Last week, a founder pitched me an “AI-powered” customer retention tool. It was essentially a chatbot slapped onto a dying social platform. When I asked what specific problem it solved for users, he couldn’t answer. Instead, he leaned into buzzwords: “leveraging machine learning” and “neural network insights.”
Sound familiar?
Every day founders echo the same question in pitch meetings and boardrooms across the country:
“How can we use AI to get more customers?”
It sounds strategic. It sounds investor-ready. But it’s the wrong question.
As a venture capitalist, technologist and advisor to dozens of early-stage companies, I see this all the time. Under pressure to grow fast, founders treat AI as a bolt-on feature — a shortcut to revenue or credibility. But AI isn’t just another tool in your stack. It’s a shift in how you think, operate and solve problems.
If your questions are shallow, your AI results will be too. And unless you reframe your mindset, you’ll miss the true opportunity this technology offers.
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The silver bullet trap
Many founders treat AI like a Swiss Army knife:
User acquisition problem? Slap on a chatbot
Need better marketing? Auto-generate content
Pitch deck due? Let AI write it
Here’s the truth: AI doesn’t fix broken fundamentals.
I recently reviewed a pitch deck from a founder running a struggling social platform. User engagement was flat. Instead of digging into product-market fit they added a vague “AI-powered engagement engine” to the deck, hoping to attract investors.
The result? Confusion. AI wasn’t solving a real problem — it was camouflaging a lack of clarity.
Most founders bolt AI onto ideas that haven’t been validated. What they need isn’t another feature. They need focus.
Yes, 89% of small businesses report AI adoption and over 60% say it improved productivity. But most are still applying AI reactively, not strategically.
The real power of AI isn’t instant answers—it’s sharper thinking.
Surface questions vs. strategic questions
Surface-level questions
“How can AI get us more users?”
“Can AI write our pitch deck?”
“How do we add AI to our product?”
“Will AI features impress investors?”
“Can AI automate our customer service?”
Strategic questions
“What friction points in our user journey could AI eliminate?”
“How can AI help us validate our assumptions before pitching?”
“Which repetitive tasks are draining our team’s creative energy?”
“Where are we making decisions with incomplete data?”
“What patterns in customer complaints are we missing?”
One founder I work with doesn’t use AI to generate content. He uses it to simulate customer conversations, stress-test pitches and explore dozens of ways to frame his value proposition. His secret weapon? Curiosity —and a willingness to be wrong.
Context before code
Founders eager to “AI everything” often skip the most critical step: understanding context.
I call this the HurricaneMethod — pairing binary decision-making with radical empathy. Before building any AI workflow, founders need to deeply understand their teams, products, users and data.
Skip this step and you risk breaking what works — or worse, alienating your users.
Founders who succeed with AI ask questions like:
What’s draining my team’s creativity?
Where are we wasting time or missing clarity?
How could AI support our people, not replace them?
What assumptions about our users need testing?
Related: This Entrepreneur Used AI to Transform Their Business and Create Multiple Revenue Streams — Here’s Exactly How They Did It
AI as a translator
AI is one of the best translation tools ever created — especially inside organizations.
Imagine a non-technical CEO preparing for a meeting with both the CMO and the head of engineering. He feels stuck between two silos, each speaking its own language. He uses AI to simulate conversations, simplify jargon and predict objections. Suddenly, he walks into the meeting as a bridge, not a bystander.
This is the co-pilot mindset: AI should clarify, not replace. Empower, not override.
AI also creates space for “dumb” questions that founders might not feel safe asking out loud. That vulnerability, if embraced, sparks real growth.
Some companies will use AI to cut jobs. The smart ones will use it to level up everyone’s work.
A legal team using AI to spot compliance risks is still a legal team — just faster and more strategic
A junior marketer using AI to draft ideas is still building the brand — just with more iterations
Founders must create cultures where AI supports exploration, not fear. Model curiosity over perfection. Show your team that asking smart questions leads to smarter decisions and momentum.
A 30-day AI reframe
If you’ve been thinking about AI all wrong, reset with this plan:
Week 1: Question your questions
Day 1–3: Ask AI to role-play as your harshest critic and identify three blind spots in your business model
Day 4–7: Give AI your pitch deck and ask: “What would make an investor pass on this?”
Week 2: Empower your team
Day 8–10: Have each team member use AI to solve their biggest time-waster, then share results
Day 11–14: Run “AI office hours” where experimentation is encouraged
Week 3: Document your logic
Day 15–17: Before using AI for any decision, write down your hypothesis first
Day 18–21: Track outputs, your reasoning and surprises
Week 4: Redefine success
Day 22–25: Measure improvements in clarity and decision speed — not just AI usage
Day 26–28: Identify which AI experiments should become permanent workflows
Day 29–30: Share your biggest AI-enabled insight with your team
Remember: AI isn’t the win. Improved clarity, speed and collaboration are.
The competitive edge
AI doesn’t reward the person with the flashiest feature. It rewards the most curious person in the room.
Don’t focus on sounding interesting. Be the most interested. Ask, again and again:
“What am I not seeing yet?”
Then go find out.
Curiosity compounds. That’s your real AI advantage.