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How do you position and scale an AI company in a rapidly evolving market?

Join us for an in-person Office Hours session in San Francisco with Alan Hsia, VP of Marketing at Fireworks AI.

Alan brings deep expertise in go-to-market strategy and will share insights on:

• Building a strong brand in AI from the early stages
• Creating a differentiated GTM strategy to create distance from competition
• Aligning marketing with sales for maximum growth
• This session is designed for early-stage AI founders looking for tactical advice from a seasoned Marketing & GTM leader.

📅 March 25, 2025, 5:30pm
📍 San Francisco
🔗 Register here

A small spin-out from a publicly traded behemoth launched with the ambitious vision of transforming their entire industry. Within just a few years, as capital markets shifted in their favor, they emerged simultaneously as both innovators & titans in their field.

We don’t often think of private equity this way, but that’s exactly what happened when KKR spun out of Bear Stearns and Michael Milken at Drexel Burnham Lambert catalyzed the junk bond boom of the 1980s.

Imagine if every time you edited a document, the word processor forced you to retype everything that had been written before that edit.

How expensive would that be for a company?

This is exactly how data transformation works today. Each time a data engineer modifies some part of the data stack, the Cloud Data Warehouse & its transformation layer recalculates everything.

What if the system were designed so that it only recalculated the metrics needed? How much less expensive would it be?

As startups scale, effective management becomes the difference between chaotic growth and sustainable success. After analyzing hundreds of posts on startup management, I’ve distilled the key pieces of advice that founders and leaders should keep in mind.

1. Management Philosophy

• Management is a design pattern: Just like engineering has patterns, management has best practices that can be learned and applied systematically.
• Use Situational Judgement: tailor support for employees ranging from micromanagement for new hires to hands-off for high performers.
• Lead authentically: The best managers don’t rely on mimicry but develop their own authentic style based on their values and strengths.

Management, like engineering, has repeatable design patterns that can be learned and applied

Which is the best business in AI at the moment?

I analyzed Q4 revenue data from publicly traded companies across multiple sectors—software companies, consulting firms, and hardware manufacturers to determine which segment dominates the AI market.

NVIDIA’s data center business dominated the field, generating $31b in Q4 revenue with impressive margins exceeding 70%.

In second place, Microsoft’s AI business, including Azure, is at a $3.25b Q4 revenue.

During a recent Theory Office Hours with Kady Srinivasan CMO at Lightspeed Commerce, Dropbox, and Klaviyo, we discussed several powerful insights emerged on how early-stage companies should approach marketing.

Here are the highlights :

1. Define Your ICP Before Anything Else

   The most fundamental decision for any startup is determining your Ideal Customer Profile (ICP). Without clarity on exactly who you’re targeting, GTM efforts become diluted and ineffective.

Most startups play defense when discussing pricing with customers. They dance between asking for too little, leaving money on the table, and asking for too much, only to lose the customer’s interest. The very best companies lead their customers in that dance. They use pricing as an offensive tool to reinforce their product’s value and underscore the company’s core marketing message.

Algorithms needed for unpredictable journey. Significant compute costs, endless data processing, long periods of unexplained failures. Safe convergence doubtful. Honor & recognition in event of success.

What Shackleton might have written in 2025.

AI isn’t perfect but its productivity gains are undeniable. ServiceNow, Microsoft, and Amazon, plus nimble startups generating tens of millions in ARR with teams small enough to feed with a few pizzas all have benefitted.

The new boast of 2025? ARR per employee measured in the millions up 5x or more from the previous generation of software companies.¹ Fueled by AI.

A decade ago, most startup pitches ended with a calculation justifying the amount they sought to raise.

In other words, the raise was an output of the financial model.

But for the most sought after companies, the raise amount is disjointed from the capital needs of the business - instead it’s driven by the fundraising auction.

Great fundraisers are the teams that build the most auction pressure.

This auction dynamic, combined with venture capital’s explosive growth over the last decade, has transformed fundraising strategy. The goal is no longer to raise what you need, but to optimize for the lowest cost of capital.

October 2024 marked a critical inflection point in AI development. Hidden in the performance data, a subtle elbow emerged - a mathematical harbinger that would prove prophetic.

What began as a minor statistical anomaly has since exploded into exponential growth.

Since then AI performance has surged attaining a new trajectory, a new slope - no longer linear but geometric.