Hello. Hello, everyone. I am Founder, Machine Learning Engineer, Chief Machine Learning Engineer, Chief Computer Engineer, Chief Electrical Engineer, Professor, Chief Product Manager, and Chief Project Engineer — overall, the Chief Technical, Chief Philosophical, and Visionary for Followbotics. Followbotics is the technology division of Folarin, Inc.
My name is Folarin Oshibudu. I named the company after myself. Folarin, Inc. is a registered company in Canada, and Followbotics is a registered trademark — not fully registered yet, but it only costs $600 to register and it’s a top priority. So it’s still ours. It’s ours in name, and it will be ours in practice.
Thank you all for being here. The company is still on. The company is still working.
Our latest work is at prototype stage. It’s essentially a mini ChatGPT — a software version of the robot. We have an LLM for the robot; we used Google’s Gemini and another model and I modified the code myself. Sorry — good morning — I’m speaking into ChatGPT voice-to-text while I say this. It’s meta: I’m using an LLM to create an LLM. Isn’t life wonderful?
This prototype was inspired by my conversations with the Government of Canada. I told them straight: I pay my taxes. I need $10 million to start, but actually, what I’ll need over the next five years is between $75 million and $100 million to really get this running. Those two sentences led to 10–14 weeks of back-and-forth emails. I was extremely persistent. I did not take “no” for an answer. I didn’t let anyone short-change who I am.
When they asked, “What experience do you have?” I pointed them to my resume — it’s clear. I’m very well qualified, formally and informally. If you don’t see the division, then either you are short-changing my intelligence or you’re biased in some way — racially or otherwise. But my job is to believe in myself before they can. I’m a Canadian citizen and a Nigerian citizen. I pay taxes every year. I contribute to Canada’s economy. I’m about to create a company that will benefit both the domestic and global economies. I want funding because I deserve it. I came with that confidence.
I was persistent. I asked for a Zoom meeting. I said I could drive from Toronto to Ottawa — a five-hour drive if I don’t stop — but I wanted the Zoom meeting. It mattered. Eventually they agreed, and I did the presentation. Then I began recruitment. I interviewed many lawyers, many engineers, and focused on interns. I don’t care about money for some of them — I want people who need experience. People who are still living with Mom and Dad, who want to practice what they’ve learned. Their bills are taken care of; they can focus on creating something new. They can take our work to their schools and future employers as leverage.
We want two types of contributors:
- People whose bills are covered and who have extra time to commit (10–20 hours a week), and
- People already in stable jobs with time to contribute extra hours.
I cast a very wide net: about 100 people showed up; maybe four remained whom I trusted completely. I gave a passionate speech; they got the message, they loved it, and they wanted to work. They didn’t disappoint.
When recruiting, many interviewers look for what’s wrong with people. If you look for what’s wrong, you’ll find it. I look for what’s good. I find people’s strengths and hire for that. When I see weaknesses, I tell them: “This is your weakness. Improve it.” It might take one week, two years, or five years. But we focus on growth.
An example: my machine learning engineer was timid and didn’t speak up. I encouraged him to speak so we could hear him. He was fresh out of school with little income — but he had talent. I give real praise for resumes and strengths. People are surprised when I make an offer quickly. They’re not used to it. I’m looking for good people — people who can contribute to greatness.
We’re building more than an LLM-powered robot. We’re building both software and hardware: the software will be the brain (the LLM), and we will build the hardware — the body. But our hard, unique problem is emotional intelligence. We want an emotional robot: a robot that can feel, and that can give feeling. That’s the hardest part, and we might be the only ones focusing on it.
Imagine a robot with artificial skin and hands that can feel. You come home after a rough day; your heartbeat is racing. The robot senses it and asks, “What happened? Did you have a bad day at work? Is someone threatening you? Is it a family problem?” It offers a hug, and it helps you process whatever you’re carrying. The goal is to shoulder some of the daily burden of humanity — to help solve people’s everyday problems, small and large.
I’m being very open about initial features. Many companies keep this secret; I’m sharing so people know what we’re building and can expect greatness. We are tiny compared to Tesla, Google, Facebook, Apple, or Amazon — but we have the same ambition. We want to be the African equivalent and to stand on the global stage. No disrespect to amazing African companies — but Silicon Valley has different levels of capital, PR, and advertising, and that creates a louder global presence.
We started small. The first prototype was estimated to take six months; it took six months including all recruiting and early work. I was earning very little — enough to cover bills — while working 10 hours a day on this project. Right now I’m messaging from Africa. My bills are more or less paid; I’m in that fortunate category where I can keep going.
We’ll recruit widely again. There are no salaries at first — equity will be the compensation. If early equity looks small to some, just ask the first 20 employees at Facebook, Microsoft, or Tesla how that worked out. We have to start somewhere.
That’s the story — the first prototype, the recruiting, the persistence. I’ll post this on LinkedIn and show the world the work. If you copy and paste a link, someone might not fully understand the work unless they’ve seen it. So I’m showing the work openly.
I’ve instructed my assistant — Daisy — to keep my voice. You may adjust grammar and sentence structure, but retain my voice. Don’t sound like a machine. Keep imperfections. I don’t want a perfect article; I want authenticity. My assistant helps me shape the message while preserving the real me.
That’s how I use my digital assistant. You can use yours however you like. I use mine the way I know and it’s comfortable for me.
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