There's a question I've been wrestling with for a while. Only recently did I finally understand the answer.
"Should I Keep Going or Give Up?" Is the Wrong Question
I made a video earlier where I said something contradictory.
One moment: "When systems crash, maybe the timing just isn't right—push through and things might turn around." The next: "You need to cut losses quickly."
These sound like completely opposite advice, and frankly, viewers were confused. Then it hit me—people giving these answers are usually victims of survivor bias. Successful people look back and preach persistence. Failed people preach adaptability. Everyone's right.
But here's the thing: anyone actually in the trenches is asking themselves the same gut-wrenching question over and over: When do I push? When do I pivot?
I've lived this firsthand.
In 2023, I jumped into e-commerce. Sold pet food, human food, tried dozens of products. Then I found something that worked—gummy supplements doing 5,000+ units a month. Finally, I stopped chasing new products. I told myself: product selection decides everything.
So I went to the manufacturer and tried scaling it under my own brand. Sales dropped like a stone.
For months, I didn't look for new products. I just obsessed over marketing, pushing harder, staying committed. The product died anyway. I was devastated for a long time.
Looking back, I realized something: Persistence wasn't wrong. Adaptation wasn't wrong either. The stage I was in mattered more than anything.
Exploration Phase vs. Stability Phase
After that, I reframed the whole question.
Think of it like playing Civilization VI. During exploration, you're sending scouts in different directions—each path might be wrong, so you need to keep adjusting and testing. The core here is fast iteration until you find what works.
Then you hit 0→1. The business model actually generates money. You enter stability phase. Now the question isn't "Is the direction right?" It's "How big can this get? Where's the ceiling?" In stability, you lock into the growth engine that's actually working. You don't keep rotating strategies.
Eventually, everything enters decline. If persisting stops making sense, reset your mindset and start exploring again.
This framework shifted how I think. But the real test came when I spotted a new opportunity—and suddenly realized: frameworks aren't enough. You also need to recognize which opportunities don't actually belong in your world.
More Opportunities Don't Mean Better Decisions
I recently got deep into researching an AI-related angle. It looked incredibly promising.
My thinking: Could this become my cash flow while my main AI project is still proving itself? Cash flow stress is real.
I landed on: API proxy services.
Low startup cost. Server runs ~$200/month. Theoretically, 500 users = solid income. On paper, this looked like a solid business. I even found some cost edges. I was this close to jumping in.
Then research went deeper, and I found a truth: a profitable model doesn't mean a viable business.
First problem: Compliance. The space exists in a grey zone. No clear rules. You can operate today and get shut down in six months. Risk never disappears.
Second problem: Competition. More people entering every week. Without cost advantages, you can't attract users. With cost advantages, price wars compress margins until there's nothing left.
Third problem: Hidden overhead. People see the server bill. They don't see what actually drains time: handling attacks, managing risk, content moderation, customer support. This stuff will destroy you.
So I made a choice: Don't do it.
Researched the whole thing. Then talked myself out.
But I didn't waste the research.
Where Real Value Actually Lives
The whole investigation pivoted into something else—private deployment.
Unlike API reselling, private deployment solves real problems for enterprises: data security, ownership, actual integration into their operations. Yeah, it's harder. You need to understand hardware, deployment, real customer needs.
But here's what I see coming: AI capabilities get cheaper every month. What becomes valuable isn't who sells the model—it's who puts AI inside actual workflows.
So the real question shifted: it's not "Should I persist or walk away?" It's "What phase am I in, and does this opportunity fit my actual path?"
When founders see AI creating opportunities everywhere, it's tempting to chase them all. But abundance of options actually tests your judgment harder—sometimes walking away from a profitable model is how you protect the bigger picture.
That's what clarity looks like.
If you're stuck in that same loop—"Do I keep going or cut losses?"—here's what matters: Know what phase you're in. Know if this opportunity actually belongs to your journey. Accidental money and strategic money tell completely different stories.
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