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AI infrastructure & unit economics · independent consulting

Nobody owns a cost they can’t see.

I’m Tim Urista. By day I’m a Senior Cloud Engineer at Apple, working on private cloud for internal AI workloads. Independently, I help teams attribute their AI spend, cut the waste, and ship more with less by delegating real engineering work to agents.

Cash-pay · advisory from $250/hr · fixed-price sprints & audits

Receipts, not slides

Line items from my own stack

verified in git
  • TendForm

    commits co-authored by an agent

    149 / 176

  • TrendVesting

    commits in production since Feb 2024

    1,984

  • TigerMill

    first 8 image-model calls

    ≈ $1.00

  • Roku

    AWS spend attributed per quarter

    $10–12M

Unit that matters

$ per accepted output

Cloud spend attributed

$10–12M/qtr

Cost-attribution pipeline at Roku; co-led the ECS→Kubernetes migration.

Fleet under attribution

~700K servers

Financial attribution where quiet misattribution warps budgets by millions.

Production AI

2.5 years

TrendVesting has run since Feb 2024, on an invoice I pay myself.

Agent co-authored

85%

Of TendForm’s commits: a HIPAA-capable SaaS shipped solo in 11 weeks.

What I do

Spend less on AI. Get more out of it.

Three kinds of work, one discipline: measure the unit that matters, then change the system until the number moves.

New series · Built with Agents

What the commit history actually says

Field notes from shipping real products with AI coding agents: what the commit history says, what it cost, and what I would delegate differently next time.

Full outline (9 parts) →
  1. Part 1

    Sep 13, 2026 · 12 min · TendForm

    TendForm: 176 commits, 85% co-authored by an agent

    I built a HIPAA-capable form builder alone, on my own time, with Claude on 149 of 176 commits. What the agent did, what broke, and where the money goes.

  2. Part 2

    Sep 13, 2026 · 12 min · TrendVesting

    TrendVesting: 2.5 years of production AI, before and after agents

    1,984 commits in three eras. Agents sped up the code, but the bigger change was that measuring got cheap, and the numbers overturned what I believed.

  3. Part 3

    Sep 13, 2026 · 12 min · TigerMill

    TigerMill: an AI content factory in 33 hours

    Two agents built a gated webtoon factory in a weekend. The cheapest lever was not generating, and the metric that matters is the one it doesn't record yet.

Case studies

Costs, at every scale

From quarterly cloud bills in the millions to the dollar a side project spends on image models.

All case studies →

My own practice · 2025–2026

88%

of TrendVesting commits co-authored by an agent, Jul–Sep 2026

How I delegate engineering work to AI agents without losing the plot

Three products shipped mostly by agents, and the operating model that kept quality and cost under control: one lead per repo, gates with attribution, no spend in the toolbelt, and receipts in every commit.

Read case →

TendForm · Jun–Sep 2026

85%

of 176 commits co-authored by an agent

A HIPAA-capable SaaS, shipped solo, priced against its own cost stack

A form builder with multi-form packets, a markdown DSL, a 27-tool MCP server, and a HIPAA tier, built in 11 weeks with an agent co-authoring 85% of commits. The cost decisions mattered as much as the code.

Read case →

TrendVesting · Feb 2024–present

+54.7 pts

stated confidence above the realized win rate

When cheap measurement overturned 2.5 years of beliefs about an AI product

A production AI signals platform I've run since February 2024. Agents made rigorous measurement cheap enough to do, and the numbers said the confidence scores meant nothing. That's the most valuable finding of the whole project.

Read case →

TigerMill · Sep 2026

≈ $1

for the first 8 measured image-model calls

An AI content factory in 33 hours, and the metric that actually matters

A webtoon production pipeline with five gated stages, built by two agents over a weekend. Image generation is cheap per call; what it costs per accepted panel is the number nobody tracks.

Read case →

Try it

AI cost teardown

Describe a workload in a sentence. Get a monthly estimate, a unit cost, and the levers, the way I’d sketch it on a first call.

Estimates from a language model. Useful for orientation, not a quote.

🧾

AI Cost Teardown

Describe an AI or cloud workload in plain English. You'll get a fully-loaded monthly estimate, a per-unit cost, and the highest-leverage ways to cut it. Live, powered by Claude.

Rates

Published prices. Cash-pay.

Invoiced directly, paid by ACH or card. No platforms or agencies in the middle.

Rates & fit check

Advisory hours

$250/hr

2-hour minimum

Executive Cost Briefing

$2,500

90 minutes

Unit Economics Sprint

from $5,000

1 day

AI Cost & Unit Economics Audit

$12k–$25k

1–2 weeks

ML Cost & Reliability Evals

$15k–$30k

2 weeks

AI-native rebuild

Fixed quote

After a Sprint

Cash-pay advisory
from $250/hr

Check fit