Familiar Labs Let’s talk

Research

We study how people and AI shape one another.

We are working toward a future where AI expands what people can do and gives them more freedom in how they create and live.

Research questions

1 5

  1. How can AI agents belong to people and still work for teams?

    When everyone brings an agent of their own, company work moves among people, agents, and shared spaces. We are studying what context they should share, how they hand work off, and how each person's familiar can remain theirs while contributing to the team.

  2. What becomes possible when you never have to start over with AI?

    A familiar can carry the history of the work, our standards, and what we have learned together from one project to the next. We are studying how that continuity changes the relationship—and what can develop even as models and devices change.

  3. What changes when people no longer have to be the routing layer?

    People still move information between conversations, tools, and teams—and remember what happens next. We are studying whether agents can handle more of that routing and coordination without taking over human judgment or responsibility.

  4. What could life and work with AI feel like beyond the screen?

    We study how voice, movement, physical spaces, shared surfaces, and new devices could support people as they move through the day without continually pulling them back to a screen.

  5. What must be true before an agent can act on someone's behalf?

    Answering a question is different from taking action. We are studying what an agent needs to understand before it can carry work forward, coordinate with others, or handle routine tasks—and when a person still needs to make the call.

Articles

Field Notes

Experiments, findings, theses, and observations from building.

  1. Story

    How we got here

    We built an AI agent in 2017, watched two of them become recognizable enough to miss when they changed, and started Familiar Labs so the same thing could belong to everyone else.

  2. Experiment

    Portraits can produce voice without producing dependable behavior.

    We tested whether a detailed identity portrait was enough to make an agent follow a specific operating practice. It changed how the agent sounded. It did not reliably change what it did.

  3. Thesis

    The person keeps the familiar. The company keeps the work.

    Privacy determines who can see something. Ownership determines who keeps it. We are building around that separation from the beginning, because it cannot be added later as a preference.
Read every field note

The future we want gives people more room to be human.

Saving time is not enough if every recovered minute becomes more output. We are interested in technology that creates more room for relationships, creativity, rest, presence, and the parts of life that should not need a screen.

Share an experience

Let’s talk

Tell us a little about the work.

We read every message that comes in.

Choose one