You are an expert resume writer. Create a professional resume for:

Name: {name}

Role: {role}

Experience: {experience}

Skills: {skills}

Rules:

• Use action verbs with metrics
• One page maximum
• ATS-friendly format
• Modern but not flashy
• Include a summary tailored to the role

Output as markdown.

Hour 8-16: The Launch

I posted on:

• My Twitter (2,400 followers)
• Hacker News "Show HN"
• Reddit r/webdev
• Indie Hackers

Not life-changing. But proof that people wanted it.

Hour 16-24: The Iteration

Based on user feedback, I built three features in 8 hours:

1. Real-Time Preview

Users wanted to see the resume as they typed. I added a split-screen layout with a live preview updating every 2 seconds.

2. Multiple Templates

Turns out "modern but not flashy" means different things to different people. I added 3 templates:

• Minimal: Clean, single column, lots of white space
• Professional: Two column, skills sidebar, traditional feel
• Creative: Color accents, modern typography (for design roles)

3. ATS Score

This was the feature nobody asked for but everyone shared. After generating a resume, the tool gives an "ATS Score" (0-100) based on:

• Keyword density vs. job description
• Formatting compatibility
• Section completeness
• Length optimization

1. User pastes a job description
2. Tool extracts keywords using simple TF-IDF
3. Compares against resume content
4. Generates a score + specific suggestions

Hour 24-48: The Reality Check

By hour 30, the site had 400 signups and 12 paid users. $60 total.

Here is what I learned:

What Worked

1. Fast iteration. I shipped 6 updates in 48 hours. Users noticed and appreciated it.
2. Public building. Tweeting the journey in real-time built an audience that cared.
3. Simple pricing. $5 flat fee. No tiers, no subscriptions. Decision fatigue = zero.
4. PDF export. This was the killer feature. Google Docs export was requested but barely used.

What Broke

1. OpenAI costs. 400 resume generations at ~$0.02 each = $8. Plus my own testing = $12 total. Fine at this scale, but would be a problem at 10,000 users.
2. No auth system. I used anonymous sessions. Users could not save or edit later. 34% of support emails were "I lost my resume."
3. Mobile was terrible. 60% of traffic was mobile. The builder was desktop-only. Conversions on mobile were 1/10th of desktop.
4. Stripe tax. I did not set up tax collection. Technically illegal in some states. Had to fix later.

What I Would Do Differently

1. Start with auth. Even simple email/password would have saved hours of support.
2. Mobile-first design. I built desktop because I was on a laptop. Wrong call.
3. Use a cheaper model. GPT-3.5-turbo produced resumes 90% as good at 1/10th the cost. I switched after day 3.
4. Add analytics from hour 0. I retrofitted Mixpanel on day 2 and lost data.

The Numbers After 30 Days

• Total visitors: 12,400
• Signups: 687
• Paid conversions: 54
• Revenue: $270
• OpenAI costs: $89
• Stripe fees: $13
• Domain + hosting: $12
• Net: $156

Not quit-your-job money. But a working product, 687 emails, and proof of demand.

The Code (Simplified)

Here is the core generation logic, abstracted:

async function generateResume(data: ResumeData): Promise<string> {

const prompt = buildPrompt(data);

const response = await openai.chat.completions.create({

model: 'gpt-3.5-turbo',

messages: [{ role: 'user', content: prompt }],

temperature: 0.3,

max_tokens: 2000,

});

return response.choices[0].message.content;

}