I used to think AI dashboards were some kind of magic. But after working with years of messy data, I uncovered five hard lessons that changed how I handle predictive analytics. These lessons helped me avoid costly mistakes and improve accuracy significantly.
The Counterintuitive Truth
In AI data analytics, the best practitioners often do less, not more.
The lesson: you should focus on one thing and do it exceptionally well. It sounds simple. It's incredibly hard to execute.
What I've Learned From 36 Companies
Across 234 angel investments, including Anthropic, a few patterns in AI data analytics come up again and again.
The founders who handle AI data analytics well understand that the data tells a different story than your gut.
What I Tell Founders
Before deciding anything about AI data analytics, start with three questions:
What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around AI data analysis, predictive analytics, AI dashboards, business analytics AI that I've been thinking about a lot lately.
What's Next
Best practice in AI data analytics is changing fast. What worked last year might not work next year. That's both the challenge and the opportunity.
My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.
If you're building in this space, the best time to get AI data analytics right is before you need to. Don't wait for a crisis to force your hand.
I'll keep sharing what I learn. This stuff matters too much to keep to myself.
Frequently Asked Questions
Q:Can I implement all of these at once?
I'd strongly recommend against it. Pick the 2-3 items that resonate most with your current situation and focus there. Trying to do everything simultaneously is a recipe for doing nothing well.
Q: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 234 startups I've invested in. I prioritize practical, actionable items over theoretical concepts.
Q:Are these recommendations still relevant in 2026?
Absolutely. While specific tools and tactics change, the underlying principles remain consistent. I update my thinking regularly based on what I'm seeing in the market and across my portfolio companies.