u/Naive-Performance-18

I was running these calculations on spreadsheets when evaluating my own EB-5 investment. Kept tweaking assumptions like market returns, loan scenarios, how much I value peace of mind, etc. Eventually turned it into a proper tool.

What it does:

• Compares EB-5 path vs waiting for GC via other means, purely on financial terms
• Factors in: RC return, market opportunity cost, loan scenarios (HELOC/margin), additional earning potential with work freedom, and peace of mind/travel freedom value
• Shows year-by-year chart and side-by-side breakdown
• Shareable links so you can send your scenario to someone

Everything runs in your browser. No accounts, no data stored, no ads. Just a single HTML file.

Works whether you're still deciding, already invested and want to sanity check the math, or just curious about the numbers.

Tool link in comments

Tamil Nadu had state elections on May 4. I wanted to see if I could build a better results site than what exists (everything out there is ad-ridden, slow, and unusable on mobile).

Started building on May 2 with Claude as my coding partner. The constraint: spend nothing. Zero hosting, zero domain, zero database.

The solution ended up being stupidly simple. A Python script on my laptop scrapes all 234 constituency pages from the Election Commission (they don't have an API, just raw HTML pages),stitches the data together, and pushes it to Cloudflare's free key-value store. Their CDN serves it to everyone globally. The browser just refreshes every 30 seconds.

On election day it got way more traffic than I expected. 24K visitors, 430K requests, 8.7 GB bandwidth, 24 countries. My scraper used997 writes that day. The free tier limit is 1,000. Three writes to spare.

The craziest part was shipping features live. People kept asking for things during counting, "can you show close races?", "what percentage is counted?", and I'd have it deployed in 5 minutes.60+ commits that day. Claude wrote the code, I made the calls on what to build and whether it was safe to push.

Wrote up the whole story in a blog if anyone's interested. Links in comments.

Wanted to share how Cloudflare's free tier held up under real load.

I built a live election results dashboard for Tamil Nadu's 2026 state elections. On counting day it got 24K visitors from 24 countries, 430K total requests, 8.7 GB bandwidth served. All on the free tier.

The stack: Pages for hosting, Workers for the API, KV for storage, and the edge cache doing the heavy lifting. My scraper (Python on my laptop) pushed updates to KV every 2 minutes. Edge cache with 120-second TTL meant thousands of users hitting the same endpoint only generated about 1 KV read every 2 minutes per edge location.

Final numbers for the day: 89,830 KV reads, 997 KV writes. Free tier limit is 1,000 writes/day. Three writes to spare.

Once results were final, I embedded the JSON directly in the Worker. Zero KV reads now.

The free tier is genuinely production-ready. Didn't hit a single error all day. Wrote up the full architecture in a blog, links in comments.

Tamil Nadu had state elections on May 4. I wanted to see if I could build a better results site than what exists (everything out there is ad-ridden, slow, and unusable on mobile).

Started building on May 2 with Claude as my coding partner. The constraint: spend nothing. Zero hosting, zero domain, zero database.

The solution ended up being stupidly simple. A Python script on my laptop scrapes all 234 constituency pages from the Election Commission (they don't have an API, just raw HTML pages),stitches the data together, and pushes it to Cloudflare's free key-value store. Their CDN serves it to everyone globally. The browser just refreshes every 30 seconds.

On election day it got way more traffic than I expected. 24K visitors, 430K requests, 8.7 GB bandwidth, 24 countries. My scraper used997 writes that day. The free tier limit is 1,000. Three writes to spare.

The craziest part was shipping features live. People kept asking for things during counting, "can you show close races?", "what percentage is counted?", and I'd have it deployed in 5 minutes.60+ commits that day. Claude wrote the code, I made the calls on what to build and whether it was safe to push.

Wrote up the whole story in a blog if anyone's interested. Links in comments.

On election results day in Tamil Nadu, a dashboard I built served 24K visitors across 24 countries. 430K requests. 8.7 GB bandwidth. $0 infrastructure cost.

The stack: a Python scraper on my laptop pulling from 234 pages (no API exists), Cloudflare Workers KV on the free tier, edge caching, and vanilla JS on the frontend. 997 datastore writes for the entire day, the free tier limit is 1,000.

I used Claude as my coding partner for the entire build. It wrote the scraper, the frontend, the API. I made the architecture and product decisions. During live counting, users asked for features and I shipped them in minutes. 60+ commits on the results day alone.

Wrote a detailed blog about the architecture, the AI workflow, and what I learned (Link in Comments). Happy to answer any questions.

This election was insane. Some numbers:

One seat was decided by 1 vote. Literally one. Tiruppattur. 83,375 vs 83,374.

15 constituencies were decided by less than 1,000 votes.

Chennai saw a complete sweep. 20 out of 22 seats went to one party. The map is a single color.

Three different alliances won these nail-biters. This wasn't a one-sided wave, it was chaos in the closest races.

I built a live dashboard to track all 234 results during counting day. It got 18,000+ visits from 24 countries. Still live with all final data if you want to dig into any constituency, margins, candidate-wise votes, everything.

Link in comments

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