Mercor connects professionals with AI training projects where they can review model outputs, evaluate responses, label data, write examples, compare answers, and provide expert-level feedback.

This guide explains what Mercor does, how the work usually looks, who it may be a good fit for, and how to approach it seriously if you want to explore AI training as a potential income stream.

Disclosure: The goal of this guide is not to promise guaranteed work, but to explain the opportunity clearly so you can decide if it is worth trying.

What Is Mercor?

Mercor is a talent and AI training platform that connects skilled professionals with companies building advanced AI systems.

In simple terms, Mercor helps AI companies find people who can bring real-world judgment into the training process. That might mean reviewing an AI-generated legal explanation, checking whether a medical response is accurate, evaluating code, comparing financial analysis outputs, or rating whether a model followed instructions correctly.

For contributors, this means the work is not just “clicking labels” or doing low-value online tasks. At the higher end, it can involve careful expert review, structured reasoning, and professional judgment.

What Does “Labeling AI Output” Actually Mean?

The phrase “labeling AI output” can sound basic, but in modern AI training it often means much more than tagging data.

Depending on the project, you may be asked to:

• Review an AI-generated answer and decide whether it is correct
• Compare two AI responses and choose the stronger one
• Explain why one response is better than another
• Flag hallucinations, factual errors, or unsupported claims
• Evaluate tone, structure, clarity, and completeness
• Rewrite an answer so it meets a higher standard
• Create examples that show how an expert would solve a task
• Apply a rubric consistently across many responses
• Identify whether an AI response follows instructions
• Test whether the model can handle complex domain-specific scenarios

This is important because AI systems do not improve only through more data. They improve when humans define what “better” means.

Why Human Experts Still Matter in AI Training

AI models can generate fluent text, code, summaries, and analysis. But fluency is not the same as correctness.

A model can sound confident and still be wrong. It can write a legal explanation that misses a key limitation. It can produce code that looks clean but fails in production. It can summarize medical information in a way that feels helpful but leaves out a safety consideration.

That is why expert feedback matters.

In AI training work, human preference judgments help models learn what good output looks like. Humans compare model outputs, indicate which response is better, explain why, and create signals that can improve future model behavior.

In other words, the human expert is not just correcting grammar. The expert is helping define quality.

For domain-specific AI, this becomes even more important. A general evaluator may be able to judge whether an answer is clear. But a physician, lawyer, engineer, analyst, or scientist can judge whether the answer is professionally sound.

How Mercor Works for Experts

The exact process may vary by project, but Mercor generally follows a simple path.

1. You Create a Profile

You start by signing up and sharing your background, experience, education, and areas of expertise.

This matters because Mercor is not only looking for general AI workers. It is often trying to match people to projects where their professional background is useful.

2. You Complete AI Assessments

Applicants may be asked to complete evaluations, assessments, or interviews related to their background. The goal is to understand your expertise and determine which projects may fit.

This is where you should take the process seriously. Treat it like a real professional screening, not a casual sign-up form.

3. You Get Matched With Opportunities

If there is a fit, Mercor can connect you to projects aligned with your skills. Some projects may not require prior AI experience, but many specialized projects require strong knowledge, professional experience, or advanced education in the relevant domain.

4. You Work on Scoped Projects

Projects can vary in length, complexity, and pay. Some may be short-term. Others may continue for weeks or months. The important thing is to think of Mercor as a potential source of remote expert project work, not as a guaranteed full-time job.

What Kind of Work Might You Do on Mercor?

Mercor projects can vary, but most AI training work tends to fall into a few practical categories.

AI Response Evaluation

You may review a response and score it based on criteria such as accuracy, helpfulness, safety, tone, reasoning, and instruction-following.

Example: An AI model gives an answer about tax rules, medical symptoms, contract clauses, or Python code. Your job is to evaluate whether the answer is correct, complete, and safe.

Preference Ranking

You may be shown two or more AI responses and asked which one is better.

This is common in AI training projects where the goal is to help models understand what a stronger response looks like. The important part is not just picking a winner, but explaining your reasoning clearly.

Error Identification

You may identify factual errors, missing context, weak reasoning, hallucinations, or unsupported claims. This is especially important in fields like medicine, law, finance, engineering, and scientific research.

Ideal Answer Writing

Sometimes the best way to train a model is to show it what a strong answer should look like. In these tasks, you may rewrite a weak AI response into a better one, following specific constraints around format, tone, depth, and accuracy.

Data Labeling and Classification

Some projects may involve more traditional labeling work, such as categorizing content, identifying entities, tagging examples, or classifying responses against a rubric.

Even when the task sounds simple, the quality of the labeling depends on careful human judgment.

Prompt and Scenario Creation

In more advanced projects, you may create challenging prompts or real-world scenarios that test whether an AI system can reason properly.

For example, a software engineer might create debugging challenges. A lawyer might create contract interpretation scenarios. A finance professional might create valuation or forecasting tasks. A teacher might create assessment or curriculum scenarios.

Who Is Mercor Best For?

Mercor may be a strong fit if you have a background that AI companies need but you are not necessarily looking for a traditional AI engineering role.

You may be a good fit if you are:

• A professional with domain expertise
• A strong writer or editor
• A software engineer or developer
• A data analyst or data scientist
• A doctor, nurse, pharmacist, or healthcare expert
• A lawyer, paralegal, or legal researcher
• A finance, accounting, or investment professional
• A business operations or consulting professional
• A scientist, researcher, or PhD-level specialist
• A designer, artist, audio professional, or creative reviewer
• A bilingual or multilingual language expert
• A humanities expert with strong analytical writing skills
• Someone who enjoys evaluating quality, not just producing content

The key skill is structured judgment.

You do not necessarily need to know how to build AI models. But you do need to read carefully, follow instructions, explain your reasoning, and apply standards consistently.

Domain-Specific Mercor Opportunities

One of the most important things to understand about Mercor is that opportunities can be domain-specific.

This matters because AI companies increasingly need experts who can evaluate specialized outputs. A general reviewer can say whether an answer is clear. A domain expert can say whether it is actually correct.

Below are the domain-specific categories to consider.

Medicine

Best for physicians, nurses, pharmacists, medical researchers, healthcare educators, clinical specialists, and people with strong medical training.

Typical tasks may include reviewing AI-generated medical explanations, checking for accuracy, identifying unsafe advice, evaluating patient-facing clarity, or creating expert examples.

Access the Medicine Opportunities

Law

Best for lawyers, legal researchers, paralegals, compliance professionals, contract specialists, and people with formal legal training.

Typical tasks may include evaluating legal reasoning, reviewing contract-related outputs, identifying missing caveats, or comparing legal explanations.

Access the Law Opportunities

Software Engineering

Best for frontend, backend, full-stack, DevOps, platform, machine learning, and QA engineers.

Typical tasks may include reviewing generated code, debugging, testing outputs, writing coding prompts, evaluating architecture explanations, or identifying technical mistakes.

Access the Software Engineering Opportunities

Data Analysis

Best for data analysts, BI developers, analytics engineers, data scientists, and reporting specialists.

Typical tasks may include reviewing charts, SQL, analysis logic, spreadsheet outputs, statistical reasoning, dashboards, or business insights generated by AI.

Access the Data Analysis Opportunities

Finance

Best for financial analysts, investment professionals, accountants, FP&A professionals, economists, and banking or insurance experts.

Typical tasks may include evaluating financial reasoning, reviewing valuation logic, checking calculations, analyzing model-generated commentary, or assessing risk explanations.

Access the Finance Opportunities

Business Operations

Best for consultants, operators, product managers, project managers, HR professionals, sales operations experts, and founders.

Typical tasks may include evaluating business plans, process documentation, project scenarios, operational recommendations, or management-style analysis.

Access the Business Operations Opportunities

Life, Physical, and Social Science

Best for researchers, lab professionals, academics, psychologists, sociologists, biologists, chemists, physicists, and other science-focused experts.

Typical tasks may include reviewing scientific explanations, evaluating research reasoning, identifying unsupported claims, or creating expert-level examples.

Access the Life, Physical, and Social Science Opportunities

Other Engineering

Best for mechanical, civil, electrical, industrial, chemical, aerospace, and other engineering professionals.

Typical tasks may include reviewing technical explanations, evaluating engineering problem-solving, checking formulas, or assessing applied reasoning.

Access Engineering Opportunities

Arts & Design

Best for designers, artists, creative directors, UX professionals, illustrators, filmmakers, and content creators.

Typical tasks may include evaluating creative outputs, reviewing visual concepts, assessing design critique, or helping train models on creative judgment.

Access the Arts & Design Opportunities

Language and Audio

Best for linguists, translators, editors, voice professionals, audio specialists, localization experts, and bilingual or multilingual contributors.

Typical tasks may include reviewing translations, evaluating tone, assessing transcription quality, rating audio-language outputs, or improving multilingual responses.

Access the Language and Audio Opportunities

Humanities

Best for historians, philosophers, literature experts, educators, writers, cultural studies specialists, and researchers.

Typical tasks may include evaluating reasoning, argument quality, interpretation, writing style, factual accuracy, and nuance.

Access the Humanities Opportunities

How Much Can You Earn With Mercor?

Mercor and other AI training platforms often advertise attractive hourly rates, especially for specialized experts. However, it is important to separate earning potential from guaranteed income.

Income depends on:

• Whether you are accepted
• Whether your domain is in demand
• How many projects are available
• Your assessment performance
• Your task quality
• Your ability to follow project instructions
• Whether projects continue, pause, or end

The best way to think about Mercor is as a potential path to remote expert-based income, not a guaranteed salary. For some people, it may become a meaningful source of recurring work. For others, it may be occasional project income or a way to gain experience in the AI economy.

What Makes Someone Successful on Mercor?

The people who tend to do well in AI training work are not always the people with the fanciest resumes. Often, they are the people who can combine expertise with precision.

Clear Writing

Most AI evaluation work requires written explanations. You need to explain why something is right, wrong, incomplete, misleading, or better than another response.

Vague feedback is not very useful. Specific feedback is.

Weak feedback: “This answer is bad.”

Strong feedback: “This answer is incomplete because it explains the general concept but does not address the user’s specific constraint. It also makes a broad claim without explaining the limitations or assumptions behind the answer.”

Attention to Detail

AI training projects usually include detailed instructions. Missing one small guideline can affect your quality score.

Before starting tasks, read the rubric carefully. Then reread it.

Domain Judgment

If you are applying as an expert, your advantage is not that you can use AI. Your advantage is that you know when AI is wrong.

That means you should lean into your professional standards.

Consistency

AI training work often requires applying the same rubric across many tasks. Consistency matters because the data being created may be used to train or evaluate AI systems at scale.

Humility

A good evaluator does not overstate. If something is uncertain, say it is uncertain. If a response needs more context, say what context is missing. If a task goes beyond your expertise, do not pretend.

How to Apply to Mercor the Right Way

If you want to try Mercor, do not rush the application.

Step 1: Choose Your Strongest Domain

Do not position yourself as “good at everything.”

Pick the area where you have the strongest proof of expertise. That could be your degree, job history, portfolio, certifications, publications, or years of experience.

Step 2: Prepare a Focused Resume

Your resume should make it easy to understand what you know.

Highlight:

• Your domain expertise
• Relevant roles
• Technical skills
• Writing or analytical experience
• Tools you use
• Projects that show judgment
• Any AI-related experience, if applicable

You do not need to pretend you are an AI engineer. In many cases, Mercor is looking for people who understand a domain deeply and can evaluate AI outputs in that domain.

Step 3: Take the Assessment Seriously

The assessment is not something to “get through.” It is where you show how you think.

Read the instructions carefully, answer with structure, and avoid generic comments.

Step 4: Be Specific in Your Answers

When explaining your reasoning, avoid generic phrases.

Instead of saying: “The response is incomplete.”

Say: “The response answers the first part of the prompt but ignores the user’s request for a comparison. It also does not explain the trade-off between speed and accuracy, which is the main decision point in this scenario.”

Step 5: Track Your Work

If you get accepted, keep track of:

• Project type
• Domain
• Pay rate
• Time spent
• Feedback received
• Skills used
• Any patterns in task requirements

This helps you improve and may help you qualify for better projects later.

Is Mercor Legit?

Mercor is a real company in the AI training and expert marketplace space. Its public website describes its work as connecting professionals to AI training projects, and its resources explain categories such as AI trainers, data labeling, reinforcement learning from human feedback, and domain-specific expert evaluation.

Still, “legit” does not mean every applicant will get work, every project will be long-term, or every person will earn a high rate.

You should approach Mercor as a real opportunity, but with realistic expectations.

The Pros of Working With Mercor

Remote Work

Many Mercor-style expert projects are remote, which makes them attractive for people who want flexible project-based work.

Domain-Specific Work

Unlike generic microtask platforms, Mercor’s positioning is more focused on expert judgment. That can make it more attractive for people with professional backgrounds.

AI Economy Experience

Even if you do not want to become an AI engineer, reviewing AI outputs can help you understand how modern AI systems are trained, evaluated, and improved.

Potentially Strong Pay

Expert-level AI training work can pay more than basic data labeling, especially in fields like medicine, law, finance, software engineering, and science. However, rates vary by project, domain, demand, and performance.

The Limitations to Understand

Work Is Not Guaranteed

You may apply and not be accepted. You may be accepted but not immediately matched. You may complete a project and then wait for the next one.

Projects Can Change

Project lengths can vary. Some may be extended, shortened, paused, or concluded depending on customer needs and performance.

Instructions Can Be Detailed

Some people underestimate how much careful reading is required. The work can be flexible, but it is not always easy.

Expert Work Requires Real Expertise

If you apply for a domain-specific project, you should be ready to demonstrate that you actually understand the domain.

Is Mercor a Good Way to Earn Stable Income?

Mercor can be a good way to explore more stable project-based income, especially if you are accepted into ongoing or recurring work. However, it should not be presented as guaranteed stable income for everyone.

A more realistic way to think about it is this:

Mercor may become a stable income stream if you have in-demand expertise, perform well on assessments, receive project matches, deliver consistent work, and continue getting invited to opportunities.

For some people, it may become a meaningful part-time income source. For others, it may be one of several AI training platforms they use. And for some, it may simply be worth trying once to see whether their background matches current demand.

That is still a real opportunity.

The key is to approach it professionally.

Final Thoughts: Mercor Is Worth Exploring, But Approach It Like a Professional

Mercor represents a bigger shift in the future of work.

As AI systems become more capable, the need for human judgment does not disappear. It changes shape. Instead of only doing the work ourselves, more professionals may be asked to define what good work looks like, evaluate AI-generated outputs, and teach models how experts think.

That is the real opportunity.

If you have domain expertise, strong writing skills, and the ability to evaluate work carefully, Mercor may be worth trying. It is not a guaranteed income source, and it is not something to approach casually. But for the right person, it can open the door to remote AI training projects that are flexible, intellectually interesting, and potentially well-paid.

You can start with the general application link below, or choose one of the domain-specific links if you already know where your expertise fits best.

Frequently Asked Questions (FAQ)

What is Mercor?

Mercor is a platform that connects professionals and domain experts with AI training projects. Experts may evaluate AI outputs, compare responses, label data, write examples, and provide feedback that helps improve AI systems.

What does a Mercor expert do?

A Mercor expert may review AI-generated responses, identify errors, compare outputs, write ideal answers, create examples, or evaluate whether a model followed instructions correctly.

Do I need AI experience to work with Mercor?

Not necessarily. Some projects may not require prior AI experience, but many domain-specific projects require relevant education, professional experience, or advanced expertise.

Can Mercor become stable income?

Mercor can become a recurring project-based income stream for some experts, but work is not guaranteed and project availability can change.

How much does Mercor pay?

Pay depends on expertise, project complexity, and demand. AI trainer rates can vary widely, with higher rates usually tied to specialized professional expertise.

What domains does Mercor hire for?

Mercor opportunities can include medicine, law, software engineering, data analysis, finance, business operations, sciences, engineering, arts and design, language and audio, humanities, and other specialized fields.

Is Mercor good for beginners?

It depends on the project. Some AI training work is more general, but domain-specific projects usually require relevant expertise. Beginners should focus on clear writing, instruction-following, and evaluation skills.

Is Mercor remote?

Many Mercor expert opportunities are remote or project-based, depending on the specific assignment and requirements.

The post Mercor Expert Guide: How to Get Paid to Improve AI Outputs appeared first on Data Studio.

As AI systems continue to evolve, the way we interact with them is also changing. What started as “simple prompts” has quickly grown into something much more powerful — structured conversations, agentic workflows, deep research, and even interactive data exploration.

This is where the next generation of technical prompts comes in.

In the updated course, I’m adding new lessons that explore how to leverage features like Agent Mode, advanced research capabilities, and AI-powered data analysis to solve more complex problems and automate workflows more effectively.

Before we dive in, here’s a quick reminder of what technical prompts actually entail.

What Are Technical Prompts?

Technical prompts take prompt engineering a step further. They are designed to help AI systems perform more complex tasks, such as:

• analyzing data
• generating structured reports
• conducting research
• supporting business workflows
• creating structured content

They typically include several components that guide the AI more precisely.

Nano Tips for Leveraging Technical Prompts Using ChatGPT with Lachezar Arabadzhiev

Break down the elements of a prompt from Nano Tips for Leveraging Technical Prompts Using ChatGPT with Lachezar Arabadzhiev by Lachezar Arabadzhiev

The Curriculum

Leverage Technical Prompts in ChatGPT

• Break down the elements of a prompt
• Transform from basic prompts to strategic conversations
• Create analogies for complex technical concepts
• Supercharge your prompts with ChatGPT Apps
• Tackle difficult problems with deep research
• Use Agent Mode in ChatGPT
• Develop interactive data visualizations
• Uncover relationships and insights across large datasets
• Break down big tasks with branching
• Build an agentic workflow with Zapier

If you need a peek into other AI tools, you can always refer to the Generative AI category. I have spend a lot of time experimenting with AI tools in the voice, vision and text field. A few key highlights include:

• AI Video Creation with Runway, Sora & ChatGPT
• How to Use AI to Enhance Your Content Creation Process
• Top Generative AI Tools for Content Strategy

 If you have any questions or comments, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT, Copilot, Google Gemini and Zapier.

The post A Beginner’s Guide to Writing Technical Prompts with ChatGPT appeared first on Data Studio.

This is where Claude comes in.

From analyzing text and executing code to visualizing data and processing voice inputs, Claude helps you streamline tasks, generate ideas, and enhance collaboration without the usual friction.

I hope you enjoy the tips and insights!

Leverage Claude as a virtual collaborator from Nano Tips for Using Anthropic's Claude AI with Lachezar Arabadzhiev by Lachezar Arabadzhiev

The Curriculum

Tips for Using Claude

• Leverage Claude as a virtual collaborator
• Summarize and compare files
• Analyze CSV data and generate insights
• Create a sales funnel data visualization
• Capture and extract insights for screenshots
• Experiment with different writing styles and create your own
• Generate follow-up tasks from meeting transcripts
• Interact with Claude using voice on mobile
• Organize documents and chats with projects
• Create and publish an app with a single prompt

If you need a peek into other AI tools, you can always refer to the Generative AI category. I have spend a lot of time experimenting with AI tools in the voice, vision and text field. A few key highlights include:

• AI Video Creation with Runway, Sora & ChatGPT
• How to Use AI to Enhance Your Content Creation Process
• Top Generative AI Tools for Content Strategy

 If you have any questions or comments, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT, Copilot, Google Gemini and Zapier.

The post Unlocking the Benefits of Claude AI appeared first on Data Studio.

In this installment of my LinkedIn series, I explore the capabilities of AI-powered video generation using tools such as Runway ML and Sora. These platforms offer innovative features that can transform the way we produce video content.​

Exploring these platforms has opened up (at least for me) new possibilities for efficient and creative video production. I’m excited to share these insights and practical strategies to help you enhance your content creation workflows.

Supercharge your video creation with AI from Nano Tips for Creating AI Powered Video Creation with Lachezar Arabadzhiev by Lachezar Arabadzhiev

The Curriculum

Introduction

• Supercharge your video creation with AI
• Engage in real-time video conversations with ChatGPT
• Animate images with Sora
• Remix video content with Sora
• Blend and seamlessly connect videos with Sora
• Generate storyboard videos with Sora
• Perform video-to-video generation in Runway ML
• Create lip-sync videos in Runway ML
• Add and sync subtitles to video with Runway ML
• Inpaint and remove objects in videos with Runway ML

Once you are comfortable with using those AI video generation tools, you can also explore an extension to this course called “The AI-Driven Content Creator”. I hope you find it useful.

 If you have any questions or comments, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT, Copilot, Google Gemini and Zapier.

The post AI Video Creation with Runway, Sora & ChatGPT appeared first on Data Studio.

In this course, you will learn how to conduct AI-powered research, scale and enhance script writing, automate content workflows, enhance editing, and schedule tasks utilizing AI. Plus, explore the latest AI-powered tools that support content creation while understanding the steps and rules to consider to maintain integrity and use AI ethically.

I share a lot of tools and resources in the course, so to ensure you can follow along, I have added all the links in a separate post. This was a fun course to produce and I hope you find it useful.

How AI is transforming content strategy from The AI-Driven Content Creator by Lachezar Arabadzhiev

The Curriculum

Introduction

• How AI is transforming content strategy

AI Tips for Content Strategists

• Research content ideas with Perplexity and ChatGPT
• Create a custom GPT to scale content production
• Automate content workflows with Zapier and AI
• Generate and storyboard videos with Sora
• Edit video content effectively with Descript
• Create and repurpose viral content with Opus Clip
• Create engaging content with Canva Magic Studio
• Edit voiceovers efficiently using ElevenLabs
• Create voice agents with ElevenLabs
• Using AI Ethically and Securely in Content Creation

Helpful Resources

• Top generative AI tools for content strategy
• Essential AI prompts for content creation

 If you have any questions or comments, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT, Copilot, Google Gemini and Zapier.

The post How to Use AI to Enhance Your Content Creation Process appeared first on Data Studio.

Research and idea generation

• Perplexity AI: An AI-powered search engine providing concise, sourced, and context-aware answers
• ChatGPT Deep Research: An advanced feature of ChatGPT enabling in-depth research and analysis with detailed insights

Content creation and repurposing

• Canva Magic Studio: An AI-powered design suite within Canva that assists in creating and enhancing digital content
• Opus Clip: An AI tool that repurposes long-form videos into short, engaging clips optimized for social media
• CapCut: A user-friendly video editing app offering a range of tools and effects for creating polished videos

Audio and video production

• Sora: OpenAI’s AI-powered text-to-video engine that generates realistic and cinematic video content
• Descript: A multimedia editing platform that allows users to edit audio and video by manipulating text transcriptions
• ElevenLabs: An AI-driven voice synthesis and text-to-speech platform for creating realistic voiceovers and conversational agents
• Synthesia: An AI-powered platform for creating videos featuring human-like avatars from text input

Workflow automation

• Zapier: No-code automation platform that connects apps and automates workflows
• Zapier AI Actions: AI-driven features within Zapier that integrate AI models with various apps for seamless workflows

Software engineering and development (vibe coding)

• Lovable: An AI-powered platform that transforms natural language descriptions into fully functional, beautifully designed web applications
• Softr: A no-code platform for building websites, apps, and internal tools using data from Airtable or Google Sheets

Ethical AI use and security

• Ethics of Artificial Intelligence

Interested in Content Strategy and Generative AI?

If you have any content strategy questions, you are more than welcome to:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT and Zapier, or take a look at the Generative AI category on the blog.

The post Top Generative AI Tools for Content Strategy appeared first on Data Studio.

Of course, there are plenty of tools out there that allow for designing webpages via “drag and drop” or using templates (e.g., WordPress, Wix) to create a more interactive application. However, up until this point, there hasn’t been a platform that fully allows non-technical users to build a sophisticated application (API Calling, Database, Authentication, UI etc.) with no code, and just prompts.

Enter Lovable! (I tried it myself and was super impressed)

This guide will walk you through the key steps of building and publishing an app from the ground up with Lovable. I am going to use a demo project, so you can follow along.

By the end of this guide, you will be clear on the procedures to transform your application ideas into a finished product, even with the least amount of technical knowledge required.

Part 1: What is Lovable?

Lovable is a platform that builds fully functional applications by turning text-based prompts into working applications. With application creation possible through a chat interface where requirements are described, an artificial intelligence capability enables application building without prior coding knowledge. This makes app development accessible both to beginning programmers and to seasoned developers looking for rapid prototyping solutions.

It builds applications fundamentally within the frameworks of React and Vite for a responsive frontend. On the backend, the integration works with Supabase, an open-source Firebase alternative, for database storage, authentication, and cloud functions. Lovable supports GitHub integration for version control and collaborative development by the users.

Part 2: Step-by-Step Guide to Building Your First Project with Lovable

1. Getting Started with Lovable

To get started, you need to sign up on Lovable for a free account on its official portal. After signing up, users are provided with an AI-powered interface through which they can instantly start building their projects. With the free version, you get 5 prompts daily.

Next, you have to put in the first prompt, so describe the app idea with the simplest of words. This prompt becomes the very basis of the project that gives the AI some footing to generate an initial structure.

Based on your description, Lovable produces a simple app with a modern UI design and basic functionality. From here, you can play around with the generated designs, try out what works and what does not, and make further refinements until it all matches your vision.

2. Writing your first Lovable prompt

Let’s see how this works with an example.

To display Lovable’s features, let’s try to build a simple budget tracking application. The following prompt is what we will use to get started.

“I want a mobile budget tracker app: Add Income/Expenses, Categorize Transactions, and show the summary view of the financial activity of users.”

Lovable will generate a working version of the app that has simple CRUD (Create, Read, Update, Delete) functionalities. Users will be able to log their transactions, categorize them (food, rent, entertainment), and see running balances of what is available to them.

For now, the app will store data in local storage so that the user can keep the financial record variables intact even after refreshing the page. Local storage being device-dependent would somewhat hamper users from accessing their budgets from different devices.

So, it is important to integrate a database, in your case, Supabase.

3. Upgrading to a Cloud Database with Supabase

Lovable’s native integration with Supabase allows you to manage both your front-end UI and back-end database through a single, user-friendly chat interface. This means you can design your app’s screens and set up a cloud PostgreSQL database all within Lovable, without having to leave the platform.

Steps to Connect Supabase

• Click the “Supabase” button in the Lovable interface.

• Sign up for a Supabase account or log in if you already have one.

• Create a new organization in Supabase and authorize Lovable to access it.

• Click “Create Project” to generate a database.

• Return to Lovable and connect your app to the Supabase project.

4. Adding User Authentication

For improved access control and privacy, let’s add user authentication to our budget tracker app. Built-in authentication from Supabase would allow a very simple prompt for adding login and signup functionality.

“Add user authentication so that every user has their own private mobile budget tracker app.”

Once prompted, Lovable will automatically:

• Set up authentication tables in Supabase for user account management.
• Add login and signup screens to the app’s user interface.
• Secure database access such that each user can view-only and manage their financial information.

5. Publishing your Lovable App

After your app is complete, the next step is to publish it online, thereby making it available to users. The process has been made easy by Lovable, which can be done in just a few clicks. When you click the Publish button, you initiate the deployment process, allowing the AI to take care of the technicalities of hosting and launching your app.

The moment you click publish, Lovable’s AI quietly manages deployment in the background. This may take some time while the platform configures your app for public access.

Once the deployment is successful, Lovable gives you a special link to your app. You can provide that link to anyone, so they can experience the app in real-time.

If you update or add features later, just hit Update and the latest version will be available immediately.

6. Adding a Custom Domain

By default, your application is accessible via staging subdomain (e.g., yoursite.lovable.app). However, you can connect your site to a custom domain (e.g., yourdomain.com) or a subdomain (e.g., subdomain.yourdomain.com) that you own. This is fairly easy to setup.

You can navigate to Project, then Domains and then click, Add another domain. From there, just follow the steps, and you will be verified in no time. For more information on specific domain setups, you can access the Lovable documentation.

Part 3: What other features does Lovable have?

As mentioned previously, Lovable is not just a “landing page” generator, but rather a full-stack platform, which can take care of almost all software development aspects.

1. GitHub Integration for Manual Code Edits

Lovable allows users to connect a project with GitHub for manual editing. Through this, developers will be able to edit the code in the traditional way to enhance or build their app beyond Lovable’s interface.

How to Connect Lovable to GitHub

1. Create a GitHub account if you don’t have one.
2. Click on the “GitHub” in Lovable.
3. Then, select “Transfer project to GitHub” and choose an organization/repository.

4. Once linked, you can manually modify the code using Visual Studio Code or another IDE (eg. GitHub Codespaces).

How to Edit Code in Lovable with Dev Mode

Originally, editing your code required connecting your Lovable project to GitHub, but Dev Mode provides an alternative. You can now edit your project’s code directly in Lovable, providing you more control as a developer.

You can now enable code editing in Account > Settings > Labs.

2. Monetizing Apps with Stripe Integration

Integrating a revenue stream into your app is easy with the Stripe integration in Lovable. You can add paid plans with a command such as:

“Add Stripe payments so users must subscribe to create more than 10 budgets.”

You must first put in the Stripe API key after being asked if you wish to set up payments through Stripe.

• Next, put together a pricing plan in Stripe and copy the Price ID assigned to it.
• Then, paste this Price ID into Lovable’s chat to finalize the integration.

​Lastly, integrating Stripe with Lovable can enable you to monetize your application by offering subscription or single payment access to premium features.

To implement this, you can either limit certain features for free users or offer exclusive content to subscribers. By integrating Stripe, you can efficiently manage subscriptions and payments, thereby generating revenue while enhancing user satisfaction. In the example above, we have done that with a tool called the LMS Advisor.

3. Implementing Cloud Functions (with Supabase)

Cloud functions offer you automation for backend tasks such as sending email reminders for uncompleted tasks. You can use it by instructing Lovable as follows:

“Include a cloud function calling for emailing reminders to make budgets at the end of the month”

Lovable would thereby create a serverless function to run on a schedule for the sending of reminders. The sending would be done through an integration with a third-party email API, such as Resend or SendGrid, to take care of email delivery. When asked to do so, just add the API key and the service becomes active. This will allow users to receive timely notifications without any manual intervention. It can be extremely helpful in applications that need updates often.

Reminder! In Lovable, cloud functions are implemented through Supabase Edge Functions – serverless TypeScript functions that run on Supabase’s infrastructure, distributed globally close to your users.

4. Converting Your App into a Progressive Web App (PWA)

By default, applications created with Lovable run in standard web applications. However, there are ways to make the user experience better, like installable applications for mobile devices. Just ask Lovable:

“Convert this app into a Progressive Web App (PWA) so that the users can install it on their phones.”

Once the actual installation is complete, whenever the users open the app in a mobile browser, they will see an “Install App” prompt, so they can have the app on their home screen. It brings accessibility closer as well as the native app-like experience, including faster loading times and offline availability.

5. Adding Images to Your Lovable Project

Adding images also refine your project visually and engages users. Lovable helps you bring up images through uploading directly, external imaging sites, and even GitHub storage.

1. Directly Upload Images

The easiest way to add images is the drag and drop them into the chat window or select a file from your device. Lovable is going to analyze and connect that image to your project. In fact, users can mention how to use an image in the prompt; whether as background or header or in a specific section. These prompts can be useful for speedy prototyping since Lovable controls placement.

2. Using Supabase for File Storage (Images & Media)

When your Lovable app needs to handle file uploads, such as user profile pictures, attachments, or other media, Supabase integration is the perfect solution. Supabase offers a Storage service that allows you to conveniently host files—like images, videos, PDFs, and more—alongside your database.

By adding an Upload component or an image upload feature in your Lovable app, the app will utilize Supabase Storage behind the scenes. Uploaded files will be stored in a storage bucket within your Supabase project, and you will receive a URL or reference to display or download the files later.

3. Adding Images to GitHub

This would be the best way to manage your assets as you would want to store your images in a public GitHub repository and reference them into your project. You should first link your project to GitHub.

Then you can upload your images to the public directory, commit the changes, and copy the image path (public/my-image.jpg). Finally, this path can be used in your Lovable prompt, such as: Set the hero section background to public/my-image.jpg. This method will allow full control of the assets and sync.

6. Using Custom (Google) Fonts

Fonts give a very characterful identity to an application. There is no direct mechanism for uploading a font in Lovable, but significantly, you can still use it for your design in conjunction with web-safe fonts and Google Fonts.

1. Websafe Fonts

Web-safe fonts have been installed on almost any operating system, thus ensuring their consistency across devices. They load very quickly, thus enhancing performance. Some of the more commonly used fonts include Arial, Times New Roman, Georgia, Courier New, Verdana, Tahoma, and Trebuchet MS. You can apply any of them in Lovable, for instance, use a prompt like:

“Use Courier New for all headings on the landing page.”

2. Google Fonts

Google Fonts is a repository for free fonts where very creative fonts hide. There are two possible input methods:

• By Name: Use ‘Playfair Display’ for section titles. Use prompts like:

“Use ‘Playfair Display’ as the primary font for section titles.”

• By Link: Copy the link from Google Fonts to reference it, e.g., Apply this Google Font: Dancing Script to all subheadings.

Conclusion

Ultimately, Lovable offers a comfortable and easily manageable platform where anyone can create applications without any knowledge of coding. This makes it especially great for people who are not developers and just want to build a prototype quickly.

Those developers used to working with specific tools and workflows may find it less efficient, but above all, Lovable provides an easy entry point into the coding world.

 If you have any questions, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT, Gemini, Claude and Zapier, or take a look at the Generative AI category.

The post The Ultimate Guide to Building Apps with AI Prompts in Lovable appeared first on Data Studio.

In my most recent course called “Nano Tips for Using Google Gemini” I have gone through a few productivity hacks. You will learn how to summarize and compare files in Google Drive, generate text and reference files in Google Docs, create tables and formulas in Google Sheets, and use Gmail to write professional emails in seconds. This was a fun one to do and I enjoyed the production process.

Here is a short snippet and remember that all of my nano courses are FREE on LinkedIn Learning:

What is Gemini? from Nano Tips for Using Google Gemini with Lachezar Arabadzhiev by Lachezar Arabadzhiev

The Curriculum

Boosting Business Productivity with Google Gemini

• What is Gemini?
• Summarize and compare files in Google Drive
• Generate text and reference files in Google Docs
• Create tables and formulas in Google Sheets
• Write professional emails in seconds in Gmail
• Simplify email summaries and responses in Gmail
• Create images and slides in Google Slides
• Use the standalone Gemini website on desktop
• Experiment with contextual browsing on YouTube
• Use Gemini Gems for custom help

Also, if you get the chance and want to play around with the tool a bit more, you can download the app here.

 If you have any questions, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT and Zapier, or take a look at the more introductory ChatGPT articles on the blog.

The post How to Boosting Business Productivity with Google Gemini appeared first on Data Studio.

In this one, I share a few tips on how to leverage the latest features of Copilot to streamline everyday work tasks across the entire Microsoft 365 suite. You will learn how to reference files and visualize text in Microsoft Word, analyze data in Excel, and summarize and draft emails in Outlook, using Copilot as your personal writing coach.

If you are new to Copilot, this is the intro video in my course. You can watch it before diving into the rest of the tips.

What is Microsoft 365 Copilot? from Nano Tips to Streamline Work Tasks Using Microsoft Copilot with Lachezar Arabadzhiev by Lachezar Arabadzhiev

The Curriculum

Streamline Work with Microsoft Copilot

• What is Microsoft 365 Copilot?
• Reference files and visualize text in Microsoft Word
• Analyze data in Excel with Copilot
• Summarize and draft emails in Microsoft Outlook
• Get email coaching with Copilot
• Create slides with a prompt in Microsoft PowerPoint
• Extract actionable insights from a PowerPoint presentation
• Use Copilot Vision on Mobile
• Use Copilot Audio on Mobile
• Experiment with the Copilot Lab

Copilot’s biggest advantage is its seamless integration into the Microsoft 365 suite of products. At first, I thought that was no big deal, but trust me Copilot comes in handy, especially when working in Outlook and Excel.

 If you have any questions or comments, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT, Copilot, Google Gemini and Zapier.

 Subscribe to receive the by-weekly “My Next Story Is…” newsletter. Yep, it is my brand new newsletter!

The post Streamline Everyday Work Tasks with Microsoft Copilot appeared first on Data Studio.

Here is a short snippet and remember that all of my nano courses are FREE on LinkedIn Learning:

Supercharge GPTs with Zapier AI Actions from Nano Tips for Building AI Actions for GPTs with Zapier and ChatGPT with Lachezar Arabadzhiev by Lachezar Arabadzhiev

The Curriculum

Building AI Actions for GPTs with Zapier and ChatGPT

• Supercharge GPTs with Zapier AI Actions
• Activate Zapier AI Actions for GPTs
• View: Data Insights and Analytics GPT
• Build: Data Insights and Analytics GPT
• View: Creative Image Organizer GPT
• Build: Creative Image Organizer GPT
• View: Business Receipt Manager GPT
• Build: Business Receipt Manager GPT
• View: Agenda and Event Maker GPT
• Build: Agenda and Event Maker GPT

Once you are comfortable with building custom GPTs and configuring AI Actions, take a look at the latest OpenAI Cookbook, an awesome resource for GPT Action libraries, API releases and more.

 If you have any questions, feel free to do one of the following:

 Follow me on LinkedIn, and click the at the top of my profile page to stay up to date with my latest content!

Explore my nano LinkedIn Learning courses covering AI tips with ChatGPT and Zapier, or take a look at the more introductory ChatGPT articles on the blog.

The post How to build AI Actions for GPTs with Zapier and ChatGPT appeared first on Data Studio.