How to Build a LinkedIn Post Generator with Lovable in One Weekend

One of the most consistent challenges founders tell us about isn't product strategy or fundraising. It's content.

Specifically: LinkedIn. Everyone knows consistent LinkedIn posting builds audience, credibility, and inbound. Everyone also knows that sitting down three times a week to write something original — when you're also building a product, managing a team, and talking to customers — is genuinely hard.

So we built a tool to make it easier. Here's exactly what we built, how we built it in Lovable, and what the process taught us about using AI tools to solve real problems.

The short version of how the tool works is in this clip:

The Problem We Were Actually Solving

Before building anything, we were specific about the problem. It wasn't "LinkedIn posting is hard." That's too vague to build against.

The actual problem: founders know what they want to talk about but struggle to turn a raw idea into a structured, shareable post. They have the thought. They don't have the hook, the structure, the call to action, or the confidence that it's worth posting.

A generator that takes "I want to talk about why non-technical founders should validate before building" and turns it into a fully formatted LinkedIn post with a hook, three insight paragraphs, and a CTA — that solves a specific problem.

That specificity shaped everything about what we built.

What We Built

The tool is simple by design:

1. You describe your topic or paste in a raw idea — a sentence, a few bullet points, a rough thought
2. You select a tone — professional, conversational, or thought leadership
3. The tool generates a formatted LinkedIn post — with hook, body, and CTA
4. You copy, edit slightly, and post

No login wall in the prototype. No scheduling. No analytics. Just the core workflow — idea in, post out.

How We Built It in Lovable

Prompting the core UI

The first Lovable prompt described the exact interface: a text input for the topic, a dropdown for tone selection, a generate button, and an output area with a copy button. We described what each element does and how they connect.

Lovable built a functional version in one session. Not perfect — the styling needed tweaks, the copy button initially didn't work correctly — but the core flow was there.

Wiring in the AI

The content generation uses the OpenAI API. To set this up in Lovable:

1. Add your OpenAI API key to the Supabase environment secrets (Lovable uses Supabase as the backend)
2. Create an edge function in Supabase that takes the user's topic and tone, calls the OpenAI API with a carefully crafted system prompt, and returns the generated post
3. Connect the Lovable frontend to call that edge function when the user hits "Generate"

The system prompt is the most important part. Ours tells the AI: you are a LinkedIn ghostwriter for [audience]. Write posts with a strong hook in the first line, use short paragraphs for mobile readability, include a specific actionable insight, and end with a question to drive comments. Adjust the tone based on [tone selection].

A well-crafted system prompt is the difference between generic AI content and output that actually sounds usable.

Iterating on the output

The first outputs were too generic. We refined the system prompt to include:

• Instructions to reference the founder's specific background
• A rule to start with a counterintuitive statement or specific number
• Examples of strong vs. weak hooks to learn from

Three rounds of prompt iteration took the output from "AI-sounding but usable" to "needs a small edit but genuinely good."

The Full Build Session

We documented the entire process — building the tool, refining the AI prompts, testing with real content, and launching it as 10xBuddy (our LinkedIn AI SaaS for professionals). The full session is here:

What This Taught Us About Building Tools for Yourself

The best tools to build with Lovable are the ones you'll actually use yourself. When you're the user, you know immediately when the output is good and when it isn't. You don't need to run a user research session — you know the friction points because you feel them.

The LinkedIn generator is useful because we built it around our specific problem: knowing what to say but not having the time or energy to structure it. A founder who has a different content problem — e.g., not knowing what topics to write about — would need a different tool.

The lesson: before prompting Lovable, spend 20 minutes writing down the exact moment of friction you want to solve. The more specific your problem statement, the more focused your build, and the more likely your output actually solves something.

Using Your Own Tool as a Product Idea

Building a tool for yourself has a secondary benefit: it's a natural first step toward a product others might pay for.

If you build a LinkedIn post generator that you use every week, you already know:

• The core workflow (because you designed it around your real need)
• The main frustrations (because you've experienced them)
• What good output looks like (because you've used it enough to have a standard)

That's more validated product knowledge than most founders have when they start building for an external audience.

The Bigger Point

This post isn't really about LinkedIn posts. It's about a way of working: identify a specific, real friction you have, build the minimal tool that removes it, use it yourself, and learn from that experience before deciding whether to take it to market.

Lovable makes that loop fast. An idea on Monday can be a working tool by Friday. That changes the economics of exploring what's worth building — and it's exactly how we approach early-stage product development with the founders we work with.

If you've built something in Lovable and want to take it to a real product — with proper auth, a production backend, and the ability to handle real users — that's what we do. Book a free call →