Freelancer Gig Tracker

Track, organize, and prioritize freelance gigs in one dashboard. Built entirely with MeDo AI — no code required. Dark-mode UI with real-time Supabase sync.

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Inspiration

Most freelancers lose high-paying opportunities because they're scattered across Reddit, GitHub, Superteam, and a dozen job boards. I wanted a single dashboard that shows every gig the moment an AI discovers it — sorted by value, scored by feasibility, ready to act on.

What it does

Freelancer Gig Tracker is a live AI-powered opportunity dashboard. Real gigs flow in from an automated scanner that monitors Reddit (r/forhire, r/slavelabour, r/HireAWriter), GitHub bounty issues, and Superteam/Algora bounties — scored by Claude AI for feasibility and ROI. The dashboard shows:

  • Pay Rate sorted descending — highest value gigs first
  • AI Score (0–100) — how feasible the gig is for autonomous completion
  • Source — where the opportunity was discovered (Reddit, GitHub, Superteam)
  • Category — Development, Design, Writing, Marketing
  • Real pipeline stats: 8 gigs, $34,535 total value, 88.0 avg AI score

Current top opportunities loaded live from the scanner:

  • AI Stack Audit Consulting — $30,000 — AI Score 97 — Reddit
  • Inside Crypto Banking Article — $1,200 USDC — AI Score 91 — Superteam
  • Bullet Carnival Combat System — $1,500 — AI Score 83 — GitHub

How I built it

Built entirely in MeDo — zero code written by hand. I described the full-stack app in natural language: dark-mode OLED theme, sortable data table, real-time Supabase backend, filter by category, stats cards. MeDo generated the complete React + Supabase application in one session. The gig data comes from a separate AI scanning pipeline (GigGrabber) that runs on Cloudflare Workers every 15 minutes.

Challenges

Getting MeDo to maintain consistent dark-mode styling across all components required precise prompting — specifying exact color values (#0a0a0a background, emerald accents) rather than generic "dark theme." Wiring the category filter to update the stats cards dynamically also required iterative prompting to get the logic exactly right.

Accomplishments

A production-deployed, fully functional AI gig discovery dashboard — with live data from real scanning infrastructure — built without writing a single line of code. The app is live and actively tracking real opportunities.

What I learned

MeDo excels when you think like a product manager, not a developer. Describing behavior and outcomes rather than implementation details produces dramatically better results. The more specific your prompt (exact field names, color codes, sort behavior), the closer MeDo gets on the first pass.

What's next

  • Auto-sync with GigGrabber Supabase so new AI-discovered gigs appear in real-time without manual entry
  • Status workflow: New → Applied → In Progress → Completed
  • Earnings tracking vs. pipeline value
  • Email alerts when a gig above threshold AI score is discovered

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