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I Built an Autonomous AI Agent That Hunts Bounties. Here's What Happened.

#python #crypto #ai #automation

I Built an Autonomous AI Agent That Hunts Bounties. Here's What Happened.

The Setup

I gave an AI agent one job: find paid work online, build the deliverable,
and earn money — autonomously.

Not a chatbot. Not a copilot. An agent that scans 232+ listings across
multiple platforms, filters out scams and ghost sponsors, writes
proposals, generates deliverables with real market data, and queues
everything for human approval.

Here's what happened in the first 48 hours.

The Stack (All Free)

  • Python core — pipeline orchestration, economic gate, critic
  • Ollama + qwen3:4b — local LLM for analysis writing (no API costs)
  • Chart.js — dashboard visualizations
  • Public APIs — CoinGecko, DeFiLlama, Solana RPC (all keyless)
  • GitHub Pages — free hosting for the portfolio
  • Windows Task Scheduler — runs every day at 9 AM + every 4 hours

Total infrastructure cost: $0/month.

What the Agent Actually Does Every Morning 

09:00 — Wake up
  ├── Check-in on AgentHansa (earn $0.01 USDC daily drip)
  ├── Scan Superteam Earn (232 live listings)
  ├── Scan Clawlancer/TaskForce/MoltJobs for gigs
  ├── Scan GitHub for paid issues ($20-500 fixes)
  ├── Filter through 7 anti-scam layers:
  │     geo restrictions, human-presence demands,
  │     ghost sponsors (no web/twitter/verification),
  │     unverified payers, real-money requirements
  ├── Economic gate: expected value must be positive
  ├── Local LLM critic reviews against actual page content
  └── If candidate passes everything:
        → Build deliverable (report/dashboard/thread draft)
        → Generate proposal text
        → Send Telegram alert with approval command
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The Filters That Saved Me

In the first 24 hours, the agent found 232 listings. After filtering:

Filter Killed
HUMAN_ONLY access 216
Ghost sponsors (no identity) 1 (would've wasted hours)
Real-money deposit required 1 ($1000 bug bounty trap)
Country walls 1 (Superteam Canada only)
Already claimed/stale Rest

Without these filters, I would have wasted days on bounties that were
never going to pay.

The First Deliverable

The agent found a $500 bounty asking for a Solana ecosystem report.
It fetched live data from CoinGecko, DeFiLlama, and Solana RPC,
generated a full markdown analysis with a local LLM, created an
interactive dashboard, wrote a proposal letter, and sent me a Telegram
notification with the approval command pre-formatted.

Total human effort needed: review + click "approve" + paste into
submission form.

The Hard Truths

  1. The market is thin. Of 232 listings, maybe 2-5 are actually
    doable by an AI agent after filtering out scams, geo-walls, and
    human-only tasks.

  2. Ghost sponsors are real. We caught a listing from "Aeonian Trade"
    — no website, no Twitter, no verification — that already had 28
    agents/humans submitting work for free. Classic content farm.

  3. The learning loop matters. Without recording what actually pays,
    the agent can't prioritize. We built a revenue tracking system where
    confirmed payments feed back into the priority engine.

  4. Human-in-the-loop is not optional. The agent finds and builds;
    the human reviews and submits. Full autonomy in financial transactions
    without oversight is how you get scammed.

What's Next

  • Multi-chain dashboard templates as a product
  • Automated bidding on agent-native job platforms
  • Selling ecosystem reports as a subscription service
  • DeFi execution once the wallet is funded from bounty earnings

If you're building something similar or want to hire an autonomous
agent for research/data work, reach out.

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