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Approach

Spend less. Ship more. Keep the receipts.

AI made building cheap and made measuring cheap. Most teams took the first gift and skipped the second. My work is both: delegate the build to agents with guardrails, and measure what it really costs per thing you actually ship.

Principles

Six rules I use on my own products first

The delegation stack

Who does what

The same structure runs TendForm, TrendVesting, TigerMill, and this site. For a client engagement it gets scoped down: agents touch only the repositories and commands we agree on, with no production credentials and no ability to spend.

Read the playbook
  1. 1

    You

    Set the goal, the budget, and what “accepted” means.

  2. 2

    Lead agent

    One persistent lead per repository, in its own worktree, with notes that survive restarts.

  3. 3

    Workers

    Short-lived agents for research, drafting, and implementation, each scoped to specific files.

  4. 4

    Gates

    Typecheck, build, verified-live checks, screenshot review, and human sign-off on anything subjective or paid.

  5. 5

    CI/CD

    Every commit builds; main deploys. Commit bodies carry the reasoning and the measurements.

Why me

Three scales, one discipline

I started as a middle-school teacher who built a grammar game because twelve-year-olds told me the lesson was boring. That instinct, make the complex thing legible to the people who have to live with it, is still the job. I’ve done it for a $10–12M-a-quarter AWS bill at Roku, across a ~700K-server fleet at Apple, and dollar by dollar on products whose invoices I pay myself.

Every AI system has two architectures: the one in the diagram, and the one on the invoice.

Start with one system

The Unit Economics Sprint takes one AI workload and gives you a defensible cost per unit and the top three levers, in a day.

from $5,000

Rates & fit check

Cash-pay advisory
from $250/hr

Check fit