The first version of this system failed hard. My audience conversations lived in scattered WhatsApp threads I could never find again. Content ideas vanished. Personal touches got lost in the noise. I was trying to run a one-woman AI product business from Panama while speaking three languages and the whole thing felt disconnected.
That mess is exactly why I started paying attention to how the pieces could finally talk to each other. What follows is not a polished case study. It is the current messy reality of my solo founder marketing stack that actually started working this week.
AIdeazz is not really a podcast. It is my public build log. The place where I document the chaotic process of building real AI products as a solo founder living in Panama. The name plays on "AI ideas" with my Russian twist. It shows other technical founders that you do not need a big team or perfect conditions. You start and keep shipping.
The real problem I have been wrestling with is turning that documentation into a marketing and distribution engine that does not drain me. The answer showed up in a tool I already used every day.
I began treating WhatsApp as my primary fan connection layer. It feels personal. Messages arrive instantly. People actually open them unlike tweets or LinkedIn posts that disappear. I now send a growing group of builders experiments, early thoughts, and voice notes about whatever I am playing with. Because it stays lightweight I actually enjoy the process.
But enjoyment alone does not scale. I needed a way to remember who these people are what they told me and what they care about. So I built a tiny system that funnels those conversations into a local SQLite database I call fan SQLite. Nothing fancy. Just a simple database living on my laptop. Every message share or request for advice gets captured in a way that respects the humans on the other end.
This is where CrewAI became useful. I use it to spin up small autonomous teams of agents for specific jobs. One agent reads new messages. Another summarizes key insights. A third looks for patterns across everything. What are people struggling with? What questions keep coming up? Which topics actually excite them? The crew turns raw conversation into structured knowledge instead of another forgotten chat log.
Gemini sits on top as the intelligent layer. It takes the SQLite data plus CrewAI outputs and produces insights content ideas personalized sequences and even draft messages. It behaves like a strategist who has read every single conversation I have ever had with my audience. That intelligence then flows into HubSpot where the more traditional marketing lives: sequences email campaigns and segmentation.
The difference is these are no longer based on guesses. They come from real WhatsApp conversations processed by AI agents and synthesized by Gemini.
This morning I finally mapped the whole flow on paper: WhatsApp into SQLite into CrewAI into Gemini into HubSpot. For the first time it felt like an actual system not random tools. A flywheel.
This is what building in public on the go looks like for me. I am literally in Panama drinking coffee connecting with people on WhatsApp letting small AI crews do the heavy lifting and slowly turning human relationships into a smart marketing layer that scales with me.
The stack is far from perfect. The SQLite remains basic. CrewAI agents sometimes go off the rails and need tighter prompts. The handoff from Gemini to HubSpot is still partly manual. Yet it already delivers better audience signals than anything I have tried before.
Six months from now this entire setup will probably look completely different. That is why I recorded the voice note while it was fresh. I wanted a marker for the exact moment it clicked.
If you are a technical founder stitching together your own little AI-powered engine I hope this messy walkthrough gives you ideas or at least makes the beautiful mess feel less lonely.
FAQ
How do you avoid creeping out your audience with the fan SQLite database?
I only capture context they voluntarily share in direct conversation with me. The goal is to remember details so I can be more helpful not to build surveillance. Transparency and respect come first.
What happens when CrewAI agents go off the rails?
They do it regularly. The current fix is better prompts and tighter job definitions. Each iteration teaches me what these small autonomous teams actually need to stay on task.
Do you plan to replace HubSpot with something more AI-native?
Not yet. HubSpot still handles execution well. The intelligence layer lives in Gemini and the agents. The current handoff is manual but the signals coming in are already richer than before.