Read this Before you make your next hire (to build a 100x business)

Strategies we deployed to go down from 25 to 12 hires, without sacrificing work quality.

Strategies we deployed to go down from 25 to 12 hires (without sacrificing work quality)

Few days ago I talked to my dad, and he asked me:

“How do you make AI do the work for you?”

My family and friends know that I spend too much time on AI as it is. And that I’ve been making it do things. Spent to much time on it, that it is an integral part of my muscle memory at this point.

This led to many breakthroughs and revelations on how to create the bionic version of you, that outproduces 100x compared to people that are not working with the AI.

As a result, we’ve managed to cut down our team from 25 people down to 12. This dramatically increased our margins, and replaced people who were doing monotonous tasks that didn’t require thinking, helped us retain people that have been activating their brain cells and deployed real intelligence in tandem with the artificial one.

We live in the era where web developers and tech employees lived through massive layoffs season. Rightfully so. Many people were just getting by, and now AI replaced their roles completely.

But as the dust settles, we are witnessing new demand.

Harvard Business School researchers went through nearly every US job vacancy from 2019 to March 2025. After ChatGPT launched, postings for roles built on structured, repetitive tasks fell 13%. Postings for analytical, technical and creative work grew 20%.

The market didn’t shrink. It moved. Companies are going to hire people that are Agent Native, rather than people who work the old school way.

People who embraced the gap and studied are reaping early adopter rewards. The window where that is still an edge is closing, and it is closing this year.

When someone hops on an interview and they aren’t able to demonstrate what they can do with Claude or Codex, why would companies even bother hiring them?

I need you to understand what is happening right now

Claude Code. A data pipeline. A data warehouse. A server. A GitHub repo. A folder of skill files.

That is the stack. One person running it does in a day what a Fortune 500 marketing department does in a year.

This is one day of output. Not a quarter. A day.

• 40 Facebook ads

• 30 Google Ads ad groups

• 100 landing pages

• 3 guest blog posts for backlinks

• 4 podcast bookings

• 5 help desk articles

• 2 vlog videos edited

• 25 tweets scheduled across 3 accounts

• 2 pieces of scripting software written and given away as LinkedIn lead magnets

One person. One day.

Now go price it.

Start with one line of that list. At agency rates a single landing page runs $500 to $3,000. So 100 landing pages is somewhere between $50,000 and $300,000 of billable work. Shipped in a day.

The rest of the list is a department. A media buyer averages $66,414. A video editor $65,728. A social media specialist sits around $53,000. Robert Half puts a marketing manager at $108,000 mid range. Add a copywriter and a developer and you are north of $400,000 in salary alone, before benefits, before software, before the hours you spend managing any of them.

Rent it instead and Clutch puts digital marketing retainers between $5,000 and $50,000 a month across more than 100,000 firms.

Here is the number that should actually bother you. The average time to hire for a marketing role is around 50 days, and staffing a four person team takes six to eight months. Six months of job posts, interviews and onboarding, against a stack that ships everything on that list before dinner.

I don’t think you understand what is happening in marketing engineering right now.

This is not coming. It shipped. Somebody in your market is already running this stack while you are sitting down to write a job post.

Big question remains, why do you want to hire in the first place?

If you sat down to see what you need your employee to do, you’ll realize that in that same language you can instruct AI to do this job for you.

Why people hire in the first place?

So many business owners will nuke their margin and sacrifice their profit to pointless payroll.

The salary is never the cost. Talent practitioners put the true cost of a hire at three to four times the salary once you count recruiting, onboarding, management attention and the months before the person produces anything. A $60,000 role can run you $180,000 or more.

I am not saying that hiring is bad, I am paying a 12 people team at the time of this writing. But I am saying that today, you need to rethink your entire hiring habits.

Before you hire, you need to prototype your process with the AI. If it is not documented, it is not worth doing at all. And by the time you document it, you can have this process fully functional.

Why is process documentation hard?

Most business owners don’t like to think. Adding AI to the thinking process doesn’t make it simpler, it makes it more difficult. Solving real problems requires real intelligence to run the artificial one.

This is where most companies die. MIT’s State of AI in Business 2025 found that 95% of enterprise AI pilots deliver no measurable impact on the P&L. The cause wasn’t model quality. It was a learning gap: generic tools work for individuals because they are flexible, and stall inside companies because they never learn the actual workflow.

You cannot hand a model a process that only lives inside someone’s head. That is the whole game.

In a world of instant gratification, even business owners are stuck on the dopamine hunt. This results in short attention spans, that are making them incapable of paying attention.

Paying attention is increasingly hard in a world that is starved of focus…

Strategies we deployed to go down from 25 to 12 hires (without sacrificing work quality)

None of this happened in one move. Five things did the work.

1. We executed the job description before we published the job post.

Every open role got documented as a task list first. Not responsibilities. Actual tasks, in order, with inputs and outputs.

2. We turned each task into a prompt.

If the task could be described, it could be prompted. Most could. The ones that couldn’t were the ones worth paying a human for.

3. We ran the prompt for a week before deciding.

A week of real output tells you more than three interviews. 80% of the roles never got posted.

4. We kept the people who could run the machine.

The cuts weren’t about seniority. They were about who activated their brain cells and who was executing motions. The people who could think alongside a model got more scope, not less.

5. We made every process live in a document.

If it isn’t documented, it isn’t worth doing. That single rule is what let 12 people absorb the output of 25 without quality dropping, because nothing lived only in someone’s head.

The process that makes it simple

Building agents is a mindset shift. The problem is not just learning the tech, which believe it or not, is the easy part. AI does most of the work anyway.

The thinking part is where most people trip up. Your usual convergent thinking doesn’t help. Your lack of experience doesn’t help. However, education of the future is here…

That process has a name. Agentic Business Sprint.

It is the compendium of prompts and the documentation system we used to go from 25 people to 12 without sacrificing work quality. You bring the role you were about to hire for. You leave with the process documented, prompted and running, so you know what a human still needs to own before you put anyone on payroll.

Build the business that runs on artificial intelligence and automation, instead of running on payroll.

Launches in 4 weeks, or sooner if the remaining 19 seats sell before then.

Claim your seat in the Agentic Business Sprint

- Brian Decoded

P.S. Before you post that job, run the math. The role costs you three to four times its salary and you wait months to find out whether you were right. The Agentic Business Sprint tells you inside a week, for a fraction of one month of that payroll. 19 seats left. They go fast.