Working Smarter with AI

Imagine you’re a chef who has spent decades perfecting your signature dish. Every movement has purpose—the way the dough is folded, how long the sauce simmers, the precise moment you take the pan off the heat. None of it is written down. Now imagine an AI researcher offers you $150 an hour to let them study how you cook. You think they want to know what type of pans you prefer, the brand of spices in your spice rack, whether you mince things by hand or use a food processor. Y

Prompting is a valuable part of using AI to solve problems, but it is not equivalent to system design. Treating these two activities as interchangeable (or worse, not understanding there is even a difference) is often the separator between success and failure with AI.

The uncomfortable truth? Unless you were an AI-first organization or you had a particularly prescient CTO, any platform architected before November 2022 is likely outdated.

You never think about it. But language is pattern. And patterns can be calculated.

The era of casual AI experimentation is ending. The era of professional AI implementation has begun.

Every serious AI product you’ve used that looks simple, looks that way because the people designing it made it that way. The tools we’ve been talking about so far are generalist products for the mass public. But those same tradeoffs break down fast when the use case isn’t a general audience.

With all the talk going on about AI, it still amazes us that so few people are talking about the ‘magic’ of embeddings—except for maybe in more technical circles.

And for small businesses that know where they bleed time and focus, AI is actually cheap and accurate enough to do something about it today.

Experienced writers feel this immediately. Something is off. Too much explaining. Too many words where one would do. No sense of rhythm, no

Physicians and nurses spend hours each day writing and reviewing notes, often with minimal standardization across hospitals. Why?

Why would anyone still be hiring people to fill out RFPs manually?

Given these variations, an off-the-shelf AI model would be ineffective. Due diligence requires tailored intelligence, not generic automation

Until now, markets had no way to quantify language at scale. Analysts read what their human brains could manage, missed what it couldn’t...

This shifts AI from a competitive threat to a competitive moat, ensuring that sponsored content remains ...

By implementing this AI-powered system, Pure Math AI has significantly enhanced it's ability to generate content.

There was a time when people read the markets like a novel, one chapter at a time. They waited for...

The goal was simple: create Japanese versions of English interview podcasts featuring prominent financial leaders to promote their upcoming