Solo UnicornLab
Research library

Building the foundations of AI-native organizations.

Our agenda connects problem discovery, human–AI and agent–agent collaboration, feedback-driven improvement, and distribution. The first notes look at two foundations: coordinating actions and checking evidence.

Agenda updated 08 Oct 20262 research syntheses

Notes

Results 1–2 of 2 notes · newest first

Note 001 · Coordinating work · Research synthesis

How do agents know
what they may do?

When several agents work for one founder, each needs a clear task, permission to act, and a way to check the result. This note explores how an explicit working agreement can help.

In practice. An agent can prepare a release. Who decides it is ready to reach users?

solounicornlab.com/research/workflow-contracts · 03 Oct 2026 · editorial draft · Read about workflow contracts →

Note 002 · Learning from evidence · Research synthesis

How do agents know
what to believe?

To choose a useful problem and improve a product, agents need evidence they can check. This note explores how to connect a claim to its sources, uncertainty, and review.

In practice. A user requests a feature. What evidence makes it worth building?

solounicornlab.com/research/evidence-before-output · 03 Oct 2026 · editorial draft · Read about traceable evidence →

About these notes. They are AI-assisted literature syntheses and proposed experiments, currently marked as editorial drafts. They do not demonstrate the full product lifecycle or report original experimental results.