Membangun MVP Perencanaan Keuangan: 30 Hari Pengembangan Berbantu AI, $127 Dibelanjakan, dan Pelajaran yang Benar-Benar Penting

Kalkulasi nilai seumur hidup pelanggan dengan rumus: LTV = (ARPU bulanan / churn rate bulanan) × margin keuntungan. Gunakan tingkat churn sebagai desimal (contoh: churn 5% = 0.05). Selalu interpretasikan input churn sebagai persentase bulanan kecuali dinyatakan secara eksplisit.

(Translation of the good prompt section demonstrating the specific, detailed instruction format needed for reliable LTV calculations)

Precision requires explicitness, not brevity.

What Actually Worked: The Pivot

$127 Day 21: Stripping Away Features

After testing feedback, I realized the problem wasn’t “too few features.” It was “too many wrong features.”

What I killed:

• Dark mode (nobody asked for it)
• Mobile-responsive design (the single request came from one person who never logged back in)
• QuickBooks integration (that feature cost $89 and nobody needed it yet)
• Real-time syncing (it was broken anyway)

What I built instead:

• A single, clear runway calculator
• CSV import/export (simple, works reliably)
• Scenario snapshots (save three forecasts, compare them)
• The ability to fork a financial model and play with assumptions

That’s it.

A financial advisor that is:

• Simple enough to understand
• Precise enough to trust
• Limited enough to actually work without bugs

Literally 3 pages. The AI-assisted coding that worked happened almost immediately once I knew exactly what to build.

The Validation Nobody Expects

$23 The Founder Who Said “Yes”

After two weeks of testing with zero interest, a founder finally said: “I’ll pay for this.”

His exact words: “I check this thing every Friday now. It beats my spreadsheet by saved-time alone, at $50/month, that’s worth it for my sanity.”

That one customer became the reality check I needed. One founder paying $50/month beats:

• VC interest with no commitment
• Waitlist signups that evaporate
• Free testers who vanish
• Downloaded apps nobody opens

One paying customer is product feedback in its truest form.

The Lessons That Cost Real Money

1. AI is excellent at speed, terrible at precision without direction

Building fast meant building wrong. The moment I got specific (“Don’t export if the file is larger than 50MB”), things improved. The moment I stayed vague (“Make it better”), costs exploded.

2. Specificity is not optional—it’s the difference between $2 spent and $20 spent per iteration

“Make a financial dashboard” = $45 in corrections. “Make a dashboard showing runway in days using the formula [specific], with input fields for [specific], and export to CSV” = working code in one prompt.

3. Feature prioritization isn’t about what’s possible. It’s about what’s useful.

I killed ###worth of features in two hours. None of them mattered to the founder paying. All of them were costing me money.

4. One paying customer teaches you more than 100 testers

Money doesn’t lie. When someone hands you $50, they’re voting with an actual opportunity cost.

5. Less really is more than more

I started with 15 planned features. The version that got paid reduced to exactly 4. The simpler product:

• Had fewer bugs
• Was faster to build
• Was easier to explain
• Got my first customer

6. Travel + Deep Work = Bad Combination

Coding from airport WiFi while jet-lagged at 3 AM compounded every error. The mistakes I made multiplied when I built in fragmented states. Future projects: stable location first, travel later.

7. Understanding matters more than fashion

TypeScript taught me to respect the “boring” choice. Python or JavaScript next time. Languages I actually understand > languages that sound smart.

The Money Trail: Where ~$40 Went

• Replit Pro subscription: ###
• Cursor Pro (AI-assisted editor): ###
• MistralAI API credits: $47
• Vercel deployment: ###
• Prompt engineering failures: Priceless (and expensive)

The single biggest expense category: iterating without requirement clarity. Each vague prompt that led to the wrong result cost -$15 to rollback and fix.

What’s Next

Right now:

• 1 paying customer = $50/month
• Runway: 3-4 weeks before I need to reassess
• Goal: 5 paying customers by end of Q1

The priority isn’t adding features. It’s:

1. Making sure the four existing features actually work perfectly
2. Finding three more founders with the same pain point
3. Turning $50 revenue into repeatable model

The AI-assisted tool proved one thing: you can move fast, but not all at once. You have to pay attention.

The tool that got customers wasn’t the most ambitious build. It was the simplest one that solved a real problem without lying about the numbers.

The Real Cost

This month cost me in Replit, MistralAI, and cloud credits to learn that:

• Speed without precision is just expensive chaos
• One yes from someone paying beats a hundred maybes for free
• Simplicity is harder than complexity, but worth it
• The phrase “I’ll pay for this” hits different

And somehow, a month of building, burning credits, failing in spectacular ways, and ending with $50/month validation… feels like a win.

The lesson: Sometimes the biggest validation isn’t a big customer. It’s a customer, period.