DeepGreenLabs’ 1-3-5 Year Thesis: 

By Owais Amiri, Co-founder of DeepGreenLabs

Seth Godin, in a conversation with Tim Ferriss about his book This is Strategy, briefly pivoted to talk about AI.

He said something that has stayed with me ever since:

“AI is our age’s electricity.”

That line felt simple, but profound.

Electricity wasn’t just an invention. It became the invisible infrastructure of modern life — flowing through industries, cities, and homes, reshaping everything it touched.

AI feels the same to me. It’s not a feature. It’s not a trend. It’s a force — permeating the fabric of how we live, work, and build.

At DeepGreenLabs, this belief shapes everything we do.

We aren’t building gimmicks or short-term tools. We are building the infrastructure for the next generation of work. The command centres, the workers, the orchestration layers that will run beneath the surface, just like electricity runs through every modern business today.

When ChatGPT first launched, I remember the wave of excitement.

It felt like AI had finally arrived — ready to transform everything from how we search, to how we work, to how we create.

But what followed was, in many ways, a wave of toys.

We saw people using AI mostly for content generation, rewriting, or summarising. At first glance, it seemed trivial. But I’ve come to appreciate that this work isn’t just playful — it’s essential. Compressing hours of mental labour into seconds is not cosmetic. It is a real unlock.

In fact, I had a bet with friends at the time — and I said, with full conviction, Google search will die within a year.

My reasoning was simple: if AI can generate answers directly, why would anyone click on ten blue links? Especially when Google’s business model depends on those links.

But I was wrong. Search has proven more resilient than I expected. Google continues to thrive, adapt, and grow, even as generative AI expands.

This was a healthy reminder for me: I am in the business of making quality decisions, but outcomes often aren’t in my hands.

And that’s precisely why I think in timeframes.

What I want to see in 1, 3, or 5 years may not materialise on schedule. But the exercise itself — mapping the future deliberately — sharpens my thinking, and sharpens how we, as a team, build at DeepGreenLabs.

We frame our thinking using two lenses that ground us:

→ Maslow’s hierarchy of needs, because AI, like humans, climbs from basic survival to meaningful self-actualisation.

→ First principles thinking, because underneath the noise, fundamentals don’t lie.

Here’s how I think about AI’s climb over the next 1, 3, and 5 years — and how we, as a team, are building towards it.