What We Learned From Matchwise 1.0

Matchwise was born on May 29th at a Light DAO event at AGI House in SF. It was derived from the Talking Books app which used AI guided conversations to help people with loneliness, parenting skills, and even dating.

The idea of Matchwise was to use an AI guided conversation to learn about a person (e.g. their company elevator, significant achievements, what they are looking for in a co-founder), then summarize those learnings, and semantically match them with others.

We kicked off the product as Magic Match, and the support of Gina Levy and Doug Campbell. In August we changed the name to Matchwise and Sophie Vu joined to help bring the idea to market.

Over the next few months the product evolved with AI generated synergies, strategies, and introductions. We also developed a sophisticated guided conversation prompting engine, created over 200 agents, and tested thousands of conversations.

From September through November we continued to evolve the product, pitch at events, and tested with Inception Studio. Our goal was for Matchwise to be embraced by event organizers, and become part of every networking event experience.

By November it was clear our formula was off. I had a seminal meeting with Ronak Shah where he explained how we were misaligned with the event organizers. I spent December stepping back to re-evaluate our efforts and figuring out next steps.

Here are some key take-aways:

• From the event attendee's perspective, business and social networking in-real-life (IRL) is broken.
• People have come to accept serendipity as a strategy. Most walk around and start random conversations hoping to find the right people. Few people research the attendee list beforehand (if it is even available)
• Event organizers are busy with many things which take priority over providing personalized introductions between attendees.
• Event organizers feel that bringing people into the same room is enough for networking, and it is up to the attendees to figure the rest out.
• Attendees don't want to spend several minutes talking to an AI agent to prepare their matching profile before an event.

In short, there wasn't demand from the event organizer side which made our cold-start problem very difficult.

So, what is next?

In November Gangesh Pathak hosted an event where Jeremiah Owyang was advocating agentic AI. In January I started exploring how agents could work to accomplish the goals of Matchwise.

After taking a step back from a centralized Matchwise service, and dusting off some decentralized identity and authentication code from the blockchain days (no blockchain here, just the identity and authentication pieces), I have started coding up an Agentic Profile system. More to come...