Yesterday I wrote about leaving Google after twenty one years and said there was a next chapter I would tell you about today. This is it.

Chris Perry and I are starting a company. It is called Vycari, we are building agents, and we are looking for people to test what we make. I want to spend most of this post on the problem rather than the product, because the problem is the interesting part and because the product is not ready for you yet.

Using agents today is a skill

Here is what it currently takes to get real value out of an agent.

You curate your skills, your triggers, and your extensions. You pick the right model for the task and make sure it is wired to the right API key. You keep the right software installed and updated on your machine. You have a sandbox configured, because obviously you have a sandbox configured. You learn which failures are the model’s fault and which are yours. You read changelogs, because the thing you learned last month is already wrong.

That is not using a tool. That is adopting a hobby.

I want to be careful here, because I do not mean that as a complaint. There is nothing wrong with AI as a hobby. A great many of the real sea changes in personal computing were driven by people who treated the work as an avocation first and a profession second, and the current moment is no different. I count myself among those people. They are my people. This blog exists because of them, and I am not going to stop writing for them.

But it is worth being honest that this is what we have built so far, and about who it excludes.

Most people do not want a hobby

Not everyone wants their tool to become a pastime. Not everyone wants to marvel at the stack, or to feel the small thrill of watching software take an action in the real world on their behalf. Plenty of capable, curious, technically fluent people simply want to get something done, and they want to use whatever makes that easiest.

I am friends with a lot of these people. They are not incurious and they are not afraid of technology. They carry a supercomputer in their pocket and use it fluently all day. They have just never been given a reason to believe that an agent is for them, because every agent they have encountered asked them to become a hobbyist first.

Chat apps are the exception that proves the point. They reached enormous audiences because there was nothing to adopt: you type, it answers, and the entire interface is a thing you already knew how to use. Step outside that box and agents are still close to magic for most people, and magic is not a compliment when you are trying to get through a Tuesday. Agent products remain genuinely hard to use, and the difficulty has very little to do with how good the models have become.

What I keep coming back to

The most useful thing I learned in two years of building agents has almost nothing to do with models. It is this: people do not bounce off AI because it is not smart enough. They bounce off because the cost of using it, all of it, the setup and the vocabulary and the remembering to go there, is higher than the problem they were trying to solve.

Which means the frontier I find interesting is not making these systems more capable. They are already more capable than almost anyone is extracting value from. The frontier is closing the enormous distance between what the technology can do and what an ordinary person can actually get out of it on a normal day, without a new app, a new habit, or a new hobby.

That gap is not a model problem. It is a product problem, a reliability problem, and a taste problem. It is also, as far as I can tell, wide open.

What we believe

We are early enough that I would rather tell you what we intend than what we have built. Four things we are holding ourselves to.

Meet people where they already are. If using the thing requires a new destination in someone’s day, we have already lost, no matter how good it is once they arrive.

Earn the trust the access requires. An agent worth having needs to see calendars, mail, and contacts, which is about as intimate as software access gets. There is no version of this business where that access to private data becomes an advertising product, and there is no version where you cannot take your data and leave.

Never make you learn our vocabulary. Nobody should have to know what a skill is, or which model answered, or that any of this is AI at all. Those are our problems. The user’s problem is that they asked for something and want it handled.

Be warm about it. An assistant you find pleasant is one you will actually use, and an assistant you actually use is the only kind that matters.

Who we are

My co-founder is Chris Perry. He is the CEO. I am the CTO. Chris used to report to me, and putting him in the CEO seat was one of the easier decisions either of us has made.

We have been circling each other for about a decade. We met when I was running Street View and imagery inside Maps and he was a PM on Google Photos, back when our two teams were trying to make those products understand each other’s pictures. Years later he turned up in the AI Developer organization I was running, as the product lead for Colab. Most recently we were both on the founding team of Gemini CLI and shipped its Workspace extension together. Somewhere in there he stopped being someone I had worked with and became someone I wanted to build with. He is writing his own version of this announcement, and his path here is different enough from mine that you should read both.

It is just the two of us right now, and we are both in the codebase. One of the underrated pleasures of leaving a large company is that you get to assemble the org chart from scratch, based on who is best at the job rather than on who has been there longest.

The part where I ask you for something

Twenty one years at Google taught me how to build systems where the hardest problems are problems of coordination. This is a different kind of hard. There are two of us, the feedback loop is measured in hours, and the person on the other end of a failure is someone who trusted us with something that mattered to them. I have not been this uncomfortable in a long time, and I have not enjoyed work this much since 2008.

We are opening to testers in the coming weeks, a few at a time and deliberately, because the failure I am most afraid of is someone relying on this and being let down. If you would like to be in that first group, put your name down here. What we want back is your honest experience, particularly the parts where it does not work.

And if the person who came to mind while you were reading this was not you but someone else, someone who would get enormous value from an assistant and would never in their life go looking for one, then you have understood exactly who we are building for.

I will keep writing about the engineering here as we go. It is going to be a good year.