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Whenever I hear about a new startup, I pull out my research playbook. First, I understand the pitch, then find backgrounds of the team, & tally the total raised.¹

Over the weekend, I decided to migrate this workflow to use AI tools, & the process taught me something important about how we’re actually integrating AI into our work.

Tools are small programs that expand AI capabilities. ChatGPT might call a web search tool to read a blog post I’d like to summarized. Claude might call the terminal tool to change file permissions in my current directory. Gemini might call a tool to find the latest stock price of the most recent IPO I’ve been following.

Which level do I want to use AI?

I find myself asking this question more & more frequently & I think the answer means at work I’ll be using many AIs - not just one or two.

Why are there so many levels? It depends on the context I want the AI to have.

Pricing changes are hard.

Fundamental shifts in go-to-market strategy tied to pricing? Monumentally difficult.

We recently dove deep into one such transformation with Barr Moses, CEO of Monte Carlo, during a Theory Ventures Office Hours. Monte Carlo, a data & AI observability pioneer, moved from traditional annual contracts to a daily revenue model.

These were the three most important takeaways for me from the conversation:

1. Monte Carlo customers were used to buying usage-based rather than contract-based & the alignment was an important & critical evolution. Ali Ghodsi said the annual contract is “selling like Oracle in the 1980s.”

NVIDIA announced earnings yesterday. In addition to continued exceptional growth, the most interesting observations revolve around a shift from simple one-shot AI to reasoning.

Reasoning improves accuracy for robots - like telling a person to stop and think about an answer before they reply. Here’s an example where I asked Gemini to create a financial projection for NVIDIA for the next five years.

With Salesforce announcing its intent to acquire Informatica & Google’s announced acquisition of Wiz, 2025 is the best year in the last six in terms of M&A value.¹

These massive acquisitions, totalling more than $32b propel 2025’s year-to-date number to decade highs - exceeding the fast-money pre-Covid days of 2020.

Only five months in, 2025 has been the year of stablecoins. A Fireblocks survey of banks conducted in May underscores how quickly the market is moving.

• 90% of respondents are taking action on stablecoins. 49% of them use stablecoin payments already. Only 10% are undecided on adoption.
• 58% of respondents use it primarily for an international money movement.
• 86% report infrastructure readiness with wallets and APIs or partnerships. 75% see clear demand from customers.

Why are so many banks and payment processors aggressively moving to adopt stables?

We’re looking for an investor to join our team.

We are seeking people who see alpha in ambiguity, who are passionate about crafting theories about the future & making them a reality.

The ideal person :

• enjoys researching themes & debating the future
• thrives working with founders to navigate the challenges of building companies in hypergrowth
• brings an accretive network to the firm
• values intellectual honesty & candor

If you’re interested, apply here.

“Now with LLMs, a bunch of the perceived quality depends on your prompt. So you have users that are prompting with different skills or different level of skills. And the outcome of that prompt may be perceived as low quality, but that’s something that is really hard to control.”

Loïc Houssier, VP Product at Superhuman, shared this perspective on a recent podcast. AI products differ from classic software in that the experience is in large part determined by the user.

What if every software spoke English? We asked this question about two years ago but now they do - with AI we can retrofit existing apps to speak English.

I don’t want to have to figure out any particular menu to find a setting or understand how a product manager or designer intended me to use the product.

I just want to talk to my computer and tell it what to do.

AI agents are increasingly outperforming humans in various tasks, yet they typically cost 70% to 80% less.

Will they ever be able to charge a premium?

Waymo has reduced accidents by 82 to 92 percent in San Francisco. Waymos monitor more sensors, don’t fatigue, and react more quickly than humans. But, Waymo is often 13-33% cheaper than alternatives.

Within medicine, recent studies suggest AI can be at least as accurate as human doctors, in the evaluation of rashes from smartphone photos, estimating longevity, and diagnosing medical case histories, scoring 90% accuracy compared to human doctors who averaged in the mid-70s.