DeepGreenLabs
1-3-5 Year Thesis

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.

Today, AI’s primary role is helping us survive the complexity of modern work.

From a first-principles view, businesses face overwhelming information and inefficiency.

AI’s immediate enablers are clear: accessible LLM APIs, fast fine-tuning, and affordable compute power.

As a team, we see this as AI serving the “physiological needs” of the enterprise. Just as humans seek food and shelter, companies seek stability and predictability.

At DeepGreen, we’ve designed Ziggy, our deployable AI agent, to do exactly that: ease cognitive load, automate repetitive tasks, and free up teams for higher-order thinking.

For me, this is like feeding an undernourished system. We’re giving organisations the operational calories they need just to survive today’s complexity.

But of course, survival is not the summit. It’s just base camp.

Three years ahead, I expect — and we expect as a team — the shift from automation to augmentation.

The question evolves from “What can AI do for me?” to “What can AI do with me?”

The enablers will be more advanced: multi-agent systems, orchestration layers, and AI-native platforms.

Behaviourally, this is the moment organisations will begin to see AI not just as a tool, but as a teammate.

At DeepGreen, we are building this future consciously through our ecosystem of AI workers. Ziggy, who today focuses on task execution, will evolve to anticipate needs, working proactively rather than reactively.

Alongside Ziggy, we’ve introduced Juno — designed not just as an executor, but as a strategic partner. Juno is built to help teams explore pathways they hadn’t considered, co-designing solutions, and offering insights before the question is even asked.

In this future, Ziggy and Juno operate in tandem: Ziggy drives operational excellence, while Juno orchestrates strategy and foresight.

And here’s a bold prediction: I believe we’ll start to see claims of “zero-employee companies” emerge within this timeframe.

To be clear, they may begin as provocative slogans more than operational realities — but the seeds will be real. AI agents like Ziggy and Juno will run core functions autonomously, and human input will shift to oversight, ethics, and creativity.

This is the “belonging and esteem” level of Maslow’s hierarchy.

AI becomes part of the social fabric of work — contributing meaningfully, earning trust, and elevating human capability.

Personally, I see this as the turning point where AI stops feeling like automation and starts feeling like true collaboration.

Five years may sound far, but in AI years, it’s tomorrow.

This is when, from first principles, AI moves from augmentation to transformation.

The challenges become larger: designing AI-native businesses, creating new markets, and rethinking entire categories of value.

The enablers? Autonomous agents, advanced reasoning engines, and alignment mechanisms that keep AI goals tightly coupled with human values.

At DeepGreenLabs, our ambition is to go beyond tools and platforms.

We want to become part of the invisible operating system of AI-powered enterprises — enabling businesses to function autonomously, while humans lead with creativity and vision.

In this future, Ziggy and Juno will form the backbone of AI-native organisations: Ziggy ensuring operational mastery, Juno orchestrating strategy and opportunity. Together, they will enable the rise of genuine zero-employee businesses — not as slogans, but as functioning realities.

A new class of companies will emerge, born autonomous from day one.

And just like electricity, AI will quietly run beneath everything.

It will power industries, connect ecosystems, and enable human creativity to flourish at unprecedented scale.

For me, this is the ultimate destination: self-actualisation.

AI doesn’t just do tasks — it enables us to become more human.

We move from inbox zero to chasing moonshots.

From drowning in data to swimming in insight.

From fearing automation to embracing augmentation.

This is not about AI replacing humans.

It’s about AI revealing our full potential.

I’ve learned, sometimes the hard way, that even good bets don’t always pay off on schedule.

That’s fine.

Because quality decisions matter more than predictable outcomes.

At DeepGreenLabs, this is how we think.

Our 1-3-5 year thesis is not just a forecast — it’s a commitment to building deliberately, with clarity of purpose and a deep respect for time.

And this is a future we’re deeply committed to building — powerfully, quietly, and decisively, like electricity itself.

        - Owais Amiri