gemini 2.5 Pro

Gemini 2.5 Pro (developed by Google DeepMind) stands out for its advanced reasoning capabilities and integration with Google’s ecosystem. It is designed to support complex problem-solving, coding, and multi-modal inputs, including images and text. Gemini 2.5 Pro is favored by users who seek a powerful, versatile AI assistant that combines cutting-edge language understanding with real-time access to information and creative generation.

Free plan is not available, but free API is available with strict rate limits for evaluation.
API pricing:
- Up to 200,000 tokens: $1.25/million input tokens, $10/million output tokens.
- Over 200,000 tokens: $2.50/million input tokens, $15/million output tokens.
Image input: $0.005 per image.
Search grounding: 1,500 free requests/day, then $35 per 1,000 requests.

DeepSeek R1

DeepSeek R1 (from DeepSeek) is a cutting-edge LLM focused on advanced reasoning, problem-solving, and real-time decision-making rather than a conversational chat tool like ChatGPT. It excels at understanding user intent and delivering highly relevant, context-aware answers from large datasets or the internet. DeepSeek R1 is popular in enterprise and research contexts where precise and comprehensive data discovery is critical. It is open source and it is accessible as an API.

$0.55/million input tokens, $2.19/million output tokens (DeepSeek official).
Azure and other providers range from $0.00135–$1.485/1K input tokens, $0.0054–$5.94/1K output tokens (depending on provider/region)

Perplexity

Perplexity is an AI-powered search and answer engine that leverages large language models to provide concise, context-aware responses with sources cited. It is not an LLM in itself, however, it is commonly mentioned along with the names we mentioned above. It is particularly valued for real-time information retrieval and research assistance, combining natural language understanding with web search to deliver precise answers. Perplexity is popular among users who need quick, reliable insights backed by references rather than broad generative capabilities.

Free Plan: $0 for basic access with daily query limits.
Pro Plan: $10–$15/month for higher usage limits, priority access, and enhanced features.
Team Plan: custom pricing for collaborative use with advanced administration and increased quotas.
Enterprise Plan: custom pricing with dedicated support, security, and API access tailored to organizational needs.

Section 3. Effective AI Prompting

Whatever AI you talk to, the secret to a helpful and meaningful interaction is a structured request. Any task you feed to AI needs to have these elements to hit the bull’s eye:

Persona: Define who the AI is acting as.
- You are an experienced social media strategist specializing in LinkedIn content marketing for businesses.
Task: Clearly state what you want done.
- Create a comprehensive 4-week LinkedIn content plan that will increase engagement, establish thought leadership, and generate leads for my business.
Context: Provide relevant background information
- We’re a mid-sized digital marketing agency that specializes in helping B2B SaaS companies scale their online presence. We post sporadically (2-3 times per week). Our main goals are generating qualified leads and establishing our CEO as a thought leader in the SaaS marketing space. Our target audience includes marketing directors, CMOs, and founders at B2B SaaS companies with 10-500 employees who struggle with lead generation and customer acquisition. The USP is our data-driven approach and 90% client retention rate.
Format: Specify how you want the output structured.
- Give me a content calendar with weekly themes clearly marked in a format like this: Day/Content Type/Goal for each post. Also explain the content mix breakdown, e.g. how many posts go to what content vertical.

Let these simple rules of thumb guide you whenever you decide to interact with an AI model. Sometimes there is just no time for proper prompt writing, and it’s fine. But making the most out of your AI session is possible if you ask the question correctly, helping the model grasp your request.

AI Prompting Laws

Thou Shalt Be Specific and Precise

Vague prompts = vague results. Instead of “Explain marketing,” use “Explain three digital marketing strategies for small e-commerce businesses with budgets under $5,000”.

Thou Shalt Use Natural Language

Write prompts as if you’re having a conversation with a knowledgeable colleague. Avoid overly technical jargon unless necessary for your specific use case.

Thou Shalt Provide Clear Instructions

Include explicit “do” and “don’t” statements to guide the AI’s response. For example: “Do include pricing comparisons. Don’t include companies that only serve enterprise clients.”

Thou Shalt Structure Complex Requests

Break multi-part tasks into numbered steps or bullet points. This helps the AI address each component systematically without missing details.

Section 4. Model Prompts and Considerations

FUNDAMENTAL TEMPLATE STRUCTURE

ASSIGNMENT

Role: You are a [specific expert role] with [experience/credentials]
Mission: [clear objective]

DIRECTIVES

Primary Task: [major instruction on what to accomplish]
Sub-tasks:
– [specific step 1]
– [specific step 2]
– [specific step 3]

ASSIST (if possible)

Background: [relevant context/situation]
Target Audience: [who this work is for]
Key Constraints: [limitations/requirements]
Examples (if possible):
- Input: [example]
- Output: [example]

PARAMETERS

Output Format: [structure: bullets, paragraphs, question & answer, code, etc.]
Length: [word count, sections, etc.]
Tone: [professional, casual, technical, etc.]
Focus Areas: [what to emphasize]

TEMPLATE CUSTOMIZATION

Model-Specific Notes: [any special instructions for this AI model]
Validation Check: [if applicable – what success means in this context]

FIRST AID TEMPLATE

You are a [role] tasked with [main goal].
Context: [background information and situation]
Your specific tasks:
1. [action verb] + [specific requirement]
2. [action verb] + [specific requirement]
3. [action verb] + [specific requirement]

Requirements:
– Output format: [desired structure]
– Length: [scope/size]
– Include: [necessary elements]
– Avoid: [what must not be included]

Example (optional):

[give 1-2 examples of desired output]
Success criteria (optional):
[how to measure completion]

MODULAR BLOCKS FOR CUSTOM PROMPTING

You can shuffle these blocks to design custom prompts.

Role Modules

Expert: “You are a [domain] expert with [X years] experience in [specialty]”
Analyst = “You are a strategic analyst specialized in [field]”
Creator = “You are a creative professional focused on [medium/type]”
Advisor = “You are a trusted advisor helping [target audience] with [challenge]”

Job Modules

Analytic work = “Examine [input] and identify [patterns/insights/issues]”
Creation = “Generate [deliverable] that [specifications]”
Comparison = “Evaluate [options] based on [criteria] and recommend [outcome]”
Synthesis = “Combine [sources] to produce [unified output]”

Output Format Modules

Structured = “Organize response with clear headers and subsections”
Bulleted = “Present as bulleted lists with brief explanations”
Narrative = “Write in flowing paragraph format”
Tabular = “Format as a table with columns: [specify columns]”

Quality Control Modules

Step-by-step = “Show your reasoning process step by step”
Listing sources = “Reference information sources when making claims”
Validation = “Double-check accuracy and highlight any uncertainties”
Iteration = “Ask clarifying questions if the request is ambiguous”

LET’S PRACTICE

A sound prompt might look something like this:

You are a marketing strategist. Create a social media campaign for our new app.

Context: B2B productivity app launching next month
Target: Small business owners

Tasks:
1. Develop 3 platform strategies (LinkedIn, Twitter, Facebook)
2. Create 5 sample posts per platform
3. Suggest posting schedule

Format: Organized by platform with explanations
Length: ~500 words total

But if you added delimiters to help the model navigate the prompt better, you will have a far more structured prompt that conspicuously outlines the sections of your task.

## ASSIGNMENT
Role: You are a senior digital marketing strategist with 8+ years in B2B SaaS marketing
Mission: Design a comprehensive social media launch campaign that drives app downloads and user engagement

## DIRECTIVES
Primary Task: Develop a 30-day social media campaign strategy for our productivity app launch

Sub-tasks:

Analyze platform-specific approaches for LinkedIn, Twitter, and Facebook
Create content calendar with specific post examples
Define success metrics and optimization tactics

## ASSIST
Background: B2B productivity app targeting small business owners (5-50 employees), launching in 3 weeks, $50K marketing budget
Target Audience: Business owners struggling with team coordination and project management
Key Constraints: Must maintain professional tone, comply with platform guidelines, measurable ROI focus
Example of Output: LinkedIn: “Small business owners: Are scattered tools killing your team’s productivity? Our new app centralizes [specific benefit]. Early access link in comments. #SmallBusiness #Productivity”

## PARAMETERS
Output Format: Structured sections by platform, with subsections for strategy, content samples, and metrics
Length: 800-1000 words total
Tone: Professional yet approachable, data-driven
Focus Areas: Lead generation, brand awareness, user education

## TEMPLATE CUSTOMIZATION
Success Criteria: Each platform strategy includes rationale, 5 sample posts, posting frequency, and 3 KPI metrics

GETTING PERSONAL

ChatGPT and Claude: These conversational models respond well to detailed context, examples, and iterative refinement. Use few-shot prompting (providing 2-3 examples) to demonstrate desired output style.

Example: You are a senior market research analyst specializing in B2B SaaS and digital marketing tools. Conduct a comprehensive market analysis of AI SEO tools targeting Small and Medium-sized Businesses (SMBs) in North America for 2025.

Gemini 2.5 Pro: Excels with structured prompts that clearly separate instructions from examples. Use delimiters to organize different sections of your prompt.

<<<< PROMPT START >>>>

==== INSTRUCTIONS ====
You are a software engineer expert in Python and RESTful API design.
Your mission is to implement a robust, well-documented REST API endpoint that manages “tasks” for a simple to-do application.

==== REQUIREMENTS ====

Language: Python 3.10+
Framework: FastAPI
Data store: In-memory list of dictionaries
Endpoint: POST /tasks
Request payload: { “title”: string, “description”: string, “due_date”: “YYYY-MM-DD” }
Response: 201 Created with JSON { “id”: int, “title”: string, “description”: string, “due_date”: string, “created_at”: ISO8601 }
Validation:
– title: non-empty, max 100 chars
– due_date: valid future date
Error handling: return 400 Bad Request with clear error message for invalid payload
Documentation: include OpenAPI docstrings for endpoint and models
Testing: provide one pytest function to verify successful task creation

==== EXAMPLE ====
Input (POST /tasks):

json

{

“title”: “Write blog post”,

“description”: “Draft an article on prompt engineering.”,

“due_date”: “2025-09-01”

}

Expected Response:
Status: 201 Created
Body:

json

{

“id”: 1,

“title”: “Write blog post”,

“description”: “Draft an article on prompt engineering.”,

“due_date”: “2025-09-01”,

“created_at”: “2025-08-19T09:41:00Z”

}

==== DELIVERABLES ====

main.py: FastAPI application with POST /tasks endpoint
models.py: Pydantic models for request and response
test_tasks.py: pytest file with one test for successful creation
Comments: Brief inline comments explaining key logic

<<<< PROMPT END >>>>

DeepSeek R1: This reasoning model performs best with minimal prompting. Avoid chain-of-thought instructions or excessive examples, as it handles reasoning internally. Use phrases like “Take your time and think carefully” for complex problems.

Take your time and think carefully. You are a seasoned product strategist. Generate three innovative digital product ideas for the smart kitchen appliances market.

Deliverables for each idea:

Idea title
One-sentence elevator pitch
Three key features
Primary target user segment

Constraints:

Focus on AI-driven personalization and connectivity.
Prioritize seamless integration with existing smart home ecosystems.
Keep descriptions concise and free of technical jargon.

Perplexity: Focus on search-friendly language and avoid traditional LLM techniques like few-shot prompting. Be specific about what information you need and include relevant keywords that would appear on web pages.

Help me create a list of customer development interview questions for a SaaS startup. Include keywords like “customer pain points,” “product-market fit,” “user behavior,” and “feature validation.” I need at least 10 open-ended questions that explore:

Customer pain points and challenges
Desired outcomes and success metrics
Current solutions and workarounds
Willingness to pay and purchase triggers
Feedback on prototype concepts

Bonus Ideas

Iterative Refinement
Don’t expect perfect results on the first try. Use follow-up prompts to refine and clarify: “Can you make this more technical?” or “Focus specifically on budget considerations”.

Role-Playing Prompts
Use “Act as if you are…” to get responses tailored to specific perspectives or expertise levels.

Template Approach
For repetitive tasks, create reusable prompt templates that you can adapt with specific details while maintaining consistent structure.

The freelancer is using AI to automate routine work.

Section 5. Think With Me: Let’s Freestyle

Robert Scoble, the co-author of The Fourth Transformation, famously tweeted: “You can talk to AI when your colleagues don’t want to talk to you anymore.”

And it is, in fact, AI’s super-power, among many. Along with multiple generative abilities, it also thinks with you, fostering imagination and ideation. A free creative e-buddy of sorts, ready to brainstorm with you on any topic. Here is how you can access this ‘Think with Me’ mode in the models discussed above: