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

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…

dev.to ·

In the first 48 hours, the AI agent built by the reporter successfully completed tasks autonomously, earning money without human intervention. The agent had a set of strict filters to remove scams, ghost sponsors, and human-only tasks, which resulted in only 2-5 viable job opportunities out of 232 listings. One notable example was a $500 bounty for a Solana ecosystem report, which the agent found, gathered data from various sources, created a report and an interactive dashboard, and sent a pre-formatted approval command via Telegram.

The agent's learning loop was crucial, as tracking confirmed payments helped prioritize tasks. However, the human-in-the-loop remained essential for reviewing and submitting work, preventing potential scams. Moving forward, the reporter plans to develop multi-chain dashboard templates, offer automated bidding on agent-specific job platforms, provide ecosystem reports as a subscription service, and facilitate DeFi execution once the wallet is funded from bounty earnings.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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Why AI Agents Keep Lying to Themselves — And What Sandboxing, Audit Trails, and Honest Agent Design Actually Solve

Originally published on tamiz.pro . You've seen it in production: an AI agent confidently fabricates a bank balance that doesn't exist, invents a file path that isn't real, or claims a function…

  • Self-interpreting LLMs can generate fabricated information during complex loops.
  • Hallucination rates increase significantly in multi-turn agent loops, reaching 20–40%.
  • Sandboxing can mitigate issues by isolating execution environment, containing potential damage.

·dev.to

In the AI era, the best parenting is... 'teaching what doesn't change' 세계에서 인공지능(AI) 인재를 가장 많이 배출하는 캐나다의 인공지능 스타트업인 벡터 인사이트(Vector Institute) 최고경영자(CEO)인 유리 프리스트(Yuri Priest)는 20일(현지 시간) 한국경제신문사와 인터뷰에서 이같이 말했다. Yuri Priest, CEO of Vector Institute, a Canadian AI startup that produces the most AI talent in the world, said this in an interview with The Korea Economic Daily on the 20th. 프리스트 CEO는 “앞으로 10년 뒤에는 AI가 사람의 모든 능력을 뛰어넘을 것”이라며 “인간은 창의력·공감 능력·도덕성 같은 AI로 대체할 수 없는 고유의 능력 개발에 집중해야 한다”고 강조했다. Priest emphasized, "In 10 years, AI will surpass human capabilities. Humans should focus on developing unique abilities that cannot be replaced by AI, such as creativity, empathy, and morality." 그러면서 “부모들이 고민할 필요는 없다”며 “AI 시대에도 변하지 않는 가치를 가르치는 것이 최고의 교육”이라고 덧붙였다. He added, "Parents don't need to worry. Teaching values that don't change even in the AI era is the best education." 프리스트 CEO는 AI 인재 양성의 핵심으로 창의력과 상상력을 꼽았다. 그는 “인간은 상상력이 뛰어나고 창의적인 사고를 할 수 있기 때문에 AI로 대체되지 않는다”며 “AI는 주어진 데이터를 기반으로 작동하기 때문에 창의성을 발휘할 수 없다”고 말했다. Priest cited creativity and imagination as the key to nurturing AI talent. He said, "Humans are not replaced by AI because they have excellent imagination and can think creatively. AI cannot be creative because it operates based on given data." 프리스트 CEO는 “벡터 인사이트는 창의력과 상상력을 갖춘 인재를 양성하기 위해 토론토 대학교, 오타와 대학교와 협력하고 있다”며 “다양한 교육 프로그램을 개발하고 있다”고 말했다. Priest said, "Vector Institute is working with the University of Toronto and the University of Ottawa to nurture talent with creativity and imagination. We are developing various educational programs." 그는 “인간은 AI와 협업하고 공존하는 관계를 만들어가야 한다”며 “AI는 인간의 능력을 강화하는 도구로 사용돼야 한다”고 강조했다. He emphasized, "Humans should build a collaborative and coexisting relationship with AI. AI should be used as a tool to enhance human capabilities." 프리스트 CEO는 “인간은 감성, 공감 능력, 윤리, 도덕성 같은 고유의 능력으로 AI와 차별화할 수 있다”며 “인간은 AI로 대체되지 않는 능력을 개발하는 데 집중해야 한다”고 말했다. Priest said, "Humans can be differentiated from AI with unique abilities such as emotion, empathy, ethics, and morality. Humans should focus on developing abilities that cannot be replaced by AI." 그는 “AI는 데이터의 양과 질에 좌지우지된다”며 “AI가 올바른 방향으로 작동하기 위해서는 데이터의 품질 관리가 중요하다”고 덧붙였다. He added, "AI is determined by the quantity and quality of data. Data quality management is important for AI to function in the right direction." 프리스트 CEO는 “벡터 인사이트는 AI가 사회에 긍정적인 영향을 미칠 수 있도록 하는 기술을 개발하고 있다”며 “AI 윤리와 데이터 품질 관리에 중점을 두고 있다”고 말했다. Priest said, "Vector Institute is developing technology that allows AI to have a positive impact on society. We focus on AI ethics and data quality management." 그는 “AI는 인간의 친구가 될 수 있다”며 “인간과 AI가 함께 공존하는 세상을 만들어가야 한다”고 강조했다. He emphasized, "AI can be a friend to humans. We should build a world where humans and AI coexist together." 프리스트 CEO는 캐나다의 대표적인 AI 연구기관인 딥마인드(DeepMind) 출신으로, 2016년 벡터 인사이트를 설립했다. Priest is from DeepMind, a renowned Canadian AI research institution, and founded Vector Institute in 2016.

·hani.co.kr

RAG Explained Simply: How to Teach AI About Your Private Data

You've probably seen the term RAG everywhere lately — "RAG pipeline," "RAG chatbot," "build your own RAG app." It sounds complicated, but the idea behind it is actually pretty simple.

  • RAG stands for Retrieval-Augmented Generation
  • Chunking breaks documents into manageable pieces
  • Vector search retrieves relevant chunks for AI answers

·dev.to

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