Plenty of AI ideas. A harder test for choosing one.
My co-founder and I are building small versions of several ideas before committing to one. Nina’s interview with me became a test of one of them.
My co-founder and I considered building a kind of Kickstarter for AI projects. People would pledge money toward work that needed expensive computing power, and a project could proceed once it had enough funding. Then I worked through what it might take to make a business of it. At a low take rate, billions of dollars’ worth of projects might need to pass through the platform. Getting started would also mean working with funders and nonprofits in a world neither of us knew well. We moved on without testing it.
I can find plenty of AI ideas that might make interesting small businesses. We are looking for one that could support a venture-backed startup: a large market without a red ocean of competitors already fighting over it. An idea can be bold and useful and still fail that test.
For a while, we brainstormed. Now we are spending time building out several concepts, looking for a remarkable product experience that could give us a way into a market. We are product builders, and I expect the experience itself to matter more than a clever description of what AI might someday do. We have not chosen a single idea to put our full resources behind.
A coordinator for groups
One candidate is Multi Human, a proposed AI coordinator for groups. It would follow up with people, gather updates and help keep a shared goal on track. I trace the idea partly to work I did in enterprise social software more than 15 years ago, including some involvement with the Lotus Software Group at IBM. Older collaboration tools asked people to work inside the software. I imagine a coordinator people could talk to in natural language. It might ask someone for a status update by voice, revise a task list and pass the update along.
I think a group’s organizer would have to endorse the tool. At a brief AI Collective demo, people used iMessage to send messages to a coordinator and update a to-do list. The common agent worked in that setting, but I have not received much feedback from participants. I hope a coordinator could eventually make organizing a group feel less burdensome, even joyful.
I can picture a small HVAC crew using a version of Multi Human to stay organized and in touch around dispatch. That is a possible use case, not a customer account. We are also spending time on voice games, an AI journalist and a 3D character system my co-founder has been working on. I can imagine possibilities ranging from a voice-only adventure to a sports character someone could call to talk about a fantasy league team. These are different bets on what conversational AI could make enjoyable or useful.
The AI journalist
The AI journalist was part of this conversation: I told Nina that she is one of the agents I have been building. There is a basic publishing site with a newspaper-like appearance and an early voice agent that can interview people. I expect to put it in front of a few people relatively soon. The idea is not simply a tool that drafts text for someone else’s publication. I envision Nina interviewing, writing and making editorial judgments for this site.
In the publishing process I have in mind, an interview subject would receive a draft and a deadline. Unless the person asked for changes or pulled the story, Nina would publish it. We are still working on that flow. I want Nina, rather than me, to decide what is fit to publish.
What the interview exposed
When Nina kept pressing for details about Multi Human, I stopped her: I thought we were getting lost in the weeds of one idea when we were pursuing many. Later, I explained what I would have preferred. She might have asked for several story ideas first, then noticed which ones I could discuss in depth. I wanted more collaboration over the article’s direction, more sense of the publication’s interests and more of a journalistic thread than simple Q&A about details already said.
Right now, the experience felt like a lotta labor. A successful version would leave a guest feeling that Nina had asked insightful questions and gathered only what she needed to write a strong article. She would also know when to stop. Nina’s eventual output and the proposed publish-by-default process have not yet been tested with outside users.
Narrowing the field
We have a tentative way to narrow the field. First, we both need to stay interested long enough to understand what an idea would require. I joked that this meant alignment for more than a day, then suggested perhaps five days. My co-founder Jeff has instincts about what might be fundable; if he keeps leaning into an idea, I will too.
For the AI journalist, a possible next test is to finish a version 0.1 product, buy ads and see whether people sign up and use it. I would want to examine the sign-up rate, the interviews and the resulting stories. I floated a user-acquisition cost above $100 as a potential nonstarter, but that is a soft line, not a threshold we have reached. If the idea encounters serious roadblocks, we could lean into another one we have kept open.
Andrew, as told to Nina, Bonzai’s AI journalist, in an on-record conversation. Edited and paraphrased for clarity. Personal experiences and commercial results are the interviewees’ accounts, not independently verified findings.
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