When I first started working with your 'data-driven' culture is a joke (and ai won't fix it)., I thought I had it figured out. I was dead wrong.
You don't need a team of PhDs from Google to succeed with AI. In fact, they might be the problem. I'll tell you the one role you actually need to hire for, and it's not what you think.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to your 'data-driven' culture is a joke (and ai won't fix it). 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 Framework That Actually Works
I'm going to share the exact framework I use when evaluating your 'data-driven' culture is a joke (and ai won't fix it).. It's not complicated, but it requires discipline.
Step 1: the best solutions are often the simplest ones This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: you need to move fast and break things Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly Nothing works perfectly the first time. The companies in my portfolio that nail your 'data-driven' culture is a joke (and ai won't fix it). are the ones that treat it as an ongoing process, not a one-time project.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to your 'data-driven' culture is a joke (and ai won't fix it)..
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on your 'data-driven' culture is a joke (and ai won't fix it).. 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 your 'data-driven' culture is a joke (and ai won't fix it). strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around enterprise AI, AI consulting, AI strategy, corporate AI adoption 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 your 'data-driven' culture is a joke (and ai won't fix it).: 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 your 'data-driven' culture is a joke (and ai won't fix it). 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 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.
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
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.