It’s wild how many AI Agent opportunities there are that are much bigger than their pre-AI markets. The TAM of the code editor market was a few billion dollars in 2020. AI coding agents could be a $50-100B+ market in the next 5-10 years. You can do this for many spaces.

In a world of AI Agents, the market size for SaaS grows vs. shrinks. Not only do you still need systems of record to manage enterprise data and workflows, but AI Agents create completely new value propositions for these tools. You’re bringing work to the customer now.

Here’s the new ChatGPT agent combing through market and strategy data stored in Box to produce a powerpoint presentation. The ability for AI Agents to connect to data from anywhere, use a computer, and automate work in the background is going to be wild.

ChatGTP just launched an agent with connected apps and its own computer. Here's a test of the agent tasked with making a strategy presentation with market research and a template from Box. It's early, but the future is agents doing work for us 24/7 in the background.

The software business model will be seats for the user and consumption for the agents. The big upside now is that there are many AI Agent opportunities where the TAM vastly exceeds the previous potential seat revenue. Because now you deliver work, not just enable it.

AI Agents provide an opportunity for bringing automation to so many categories of work that you could never automate with software before. Most of the time in software you’re competing within existing, largely well defined markets. While the spend may even be growing, there usually are still zero sum dynamics in the space. Given the reset happening with AI Agents, it would be a mistake to largely focus on just building what we’ve always been able to do with software, and just incrementally adding some AI capabilities on top. The big play right now is to build AI Agents for brand new categories by bringing a deep domain expertise, vertical understanding, data from the customer, and tool use. There are endless categories that would have been nearly impossible, or at least far too expensive, to automate before, where we finally can now. If you had tried to do this even 1 year ago it probably would have been too early. And ultimately, these categories will likely meaningfully exceed the total size of current enterprise software spend, as they can be tied with the amount of output generated vs. capped by a per seat price. Incredible times.

We’re at a point where we have the intelligence levels in models to build far more AI Agents than have been created thus far. Now is the time for bridging the AI to the customer with the right domain expertise, understanding vertical workflows, and context engineering.

We’re at a point where we have the intelligence levels in models to build far more AI Agents than have been created thus far. Now is the time for bridging the AI to the customer with the right domain expertise, understanding vertical workflows, and context engineering.

We’re at a point where we now already have the intelligence levels to build far more AI Agents than have been created thus far. Now is the time for bridging the AI to the customer with the right domain expertise, understanding of workflows, and context engineering.

In the early days of cloud, most enterprises needed to be convinced of the importance. Now, at the similar time frame in AI rollout, even the most conservative companies recognize how significant AI will be. This creates an entirely different dynamic.