Posts

Now that we’ve compressed nearly all human knowledge into large language models, the next frontier is tool calling. Chaining together different AI tools enables automation. The shift from thinking to doing represents the real breakthrough in AI utility.

I’ve built more than 100 tools for myself, & they work most of the time, but not all the time. I’m not alone. Anthropic’s Economic Index report reveals that 77% of business use of Claude centers on full-task automation, not co-piloting.

Like breakfast at a diner, software is cheap & fast to make. Ask for a new task management tool & you’ll have the first version in less time & for less money than an omelette.

AI-built tools may not last long. Some survive only a few minutes, long enough to answer “What’s our turnaround time this week?”

Others remain useful for a few days or weeks, like an app that can spin up a lightweight project tracker for onboarding Walmart. Sometimes they persist beyond a month.

Understanding technology is at the core of how we research new theories. As part of that effort, Theory is starting a developer relations team.

Developer relations for venture capital? What does that mean?

Internally, we’ve built hundreds of agents, we’ve struggled to debug tool calls, tested large action models, & work through AI every day. We’ve hosted events on how to build with AI.

We’d like to contribute back to the community with our experiences & learn from other builders.

MCP enables an AI to understand which tools rest at its disposal : web search, file editing, & email drafting for example.

Ten months later, we analyzed 200 MCP tools to understand which categories developers actually use.

Three usage patterns have emerged from the data :

Development infrastructure tools dominate with 54% of all sessions despite being just half the available servers. Terminal access, code generation, & infrastructure access are the most popular.

$4b in revenue run-rate. There are two data giants both now at this mark after Databricks announced it surpassed the threshold.

This is an opportunity to compare the two leading data companies at a revenue intersection.

Head-to-Head Comparison

Both are at $4b in revenue. Each claims over 650 customers paying $1M+ annually. Each boasts strong net dollar retention (140% vs 125%).

Each morning brings the excitement of a world that seems to have changed overnight.

A new model arrives promising a novel way of working. Like unboxing an iPhone in 2008, but with the steady cadence of the near-daily Amazon Prime delivery ferrying its promise of expected newness.

Those gifts present puzzles for those on the cutting edge. They offer the opportunity to look at a problem with a supercharged machine, gleaming tools replacing the loved, blunted ones.

At Theory, we create theories about the future & help them become reality.

A significant part of our work is research, understanding spaces & their evolution. Internally, we’ve been working with living market maps since our foundation.

Today, we’re exposing some of that work on our new homepage theoryvc.com. Our team especially Lauren, Bryan, & Adam have worked to visualize the structure of our market maps into a three-dimensional living market map that we will continue to update.

Software development has operated within established boundaries for decades, with clear divisions between those who code & those who don’t.

But what happens when those boundaries dissolve overnight, & anyone can build functional applications for the price of a monthly streaming subscription?

For twenty years, professional software development meant specialized teams, lengthy sprints, & rigorous adherence to architectural best practices. Companies invested months in planning, weeks in development cycles, & substantial resources in quality assurance. The barrier to entry remained high, protecting established players & maintaining predictable market dynamics.

Another day, another earnings report with accelerating growth from AI. Snowflake earnings yesterday demonstrates yet again the impact of AI on a $4.4B revenue business.

Snowflake’s revenue has rebounded from a low of 26% to 32% quarter over quarter.

And once [customers] are on our platform, AI becomes a cornerstone of their strategy, powering 25% of all deployed use cases with over 6,100 accounts using Snowflake’s AI every week.

AI vendor revenue will double classic software in terms of new bookings this year.

This trend is so large it’s starting to have second-order effects.

MongoDB reported strong Q2 FY'26 results, delivering $591M in revenue with 24% year-over-year growth. AI is causing a second-order effect & a resurgence in growth in Atlas, the cloud-hosted version of MongoDB, which represents 74% of total revenue. We’ve seen a reacceleration within the hyperscalers already, but now the impacts are felt beyond.