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How to Get Your First 10 Customers as a Solo Founder, With AI Doing the Grunt Work

PromptWorks — Fri, 25 Sep 2026 14:22:02 +0000

"How did you actually get your first 10 customers?" gets asked in founder communities over and over. It has its own threads in r/SaaS and r/FounderFAQs, for example. The answers are remarkably consistent, and none of them are "I ran ads" or "I went viral."

This post turns those answers into a plan you can start today, and shows where AI (ChatGPT, Claude, or similar) can save you hours without writing the kind of message people ignore.

What the people who did it say

Look at how founders describe their first customers and the same few sources keep coming up:

People you already know, and their introductions. Kevan Lee wrote that his agency Bonfire's first ten clients came from four friends, four referrals, and two former colleagues (Around the Bonfire #506).
Targeted strangers. The same issue quotes Lenny Rachitsky's review of how more than 100 consumer companies found early users. It lists seven levers, starting with "reach out to friends and colleagues" and "reach out to targeted strangers." Kevan's observation: five of the seven levers come down to reaching out to people.
People already describing the problem in public. In r/SaaS's "How did you actually get your first 10 customers?" thread, founders describe answering people who were publicly asking for exactly what they'd built, plus narrow ICP, founder-led outreach, and high-touch onboarding.

For customers one through ten, conversations beat channels. Scalable marketing comes later, once you know what those ten people had in common.

Step 1: Narrow until you can search for it

"Small businesses" isn't a target. "Two-person Shopify stores where the founder still answers support emails personally" is one, because you can see it: the founder's name on replies to reviews, a Gmail address on the contact page, a job ad for a part-time support assistant.

That's the test for a good early ICP: can you name the public signals that show someone has the problem right now? If you can't, you'll end up messaging people at random.

Free prompt: ICP card

My offer: [WHAT YOU SELL + WHO IT'S FOR + PRICE]
Candidate customer groups: [3–5 GROUPS]
Groups I already have access to: [NETWORK / COMMUNITIES / PAST JOBS]

Score each group 1–5 on: urgent pain now; already spending time or money on a workaround;
I can find 50 of them this week; I can tell from public info that they have the problem.
Show a table, pick ONE winner, then write an ICP card:
- Who (max 15 words)
- 5 trigger events I can SEE publicly (posts, job ads, reviews, launches, tool changes)
- Current workaround and its cost — mark guesses [assumption]
- Specific places to find 50 of them this week
- 3 disqualifiers

Check the "specific places" line critically. If it says "LinkedIn," ask again: "Name exact searches, groups, or directories."

Step 2: Start warm, even if it feels like cheating

Your first conversations should be with people who'll open your message: former colleagues, past clients, people in communities you've actually taken part in. They aren't necessarily buyers. They're the fastest route to honest feedback and to introductions, which is where a lot of early customers come from.

Make introductions easy to give. Write a two-sentence blurb that someone can forward without editing: who you help, the problem, and what you're offering. Then ask for one specific type of person, not "anyone who might need this."

Step 3: Build a list where every row has a reason

Aim for 30–50 people. For each one, record an observed detail: something true and specific you can mention. It could be a post, a launch, a review, a job ad. No detail, no message. This one rule does more for reply rates than anything you can do to the wording.

AI helps most at this stage. Paste a prospect's public info and have the model pull out the relevant detail, score the fit, and suggest an opening line. Keep it grounded: tell it to quote only from what you pasted and to say "skip" when the fit is weak.

Step 4: Write short, specific messages, then follow up

Three rules cover most of it:

Open with the detail you observed, not your name or a pleasantry.
One idea, one question. "Is this on your radar?" beats "Can we book 30 minutes?"
No invented proof. If you don't have case studies yet, don't imply them. Offer something small and free instead, like a five-point teardown or a redraft of one page.

Free prompt: the draft critic

Run this on every template before you use it widely.

Act as a skeptical [THEIR ROLE] who gets 20 cold messages a day.
Here is my draft:
[PASTE DRAFT]

1. Would you reply? Yes/no + the honest reason in one sentence.
2. Line by line: keep / cut / rewrite, and why.
3. Flag any claim that sounds invented or unverifiable.
4. Rewrite with 20–30% fewer words, same voice, same facts. Do not add facts.

Plan two follow-ups, and make each one add something new: a useful resource, a different angle, or a simpler ask. Then stop. (The cold outreach prompt guide has copy-paste prompts for the first email and follow-ups.)

Step 5: Make the first "yes" small

Your first deal should be easy to agree to: a paid pilot, a fixed-scope first project, or a single product. Put scope, price, timeline, and how to say yes on one screen. When it's delivered, ask for introductions to one specific type of person. That's how one customer becomes three.

Free prompt: the referral ask

What I delivered: [WHAT YOU DID]
Real result they saw (leave blank if none): [RESULT]
Who I'm looking for: [ICP IN ONE SENTENCE]

Write:
1. A referral ask (max 70 words) naming the exact type of person I want — not "anyone."
2. A 2–3 sentence blurb they can forward as-is.
Do not claim results that aren't in "Real result."

A daily rhythm you can sustain

About 45–60 minutes a day:

10 min: answer every reply the same day.
20 min: research five new prospects and log them with their observed detail.
15 min: send five personal first messages.
5 min: send the follow-ups that are due.
5 min: update your tracker and write one sentence about what you learned.

At five a day across two working weeks, you'll have started around 50 real conversations. How many turn into customers depends on your offer and your list, and nobody can honestly promise you a number. But you'll know far more than you would after two weeks of polishing a landing page nobody visits.

Where AI helps, and where it doesn't

Good uses: turning messy notes into a clear offer, pulling your buyers' own words out of reviews and forum posts, research briefs, first drafts, critiquing your drafts, and sorting replies.

Bad uses: mass-generating "personalized" emails from thin data, inventing proof, and replacing the conversations themselves. Your first ten customers buy partly because a real person paid attention to their problem, so keep that part.

The one-line version

Pick a group narrow enough to search for, start with people who know you, message people with a visible reason, keep it short and honest, follow up twice, and make the first yes small.

Originally published as the full guide: How to Get Your First 10 Customers as a Solo Founder.

Give ChatGPT and Claude Persistent Context with 3 Markdown Files

PromptWorks — Fri, 25 Sep 2026 14:13:50 +0000

If you use ChatGPT or Claude for real work, you've probably typed some version of this dozens of times:

"I'm building a tool for freelancers that... our tone is friendly but not cheesy... please don't use buzzwords..."

Every new chat starts from zero. The model doesn't know your product, your audience, or the things you hate seeing in its output. So you either re-explain everything (slow) or skip it and get generic results (worse).

The fix is boring and effective: keep your context in three small Markdown files and paste or attach them at the start of a session.

product.md — what you're building, for whom, and why
voice.md — how you sound
rules.md — hard constraints and output format

Here's how to write each one, with templates you can copy right now.

Why Markdown files instead of "memory" features?

Built-in memory and custom instructions are useful, but they have limits:

Portability. A file works in ChatGPT, Claude, an API script, or your code editor's AI assistant. Switching tools costs you nothing.
Version control. Put the files in a Git repo or a notes folder and you can see how your positioning changed over time.
Precision. You decide exactly what the model sees. There's no guessing about what it "remembered" from a chat three weeks ago.
Scope. You can keep different sets for different projects without them bleeding into each other.

Markdown specifically works well because models handle headings and bullet lists reliably, and the files stay readable for you too.

File 1: `product.md`

This is the single source of truth about what you sell. Keep it short — one screen is plenty. If it's too long, the important parts get diluted.

# Product Context

## One-liner
InvoiceSnap turns a finished project into a sendable invoice in under a minute.

## Who it's for
- Solo freelancers (designers, developers, copywriters)
- Billing 2–10 clients per month
- Currently using spreadsheets or Word templates

## Problem
Invoicing is tedious, gets postponed, and delays getting paid.

## What it does
- Creates invoices from a short project summary
- Remembers client details and payment terms
- Exports PDF and sends by email

## What it does NOT do
- No accounting, tax filing, or payroll
- No team features

## Pricing
(example) Single plan, monthly.

## Current focus
Getting the first 20 paying users. Priority: landing page copy and cold outreach.

Two sections punch above their weight here:

"What it does NOT do" stops the model from inventing features in your marketing copy.
"Current focus" tells the model what matters this week, so its suggestions stay relevant. Update this line often.

File 2: `voice.md`

Without guidance, models default to a polished, slightly overexcited corporate voice. voice.md pulls them toward how you actually write.

# Voice & Tone

## In three words
Direct. Friendly. Practical.

## Do
- Write like you're explaining to a smart friend
- Short sentences. Short paragraphs.
- Use concrete examples over abstract claims
- Address the reader as "you"

## Don't
- No hype words: "revolutionary", "game-changing", "unlock", "supercharge"
- No exclamation marks in headlines
- No emojis unless explicitly asked
- Don't open with "In today's fast-paced world..."

## Sample of my writing
> Invoicing shouldn't take longer than the last task on the project.
> Paste what you did, check the numbers, hit send. That's it.

The sample paragraph is the most important part. Models imitate examples far better than they follow adjectives. Paste two or three sentences you've written and liked — an email, a tweet, a landing page line.

File 3: `rules.md`

This is where you put non-negotiables: facts the model must not invent, and how you want output formatted.

# Rules

## Accuracy
- Never invent statistics, testimonials, customer counts, or partnerships.
- If a number is needed and I haven't given one, write [NUMBER] as a placeholder.
- Mark any sample figures clearly as "(example)".
- If you're unsure about a fact, say so instead of guessing.

## Output
- Default language: US English
- Use Markdown headings and bullet lists
- Give 3 variations when I ask for copy (headlines, subject lines, CTAs)
- Keep emails under 120 words unless told otherwise

## Process
- If my request is ambiguous, ask at most 2 clarifying questions, then proceed.
- When I say "tighten", cut length by ~30% without losing meaning.

The accuracy rules alone are worth the effort. The placeholder convention ([NUMBER]) means you can scan output and immediately see what needs real data, instead of discovering a made-up "93% of freelancers" in something you already sent.

The workflow: 5 minutes to set up, seconds to reuse

1. Create the files once. Put them in a folder like ai-context/. Fill in the templates above with your own details. Resist the urge to write an essay; aim for under 300 words per file.

2. Start each session with a context message. In ChatGPT or Claude, attach the three files (or paste them) with a short opener:

Here is context about my product, my voice, and my rules.
Read all three files. Don't reply with a summary — just say "Ready."
Then wait for my first task.

The "just say Ready" line saves you from a long recap you'll never read.

3. Give a specific task.

Write a cold outreach email to a freelance designer who
currently invoices with a Google Docs template.
Follow voice.md and rules.md.

4. Iterate, then feed learnings back. If you correct the model the same way twice ("stop saying 'streamline'"), that correction belongs in voice.md or rules.md. Your files get better every week.

5. Use project features if you have them. ChatGPT Projects and Claude Projects let you attach files once so every chat in that project starts with them. The files stay the same — only the delivery gets easier.

Tips from using this setup

Keep files small. A tight 200-word product.md beats a 2,000-word one. If a section doesn't change the output, delete it.
Separate stable from changing info. Your product description changes rarely; "Current focus" changes weekly. Put the volatile stuff at the bottom so it's easy to find and edit.
One set per project. Client work, your side project, and your newsletter each deserve their own three files.
Test with a known task. After editing a file, rerun a task you've done before (say, "write 3 headlines") and compare. That's the quickest way to see whether a change helped.
Don't store secrets. No API keys, passwords, or private client data in files you paste into a chat.

Wrapping up

Persistent context isn't a feature you need to wait for. Three Markdown files — what you sell, how you sound, and what the model must never do — make ChatGPT and Claude noticeably more useful from the first message. Copy the templates above, spend five minutes filling them in, and use them on your next task.

If you'd rather start from ready-made templates, PromptWorks has an AI Starter for Solo Founders pack: 40 prompts with usage context, a short guide, and checklists, as Markdown files.