I review hundreds of pitch decks every year. The ones that get my failed attempts at ai automation and the right stand out immediately.
Everyone thinks you need expensive, complicated software for AI automation. They're wrong. I built a multi-million dollar company using a few simple, powerful AI tools, and I'm revealing my entire stack and workflow in this deep-dive.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to my failed attempts at ai automation and the 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 my failed attempts at ai automation and the. It's not complicated, but it requires discipline.
Step 1: customer feedback is the only metric that matters This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the market doesn't care about your roadmap 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 my failed attempts at ai automation and the are the ones that treat it as an ongoing process, not a one-time project.
What I Tell Founders
When a founder in my portfolio asks me about my failed attempts at ai automation and the, I usually 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 automation, AI email, AI meeting notes 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 my failed attempts at ai automation and the: there are no shortcuts, but there are smarter paths.
The smartest founders I work with treat my failed attempts at ai automation and the 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 my failed attempts at ai automation and the, 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
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.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
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'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.