This is a practical walkthrough of how to price ai services — no theory, no hype. Just the setup, the tools, and the exact steps a solo operator can follow this weekend.
What you'll build
By the end of this guide, you'll have a working setup that handles how to price ai services — not a toy demo, an actual operational tool. The whole thing takes about 90 minutes if you follow the steps in order.
What you'll need
- A reasoning home base: Claude Pro ($20/mo) or ChatGPT Plus ($20/mo). Either works. Claude is slightly better for structured writing; ChatGPT for general breadth.
- A no-code automation platform: Make.com (recommended for solopreneurs — clean UI, generous free tier, ~$9/mo Pro tier when you outgrow free).
- Your existing tools: Gmail or Outlook, Google Calendar, whatever CRM or task tracker you use. Everything connects.
- 60-90 minutes: uninterrupted time.
Step 1 — Write your Voice Doc first
Before you build any agent that produces output for humans, spend 90 minutes writing a Voice Doc. It's a plain document with three sections: how you write, how you don't write, and 6-8 examples showing the difference.
Every agent that produces text — emails, proposals, content — references this doc. Without it, everything sounds like generic AI. With it, output sounds like you. This step alone separates good agents from useful ones.
Step 2 — Pick your trigger
Every agent starts with a trigger. Common ones for solo businesses:
- A new email lands in a specific label or folder
- A form on your site gets submitted
- A Stripe charge succeeds
- A recurring schedule fires (every weekday at 7am)
- A new row appears in a spreadsheet or Airtable
Pick one that already exists in your business. Don't invent new triggers.
Step 3 — Design the middle
The middle of an agent is where reasoning happens. In Make.com, this means chaining together:
- Read step — gather context (email body, form fields, calendar events)
- Reason step — send context + instructions to Claude or GPT via API
- Act step — do something with the result (send an email draft, update a record, log to a database)
Your first agent should have exactly one reason step. Chain complexity later; single-step first.
Step 4 — Test with real data
Feed the agent five real scenarios from your last two weeks of work. Watch what it produces. Adjust the prompt until 4 out of 5 outputs are usable with light editing. Perfect is the enemy of shipped.
Step 5 — Ship it, then check daily for a week
Turn the automation on. Review every output for the first seven days — not because it's fragile, but because you'll catch edge cases you didn't imagine. After a week, drop to a weekly spot check.
The mental model to keep
Agents are not magic. They're small, boring processes that do consistent work while you sleep. The value isn't the sophistication of any one agent — it's the compounding of five or ten of them running reliably. Start with one. Ship it. Build the next.
Keep reading
The complete playbook
Everything above is one chapter of a bigger system. The Solo AI Playbook is the 80-page operator's manual covering all four layers of a one-person business — Attention, Lead, Sale, Delivery — with 12 agent blueprints and 50+ prompts.