I almost gave up on 8 things i learned scaling revenue with ai entirely. Then something clicked that changed my whole approach.
When I first tried scaling our sales team, I failed miserably. It wasn't until we implemented deal scoring that everything clicked. Here's the exact framework we used to 3x our pipeline without adding headcount.
What I've Learned From 85 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with 8 things i learned scaling revenue with ai.
The biggest misconception is that you need to you need to move fast and break things. That's backwards. The companies that win are the ones that most founders overthink this and underspend on execution.
I remember sitting with the Anthropic team early on and discussing how they thought about 8 things i learned scaling revenue with ai. Their approach was counterintuitive but brilliant.
The Counterintuitive Truth
Here's what surprised me most about 8 things i learned scaling revenue with ai: 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 8 things i learned scaling revenue with ai 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 you need to move fast and break things. 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 customer feedback is the only metric that matters. Once we made the switch, everything changed.
The Numbers Don't Lie
I've tracked the performance of companies in my portfolio that take 8 things i learned scaling revenue with ai seriously versus those that don't. The difference is stark.
Companies that invest early in 8 things i learned scaling revenue with ai see, on average, 2-3x better outcomes within 18 months. That's not a small edge. That's the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around conversational sales AI, AI CRM, AI sales tools, sales forecasting AI 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 8 things i learned scaling revenue with ai: 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 8 things i learned scaling revenue with ai 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 were these items selected?
Each item on this list comes from direct experience, either from building my own companies or from patterns I've observed across the 200+ startups I've invested in. I prioritize practical, actionable items over theoretical concepts.
How do I know which items apply to my situation?
Start by honestly assessing where your biggest bottleneck is right now. The items that address that specific constraint will give you the highest return on your time and energy.
Which item on this list has the highest impact?
It depends on your stage and context, but in my experience, the items near the top of the list tend to have the broadest applicability. That said, sometimes the less obvious items create the biggest breakthroughs for specific situations.