How AI Helped Me Build a Product, Shape a Business Idea, and Write Its Own Code

How AI Helped Me Build a Product, Shape a Business Idea, and Write Its Own Code Two years ago, I was running a consulting firm in Luxembourg. After selling my previous telecom company following the tragic loss of both my co-founders — one to COVID, the other to cancer — I found myself managing consultants while trying to rebuild something meaningful. I never expected LinkedIn would become part of that journey. Running a B2B consulting company in 2022 meant one thing: you had to maintain a presence on LinkedIn. Weekly posts. Thought leadership. Showing activity. Sounding smart. All while managing operations and clients. I couldn't keep up. Worse: I didn't want to. It felt like a second job on top of my actual job. So I started looking for shortcuts. Initially, I just scraped article summaries and formatted posts with Make.com. Then I began incorporating analytics, running content through OpenAI to summarize blogs, create hooks, and adjust tone. But it was clunky. Just a patchwork of automation. No interface. All duct tape and digital string. That's when it hit me. If I could automate LinkedIn for myself, maybe others needed this too. Not with generic templates or obviously AI-generated content. I wanted to build something that could: Analyze a company's website or product documentation Capture the brand's authentic voice Create consistent content across multiple platforms Generate complete visuals (banners, logos, CTAs) without Canva hacks Let users preview posts or publish automatically All in one place, no technical expertise required That's how Linkeme.ai was born. I rebuilt everything using Bolt.new for the interface and Make.com for backend automation. Under the hood, we integrated: GPT-4.1 and Claude for content and semantic understanding Internal ranking systems to select the best posts A CTA engine adjusting text length and tone for each platform An LLM-based visual system automatically creating branded illustrations Publishing capabilities for LinkedIn, Twitter, Facebook, and Instagram requiring zero human intervention That was version 1 — when I realized this wasn't just automation, it was a genuine product. The workflows were still cobbled together, but they worked. And people were willing to pay for it. Then came version 2. Today, Linkeme runs entirely on AWS. We've migrated to a serverless architecture using Lambda and Step Functions to handle scaling. The logic now runs through Cline (our internal dev tool using LLM agents in VS Code), with workflows modeled as AI-defined services. We've replaced most of Make.com's business logic and now operate a system processing thousands of posts daily, with complete retry capabilities and audit trails. It wasn't just built with AI. It was built by AI. From conceptualizing the product to prototyping to writing the first infrastructure code — the LLMs weren't assistants. They were partners. That's what amazes me most. AI didn't just generate content for Linkeme. It helped envision the product. It helped build the pipelines. It helped design the workflows. And now, it runs the entire system end-to-end. This wasn't "AI as a feature." This was AI driving the entire development cycle. And the craziest part? It all started because I couldn't find time to write LinkedIn posts.