Matt Boone
Alice · case study

A second brain that knows what it is allowed to decide.

My network lived in a LinkedIn export, a phone and sixty days of email: 2,264 relationships I could not hold in my head. In eight days, with AI as the build partner, I built Alice. It remembers every conversation, notices who has gone quiet, and each morning tells me where the next hour is best spent and why. Building it was the easy part. The real design work was deciding what the AI may decide.

2,264relationships consolidated from three sources
1,500+proposed changes, each decided by a person
8 daysfrom empty file to running

Four decisions behind it

A second brain fails when it depends on someone typing into it. This one works because of four decisions made on purpose.

  1. Capture what already happens. Alice reads mail, calendar and meeting notes. Nobody types into it, because a second brain that depends on data entry goes stale within a month.
  2. Write the win down as structure. The objective lives in the system as fields, so Alice can find what the network is missing. It surfaced 57 people I would not have thought to look for.
  3. Draw the judgment line. The model sorts information into fixed categories. Arithmetic in the database ranks. I approve every change on a card showing before, after and the evidence.
  4. Earn every control. Each check exists because of a specific failure and retires when that failure can no longer happen. Changes to the AI's own instructions are tested against a fixed case set and ship only if they perform no worse than what is live.
    Per change
    tests, schema versus every consumer, adversarial review
    Every 48 hours, unattended
    drift, access, controlled values, job health
    Monthly
    the whole system

AI classifies. Arithmetic decides. A person approves.

What transfers to a company

Most AI rollouts automate before anyone has decided who decides, and the gap between growth and infrastructure widens. The sequence that worked here is the one I would run inside a finance organization: start from the decision that is not getting made, write the objective down, decide where judgment lives, route every change through one queue, and add controls only when a failure earns them. Alice is the smallest system I have applied it to, which is why the whole thing is visible at once.

What it looks like

The dashboard is the only surface I touch. Names are blurred; everything else is the live system.

Alice dashboard home: counts for overdue, due soon, needs action and all contacts, above a ranked list where each contact shows status, program tag, last touch and the next action owed.
The morning view: who is overdue, why, and what is owed next.
A single contact card showing status chips, the six scoring components with a confidence rating, flags, last touch, contact details, and a suggested outreach message with buttons to copy it, draft it in Gmail, or record how it was sent.
One contact. Every scoring component is visible, and the draft below it is written in my voice.

Alice has been hardened and extended every day since launch. Next, it extends from one search to every relationship across the businesses I help run. The full design, including the architecture, what I refused to build and the correction that mattered most, is a conversation I am glad to have.

If you are building a second brain for yourself or your team, let's talk →

Or tell me which decision in your company is being made badly: msandfordboone@gmail.com

Companies outgrow their decision systems before they outgrow their markets. Alice is what it looks like to build the decision system first.Matthew Boone, matthewboone.com