The AI Spell-Checker for Ambition

The Evolution of Ambition in the AI Era

We are collectively making a massive mistake with AI. We're chasing fractional improvements in efficiency, and celebrating automated note-takers and report generators as if they are the endgame. They aren't. They're the low-hanging fruit, and the orchard is full of mundane applications.

The spell-checker of tomorrow isn’t about correcting our grammar, it’s about correcting our ambition.

As someone who has spent over a decade at the intersection of AI, product development, engineering, and the physical sciences, I’ve watched the definition of “possible” expand and contract like a living thing. But what’s unfolding now is different. We’re not just pushing the boundaries of what’s impossible, we’re erasing them.

The End of “Good Enough” AI

Let’s be honest, we’re drowning in AI automation. Every product, every app, every interaction is being enhanced with AI-powered features. Automatic note taking, summarization, report generation… pick your low hanging fruit. Yes, these features are necessary. Yes, they make compelling entry points to AI. And yes, they’re becoming utterly mundane.

As large cloud providers and tech giants rush to embed AI into everything we digitally touch, all the while chasing fractional improvements in efficiency, a more profound opportunity is being overlooked. For the rebels, the visionaries, and the truly ambitious it’s time to look far beyond automation. It’s time to redefine what we consider impossible.

This narrow focus on automation is a far cry from the bold thinking that defined the last century's greatest technological leaps. To understand the scale of the opportunity we're missing, we need to look back at the original…

The Birth and Evolution of Moonshots

The space race – a time of unprecedented technological rivalry gave rise to the term “moonshot”. JFK’s ambitious goal of reaching the moon wasn’t just about landing on a celestial body, it was about proving that humanity could achieve the seemingly impossible through focused effort and innovation.

Fast forward a few decades and the term was adopted by the tech industry to signify a disruptive, outlandish, and incredibly high-risk project to solve fundamental human challenges. The bar was raised. Improving something by 10% wasn’t enough, you needed to make it 10x, 100x, or more. This mentality was paramount to giving birth to transformative technologies and companies like,

• The Human Genome Project and its ambitious goal of mapping our genetic code
• Google’s mission to organize the world’s information
• DeepMind’s goal of creating human-level artificial intelligence

The list goes on and on…

Why Moonshots Often Miss Their Mark

With great reward comes great risk. There’s some shared commonalities that make moonshots exceptionally challenging.

• They require breakthrough advances across multiple technical domains
• They demand years to decades of R&D
• They need massive capital investment and rare human expertise
• They face enormous uncertainty with undefined paths to success

But here’s the fascinating bit. The primary killer of moonshots isn’t technical complexity or even the enormous amounts of required funding to get them off the ground. It’s uncertainty. As someone who has navigated these waters many times, I can tell you that humans are fundamentally poor at handling sustained uncertainty. There’s many reasons founders are 2x more likely to suffer from depression, and 3x more likely to struggle with substance abuse, but the unrelenting and crushing weight of constant uncertainty is a major contributor. This uncertainty doesn’t end as a solo, internal struggle, it translates into uncertainty to the backers of moonshots, namely investors. Without investors on board, forget the funding, and without the funding say goodbye to the possibility of hiring a seasoned team of genius domain experts. Without the experts, forget about delivering on that moonshot promise. As you can see it’s all tightly coupled. So what if we could reduce or even remove large amounts of uncertainty? How would this transform moonshots into commonly occuring success stories?

The AI Transformation - From Shots to Trajectories

This is where artificial intelligence changes everything. As we move closer to AGI (Artificial General Intelligence), traditional moonshots are transforming into what I call “moon trajectories” - clearly defined paths with quantifiable solutions that can be achieved at previously impossible timescales.

Consider what this means,

• Small teams can now execute at scales previously reserved for governments and billion-dollar enterprises
• Experiments can be proposed, simulated, and iterated far beyond human capabilities
• Technical fields are being democratized, making expert-level knowledge accessible to ambitious generalists
• Advancements in physics, mathematics, biology, and medicine are becoming available to anyone who can dream big enough

The Real Opportunity Isn’t Efficiency, It’s Capability

The key shift that many are missing is that AI’s true potential doesn’t lay in making existing processes more efficient, it’s in enabling entirely new capabilities. The next Google, SpaceX, or OpenAI won’t emerge from automating tasks. They’ll come from leveraging AI to create entirely new domains that don’t yet exist.

As AI continues to evolve, the barriers that traditionally made moonshots so risky are evaporating.

• Domain expertise requirements are dropping as AI systems provide human-level (and soon beyond) guidance
• Capital requirements are shifting from long-term R&D to compute resources
• Multiple ambitious bets can be pursued in parallel, rather than betting everything on a single trajectory
• Uncertainty is being replaced by predictable, modelable outcomes

What This Means for Tomorrow’s Innovators

For those building the future, this brave new world demands a fundamental shift in thinking. The question isn’t, “How can we use AI to make this more efficient?” but rather “What became possible today that was impossible yesterday?”

The saturated landscape of AI automation features is just beginning. The real innovation will come from teams who understand AI isn’t just a tool for optimization… it’s a foundation for reimagining what’s possible. These teams operate from a new set of rules,

• They ask different questions. Not “How can AI make us more efficient?” but “What became possible today that was impossible yesterday?”
• They understand the shift in value. They know that AI’s true potential lies not in optimization of the old, but in the creation of the new.
• They see AI as a foundation. It isn't just another tool in the stack; it IS the bedrock upon which entirely new domains will be built."

Are you thinking big enough for the AI era?

Originally posted on LinkedIn: Ambition in the AI era