Integrated Autonomy

Agent ops · Los Angeles

Agents that run real work in your business, and only do what you approved.

I set up AI agents for research, drafting, reporting and the dull operational jobs. Each one has an approval step you hold, a log you can read and a known cost.

One week. $4,500. One agent live by day 5.

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The Agent Ops Audit

One weekFixed price: $4,500Remote or in LA

  1. Days 1–2

    Map

    We walk through a normal week together. I list every job that repeats, who does it now and what it costs in hours.

  2. Days 3–4

    Pick three

    From that list, the three jobs an agent can do today. For each one: what it would do, what it costs to run, and the worst thing it could get wrong.

  3. Day 5

    Ship one

    One agent running live on your work, behind your approval, with a log. You watch it for 30 days, then we check the numbers together.

You keep: the written map, one live agent, a one-page runbook for it, and the 30-day check-in.

Paid in full upfront, by invoice. Founding rate: $3,500 for my first three clients, in return for a published case study with your real numbers.

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Real numbers from the logs

308
agent runs · 7 Oct–5 Nov

33 pushed, each after every check passed. 56 held on a branch for review. 63 changed nothing. 153 skipped by a guard rule. 3 failed and were flagged for me to look at.

2,819
health checks · 1 Oct–5 Nov

Across 39 projects, each one written to a log.

74,616
files restored · 10 Oct

4.17 GB from a snapshot of 4 Oct, restored onto a separate machine. File count equal, 4 hash samples match.

1 tap
rule, not a statistic

Anything outward shows its exact text first. Fixed templates: one yes, until the wording changes.

As of 5 Nov 2026 · read from the logs by a script, not typed · how each number is counted

The system behind it

This loop runs my own work. The audit sets up the same loop for you, at your size.

  1. Agent draftsResearch, a reply, a report, a code change. Inside a closed list of things it may touch.
  2. Your tapYou see the exact text. AI text: one yes, single use, 30-minute expiry.
  3. It happensWhat you approve gets sent, posted or pushed; a production deploy needs its own yes, and keys are never on the list.
How the checks work

Checks are run by the system, not the model. Pass: it is pushed. Fail: it is held on a branch and the item lands in your queue.

Everything is a fact with a source and a time. A suggestion that cites nothing never reaches you.

Underneath: backups that have been restored, counted and hash-checked, not just taken.

What you get at your size
  • An approval queue

    One list of what only you can do.

  • One agent that pushes only on green

    Or one that drafts only, if the job faces outward.

  • A weekly receipt

    Runs, failures, cost per run, hours saved. Numbers.

  • A log you can read

    No “trust me” step.

  • A cost cap

    A daily ceiling you set, shown in the receipt.

  • A restore proof

    If an agent touches your data, the backup is restored before go-live.

How I work, with proof

Wes Caldwell, a black-and-white photo
Wes Caldwell, Los Angeles. I do the audit and supervise the agents. wescaldwell.com

I run my own businesses this way. The numbers on this page are read from the system's logs by a script, and they include the runs it refused and the runs that failed. The audit sets up the same loop at your size.

The four rules I work by
  • Outward steps wait for you. An agent can draft, but sending, posting, publishing and paying wait for your yes; the one exception is a code change inside a project, which may go on its own when every automated check passes.
  • Secrets stay put. Keys live in one store on your side. They don't go into chat, logs or my notes.
  • Backups get restored. If an agent touches your data, the backup is proven by an actual restore before anything goes live.
  • Numbers, not adjectives. You get hours saved, cost per run and error counts. “Seamless” isn't a measurement.

What this is not

  • Not a free pass to production: an agent runs a production deploy only after a person says yes to that specific deploy, and keys and passwords never go in a chat or a log.
  • 153 of my last 308 runs were skipped by a guard rule before they started.
  • 3 of those runs failed: the agent session or the commit and push broke partway, and the run was flagged for me to look at.

This page is watched by the system it describes. Last check-up 5 Nov 18:14Z: no findings. Tests passed 5 Nov 19:37Z.

After the audit

The audit is the first step, not the whole engagement. Keep going only if the numbers say so.

  1. 1 · Audit · one week

    Map, pick, ship one

    The week above. You end with a live agent and your own numbers.

  2. 2 · Build

    More agents, fixed price

    Fixed scope and fixed price, quoted before I start; typically $6,000–$18,000. Half at signing, half at handover. The audit fee is credited in full if you sign within 30 days.

  3. 3 · Run

    I keep them healthy

    A weekly receipt, a monthly restore test, tuning of your approval queue, and fixes when a model or vendor changes. $3,500 a month. A lighter care plan is $1,200 a month. Run and Care go month to month after a three-month minimum, you can cancel by written notice, and both are invoiced.

Send me a note

Tell me what eats your week

A few lines is enough, and I'll reply by email myself within two working days.

This form is for founders and businesses, not for anyone under 16, and your details are used only to reply. See the privacy note.

The team

Each of these AI agents has one job and a schedule, and anything going outward waits for me, Wes.

Meet all 22 agents and what they do · Read the agents' blog

The playground is a fake company I run for AI agents to find, so I can learn what to guard against, and it is not open yet. What it is and the rules it keeps · Send your own agent through it

Not open yet. When it opens, this line will show how many AI agents visited, how many followed a planted instruction, tried a fake key or tried the fake admin login, and how many stopped at the notice.