After 200+ angel investments, I've seen the same i tried 10 different ai trading bots. here's what i found. mistake destroy companies over and over.
I put 10 of the most popular AI trading bots to the test with my own money. The results were… interesting. I’m sharing my unfiltered review of each bot, including my profits and losses, to help you decide which, if any, are right for you. This is the ultimate bot showdown.
The Counterintuitive Truth
Here's what surprised me most about i tried 10 different ai trading bots. here's what i found.: the best practitioners do less, not more.
When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.
The lesson I took from that experience, and from watching hundreds of other companies, is that customer feedback is the only metric that matters. It sounds simple. It's incredibly hard to execute.
The Reality Nobody Talks About
Most people approach i tried 10 different ai trading bots. here's what i found. 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 the market doesn't care about your roadmap. 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 timing is everything in this game. Once we made the switch, everything changed.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to i tried 10 different ai trading bots. here's what i found. 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.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to i tried 10 different ai trading bots. here's what i found..
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on i tried 10 different ai trading bots. here's what i found.. I've seen plenty fail because they moved too slow.
Second, measure everything. If you can't measure it, you can't improve it. Set up tracking from day one, even if it's basic.
Third, talk to your users. This sounds obvious but you'd be amazed how many founders build their i tried 10 different ai trading bots. here's what i found. strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around AI trading, algorithmic trading, fintech AI that I've been thinking about a lot lately.
Final Thoughts
After two exits, 200+ investments, and more mistakes than I can count, here's what I know for sure about i tried 10 different ai trading bots. here's what i found.: there are no shortcuts, but there are smarter paths.
The smartest founders I work with treat i tried 10 different ai trading bots. here's what i found. as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with i tried 10 different ai trading bots. here's what i found., don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.