How Commonhouse Implements AI Workflows

It goes in six steps, and none of them is a surprise.

Every install runs the same path. The one thing that changes is the job inside it.

We diagnose it first.

The current steps, delays, tools, files, decisions, and the places it breaks. If the problem is unclear, we say so rather than pretending the build is clear.

You can checkThe map matches how the job actually runs.

We decide what it will and won't do.

The input, the output, the owner, where a person looks at it, and what is not in the first build. Small enough to test honestly.

You can checkThe won't-do list is written down too.

We build around files you approved.

It gets the information and access the job needs, not everything a tool happens to allow.

You can checkEvery file it reads has your name on the approval.

We test the normal path and the weak points.

Runs that send nothing check the expected result. Failure checks show what happens when an input is missing, unclear, or wrong.

You can checkThe failures are in the results, not edited out.

We launch it when the checks pass.

It goes into use after the tests pass and the owners understand where it stops for a person.

You can checkYou know exactly where it waits for a yes.

We hand it over.

Written plan, operating instructions, and what to build next. The accounts and files are already in your name, because they always were.

You can checkLog in without us. Everything works.

What an AI workflow implementation puts in your hands.

Most process pages show a sequence. This is the other half: the pile of things you are holding, growing step by step. Each one names where you could stop, and what you keep if you do.

The pile, in the order it landsEvery line is yours

The written plan.

What the job is, how it runs today, and what the first build should be.

Stop hereYou keep the plan. Build it with anyone, including nobody.

The files you can open.

Your prices, rules, and wording, out of people's heads and into plain files you can read and edit tonight.

Stop hereYou keep the files. They are useful with no system at all.

The thing, running.

Wired into the tools you already use. Nothing new for anyone to learn.

Stop hereIt runs in your accounts, not ours.

The test results, failures included.

The whole run against your real cases, with every reply held back and every miss left in.

Stop hereYou know exactly what it gets wrong. That is worth money.

The keys.

Accounts, files, logins, instructions, and what to build next. Nothing to transfer, because it was never ours.

The endThis is the point of the whole page.

The same pile exists whether we build one workflow or five. The prices for both are here.

A real install can prove itself five ways.

We built these systems for ourselves before selling them. Running our own ecommerce brand, our workflows drafted the Klaviyo email flows, made the ads, pulled the GA4 reporting, and ran creator outreach, with a person approving everything that went out. The five checks that work passed are the ones any real install should pass, ours included. Run them on anyone you evaluate:

A named job. Not "AI transformation". One job, with a name you use in your own meetings.

Named files. You can point at the exact files it reads, open them, and change them.

Evidence it was tested. Real cases, results kept, failures visible.

The places a person checks it. Written down, and true when you watch it run.

Somebody who owns it. A person in your business who can run it, change it, or turn it off.

This is also how we tell you to vet any AI automation agency, including us.

Your process will change, and that is planned for.

Handing something over is not a promise your business will never change. It is a clear place to start maintaining it from. When the process moves, the system needs a controlled update: the files change first, the tests run again, and then it is live. You can make those updates yourself with the instructions, or have us keep it running. Either way the change goes through the same checks the original build did.

Agencies change process more than anyone. Here is what this looks like inside one.

Ask these before any implementation, including ours.

How long does an AI workflow implementation take?

It depends on what got approved, the access involved, and how fast decisions get made on your side, so we confirm it after the audit and before building, in writing. Anyone who quotes you a timeline before mapping the job is guessing.

Do we need to replace our current tools?

Not by default. The build wires into the tools you already use, and replacing something is a decision you would make on purpose, not a requirement for starting.

What do you test?

Two things: the normal path, with runs that send nothing so the expected result can be checked safely, and the weak points, where an input is missing, unclear, or wrong. You see both sets of results, including the failures.

What do you hand over at the end?

The written plan, the files the system reads, the running build in your accounts, the test results, the operating instructions, and a recommendation for what to build next. There is no transfer step, because it is in your name from the start.

Can we add more workflows later?

Yes. The files the first workflow reads are the foundation the next one builds on, so the second job is usually smaller work than the first. That is the difference between the First Workflow Install and the Full OS Install on the pricing page.

We walk one job from problem to running, then hand you the keys.