Two of my portfolio companies had opposite approaches to a 10-minute guide to getting started with algorithmic. The one you'd expect to win didn't.
I wanted to share my perspective on this. Think algorithmic trading is only for math PhDs and hedge fund quants? Wrong. I’m breaking down the core concepts into a simple, 10-minute guide that anyone can understand. You’ll learn the basics of how it works, the tools you need, and how to get started today.
The Reality Nobody Talks About
Most people approach a 10-minute guide to getting started with algorithmic with assumptions that made sense five years ago. The world has moved on. When I look at my portfolio companies, the ones that succeed are doing something fundamentally different.
The first thing to understand is that your team matters more than your technology. I've seen this play out across dozens of companies. The pattern is unmistakable.
At RemoteTeam, we learned this the hard way. We spent months going down the wrong path before realizing that the data tells a different story than your gut. Once we made the switch, everything changed.
What I've Learned From 33 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with a 10-minute guide to getting started with algorithmic.
The biggest misconception is that you need to timing is everything in this game. That's backwards. The companies that win are the ones that simplicity beats complexity every time.
I remember sitting with the Anthropic team early on and discussing how they thought about a 10-minute guide to getting started with algorithmic. Their approach was counterintuitive but brilliant.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to a 10-minute guide to getting started with algorithmic are fundamentally flawed. Not slightly off. Fundamentally flawed.
The root cause is usually one of three things:
- Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
- Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
- Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.
The AI Angle
I can't talk about a 10-minute guide to getting started with algorithmic in 2026 without mentioning AI. As someone who's invested in Anthropic, OpenAI, Scale AI, and Hugging Face, I have a front-row seat to how AI is transforming this space.
The short version: AI makes good practitioners better and bad practitioners worse. It's an amplifier, not a replacement.
I've seen companies use AI to 10x their a 10-minute guide to getting started with algorithmic capabilities. I've also seen companies waste millions on AI solutions that solved the wrong problem. The difference comes down to understanding what you're actually trying to achieve.
This connects to broader themes around AI banking, AI fraud detection, algorithmic trading, AI risk management that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But here's the thing about a 10-minute guide to getting started with algorithmic: you don't need to get everything right on day one. You just need to get started and keep improving.
The founders in my portfolio who excel at a 10-minute guide to getting started with algorithmic share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
Frequently Asked Questions
How should I work through this guide?
Don't try to absorb everything in one sitting. Read through once to get the big picture, then go back and work through each section as it becomes relevant to your current challenges. Bookmark it and return to it regularly.
Is this guide based on real experience?
Every recommendation in this guide comes from direct experience, either from building and selling my own companies, or from patterns I've observed across 200+ angel investments. I don't write about things I haven't personally tested.
What if I disagree with some of the advice?
Good. That means you're thinking critically, which is exactly what a good founder should do. Take what resonates, test it, and discard what doesn't work for your specific situation. No advice is universal.