When AI Takes Over Productivity, Which Web3 Jobs Begin to Disappear?

比推發佈於 2026-03-05更新於 2026-03-05

文章摘要

In the evolving landscape of Web3, the integration of AI and automation is reshaping the job market, leading to the decline of certain roles while creating new opportunities. Jobs that involve repetitive or standardized tasks are increasingly being automated. These include: - Junior Solidity developers, as AI can generate standard smart contract code. - Web3 researchers/analysts, with AI handling data analysis and report generation. - Community managers and customer support roles, replaced by AI-driven communication systems. - Crypto traders, outperformed by AI in speed, data processing, and execution. - NFT content creators and low-barrier NFT creators, as generative AI produces art quickly, reducing demand for basic creative work. Simultaneously, new roles are emerging that require interdisciplinary skills: - AI × Web3 architects, designing integrated AI-blockchain systems. - AI Agent training coordinators, managing multi-agent behaviors in DeFi and DAOs. - Web3 prompt engineers, crafting prompts for code generation and AI interactions. - AI on-chain data analysts, extracting insights from blockchain data using AI models. - AI-powered smart contract auditors, enhancing security with automated tools. - Web3 automation strategy designers, developing algorithmic systems for DeFi. Overall, Web3 teams are becoming smaller but more efficient, with a growing emphasis on advanced, cross-disciplinary expertise in architecture, security, and innovation. AI...

Author: 137Labs

Original Title: Under the AI Wave, Which Web3 Jobs Are Rapidly Disappearing?


In recent years, Web3 has been considered an important direction for the development of the internet. From DeFi and NFTs to DAOs, numerous new business models have emerged, giving rise to many new professions. However, as generative AI and automation technologies rapidly enter this field, the job structure in Web3 has also begun to undergo significant changes.

More and more projects are starting to use AI to complete tasks that originally required human effort, such as writing code, analyzing on-chain data, generating market reports, and handling community issues. As these tools mature, the demand for certain positions has noticeably declined, while new types of roles are gradually emerging.

Overall, AI has not reduced the development prospects of Web3, but it is changing the industry's demand for talent structure.

I. Web3 Jobs That Are Gradually Decreasing

In the Web3 ecosystem, some highly standardized and repetitive tasks are gradually being replaced by automation tools. With the development of generative AI and automation technologies, many tasks that originally required manual effort can now be quickly completed by algorithms and intelligent systems, leading to a noticeable decline in demand for certain positions.

1. Junior Solidity Developers

Smart contract development was once one of the hottest professions in the Web3 industry. However, with the rapid development of AI programming tools, a large amount of standardized code can now be generated automatically. For example, common code structures such as ERC-20 token contracts, NFT contracts, and basic DeFi protocols can be generated by AI in a very short time. AI can not only generate complete code frameworks but also perform basic testing and logic checks. As a result, more and more companies are reducing their demand for junior developers and instead relying on senior architects to review and optimize AI-generated code.

2. Web3 Researchers / Analysts

In the past, Web3 projects often required researchers to complete a large amount of industry research and data organization work, including industry trend analysis, project evaluation, market research, and report writing. However, with the advancement of AI technology, much of this research work can now be completed using automation tools. For example, AI can quickly analyze on-chain data, simulate token economic models, and automatically generate structured market research reports. As a result, the demand for research positions primarily focused on basic information organization and data analysis is gradually decreasing.

3. Community Managers and Customer Support

Community operations were once a crucial part of the Web3 ecosystem, with many projects requiring community managers and customer support staff to handle user issues and maintain community order. However, with the development of AI customer support systems, many repetitive communication tasks can now be automated. For instance, AI can provide 24/7 automated responses, real-time multilingual translation, automatically identify and filter spam, and quickly answer common user questions. In this context, some basic community support roles are gradually being replaced by AI systems.

4. Crypto Traders

In the field of cryptocurrency trading, the advantages of AI technology are particularly evident. AI can analyze vast amounts of market data in a very short time and automatically perform trading operations based on preset strategies, including high-frequency trading, automated arbitrage, and risk control. Compared to human traders, AI has significant advantages in execution speed, data processing capabilities, and trading stability, while also reducing operational costs. As a result, traditional human trading positions are gradually decreasing in environments that rely on technical strategies.

5. NFT Content Creators

The emergence of generative AI has had a profound impact on the NFT ecosystem. Today, AI can generate a large amount of visual content in a short time, such as illustrations, avatars, and various forms of digital art. This has significantly lowered the barrier to NFT content creation while also intensifying market competition. In this environment, some NFT content creators who rely on basic design skills or simple visual creation are gradually losing their market advantage.

6. Low-Barrier NFT Creators

With the proliferation of AI image generation tools, the way digital content is created is changing. In the past, some NFT projects generated large volumes of work through simple image combinations or basic designs. Now, AI can complete similar or even more complex creation processes in a very short time. This poses a significant challenge to traditional low-barrier NFT creation models. Some creators who lack unique creativity, artistic style, or brand value are gradually losing their competitive edge as AI technology becomes more widespread.

II. Emerging New Web3 Professions

Although the demand for some positions is decreasing, AI is also creating new job opportunities in the Web3 industry. As artificial intelligence and blockchain technology continue to integrate, the demand for interdisciplinary talent with cross-domain capabilities is steadily increasing.

1. AI × Web3 Architect

AI × Web3 architects are becoming one of the core roles in future Web3 technical teams. As AI and blockchain systems deepen their integration, more projects require the construction of system architectures that support automated decision-making and intelligent collaboration. These roles not only involve designing the collaborative architecture between AI and blockchain systems but also building interaction mechanisms between AI agents and smart contracts, and planning decentralized AI network infrastructure. Additionally, these professionals need to design on-chain automated execution systems. Therefore, this role typically requires practitioners to have a technical understanding of blockchain infrastructure, AI models and agent systems, distributed computing architecture, and cryptographic economic models.

2. AI Agent Training Coordinator

As multi-agent systems become increasingly applied in the Web3 ecosystem, some projects are beginning to require specialized personnel to train and coordinate the behavioral logic of AI agents. The main responsibilities of an AI agent training coordinator include defining collaboration rules between multiple AI agents, designing behavioral constraint mechanisms for agents, optimizing their decision-making logic in scenarios such as DeFi and DAOs, and continuously monitoring the on-chain behavior of AI agents. This role is more focused on AI behavior management and system governance and will play an important role in the future Web3 automation ecosystem.

3. Web3 Prompt Engineer

As AI tools become more widely used in Web3 development, prompt engineering is gradually evolving into a new professional role. The main responsibilities of a Web3 prompt engineer include designing complex prompts to generate smart contract code, building AI automated research and analysis processes, optimizing the interaction between AI and blockchain systems, and designing behavioral instructions for AI agents. Compared to traditional prompt engineering, this role places greater emphasis on designing complex task flows and the practical application capabilities of AI systems.

4. AI On-Chain Data Analyst

Blockchain networks generate a large amount of public data every day, and AI technology can help analyze this data and uncover underlying patterns. The main responsibilities of an AI on-chain data analyst include analyzing on-chain fund flows, monitoring market trends, identifying abnormal trading behaviors, and predicting ecosystem development trends. Additionally, they need to build AI data analysis models to extract valuable information from massive blockchain data. Therefore, this role typically requires practitioners to have a background in data science, blockchain analysis capabilities, and AI modeling skills.

5. AI-Driven Smart Contract Security Expert

As AI-generated code technology becomes more widespread, smart contract security issues are becoming more complex. As a result, AI-driven smart contract security experts are becoming increasingly important in the Web3 industry. These experts typically use AI tools to detect code vulnerabilities, design automated auditing systems, simulate potential attack paths, and evaluate the overall security risks of protocols, thereby enhancing the security of DeFi protocols and blockchain applications. The smart contract security field is also considered one of the fastest-growing areas of demand in the future Web3 industry.

6. Web3 Automation Strategy Designer

In the DeFi ecosystem, automated strategies have become an important development direction. Web3 automation strategy designers are primarily responsible for developing automated yield strategies, automated arbitrage systems, and risk control algorithms, while also designing intelligent asset allocation strategies to enable assets to automatically adjust across different protocols. These strategies are typically executed automatically by algorithmic systems or AI agents, so this role requires an understanding of financial models, algorithm design capabilities, and a background in blockchain technology.

III. Trends in Web3 Employment Structure Changes

As AI technology continues to develop, the talent demand in the Web3 industry shows several clear trends.

First, team sizes are becoming smaller. Automation tools can handle a large amount of repetitive work, meaning project teams no longer need as many basic positions.

Second, interdisciplinary skills are becoming more important. Future Web3 talent will often need to possess blockchain technology, AI technology, and data analysis capabilities simultaneously.

Finally, the importance of senior positions is increasing. Roles such as system architecture, economic model design, and security engineering are becoming core positions in the industry.

IV. Conclusion

AI is reshaping the job structure of the Web3 industry. Some positions that are primarily execution-based and highly repetitive are gradually decreasing, while roles that demand creativity, systemic thinking, and cross-domain capabilities are becoming increasingly important.

In the long run, AI will not weaken the development potential of Web3. On the contrary, it may propel the entire industry into a new phase. In this process, truly talented individuals with technical depth and innovation capabilities will become the most important resource in the future Web3 ecosystem.


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Original Link:https://www.bitpush.news/articles/7616959

相關問答

QWhich Web3 jobs are gradually disappearing due to the rise of AI and automation?

AJobs such as Junior Solidity Developers, Web3 Researchers/Analysts, Community Managers and Customer Support, Crypto Traders, NFT Content Creators, and Low-barrier NFT Creators are declining as AI handles standardized, repetitive tasks more efficiently.

QWhat new Web3 roles are emerging as a result of AI integration?

ANew roles include AI × Web3 Architects, AI Agent Training Coordinators, Web3 Prompt Engineers, AI On-chain Data Analysts, AI-driven Smart Contract Security Experts, and Web3 Automation Strategy Designers.

QHow is AI changing the structure of Web3 teams and talent demands?

AAI is reducing team sizes by automating repetitive work, increasing the importance of interdisciplinary skills (combining blockchain, AI, and data analysis), and elevating the demand for high-level roles in system design, economic modeling, and security engineering.

QWhy are Junior Solidity Developers less in demand with the adoption of AI?

AAI programming tools can automatically generate standardized code like ERC-20 token contracts and basic DeFi protocols, reducing the need for junior developers while increasing reliance on senior architects to review and optimize AI-generated code.

QWhat impact does AI have on NFT content creation?

AAI image generation tools lower the barrier to entry for digital content creation, enabling rapid production of artworks. This reduces the competitive advantage of low-skill NFT creators but emphasizes the value of unique creativity, artistic style, and brand identity.

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DUOLINGO AI:將語言學習與Web3及AI創新結合 在科技重塑教育的時代,人工智能(AI)和區塊鏈網絡的整合預示著語言學習的新前沿。進入DUOLINGO AI及其相關的加密貨幣$DUOLINGO AI。這個項目旨在將領先語言學習平台的教育優勢與去中心化的Web3技術的好處相結合。本文深入探討DUOLINGO AI的關鍵方面,探索其目標、技術框架、歷史發展和未來潛力,同時保持原始教育資源與這一獨立加密貨幣倡議之間的清晰區分。 DUOLINGO AI概述 DUOLINGO AI的核心目標是建立一個去中心化的環境,讓學習者可以通過實現語言能力的教育里程碑來獲得加密獎勵。通過應用智能合約,該項目旨在自動化技能驗證過程和代幣分配,遵循強調透明度和用戶擁有權的Web3原則。該模型與傳統的語言習得方法有所不同,重點依賴社區驅動的治理結構,讓代幣持有者能夠建議課程內容和獎勵分配的改進。 DUOLINGO AI的一些顯著目標包括: 遊戲化學習:該項目整合區塊鏈成就和非同質化代幣(NFT)來表示語言能力水平,通過引人入勝的數字獎勵來激發學習動機。 去中心化內容創建:它為教育者和語言愛好者提供了貢獻課程的途徑,促進了一個有利於所有貢獻者的收益共享模型。 AI驅動的個性化:通過採用先進的機器學習模型,DUOLINGO AI個性化課程以適應個別學習進度,類似於已建立平台中的自適應功能。 項目創建者與治理 截至2025年4月,$DUOLINGO AI背後的團隊仍然是化名的,這在去中心化的加密貨幣領域中是一種常見做法。這種匿名性旨在促進集體增長和利益相關者的參與,而不是專注於個別開發者。部署在Solana區塊鏈上的智能合約註明了開發者的錢包地址,這表明對於交易的透明度的承諾,儘管創建者的身份未知。 根據其路線圖,DUOLINGO AI旨在演變為去中心化自治組織(DAO)。這種治理結構允許代幣持有者對關鍵問題進行投票,例如功能實施和財庫分配。這一模型與各種去中心化應用中社區賦權的精神相一致,強調集體決策的重要性。 投資者與戰略夥伴關係 目前,沒有與$DUOLINGO AI相關的公開可識別的機構投資者或風險投資家。相反,該項目的流動性主要來自去中心化交易所(DEX),這與傳統教育科技公司的資金策略形成鮮明對比。這種草根模型表明了一種社區驅動的方法,反映了該項目對去中心化的承諾。 在其白皮書中,DUOLINGO AI提到與未具名的「區塊鏈教育平台」建立合作,以豐富其課程提供。雖然具體的合作夥伴尚未披露,但這些合作努力暗示了一種將區塊鏈創新與教育倡議相結合的策略,擴大了對多樣化學習途徑的訪問和用戶參與。 技術架構 AI整合 DUOLINGO AI整合了兩個主要的AI驅動組件,以增強其教育產品: 自適應學習引擎:這個複雜的引擎從用戶互動中學習,類似於主要教育平台的專有模型。它動態調整課程難度,以應對特定學習者的挑戰,通過針對性的練習加強薄弱環節。 對話代理:通過使用基於GPT-4的聊天機器人,DUOLINGO AI為用戶提供了一個參與模擬對話的平台,促進更互動和實用的語言學習體驗。 區塊鏈基礎設施 建立在Solana區塊鏈上的$DUOLINGO AI利用了一個全面的技術框架,包括: 技能驗證智能合約:此功能自動向成功通過能力測試的用戶頒發代幣,加強了對真實學習成果的激勵結構。 NFT徽章:這些數字代幣標誌著學習者達成的各種里程碑,例如完成課程的一部分或掌握特定技能,允許他們以數字方式交易或展示自己的成就。 DAO治理:持有代幣的社區成員可以通過對關鍵提案進行投票來參與治理,促進一種鼓勵課程提供和平台功能創新的參與文化。 歷史時間線 2022–2023:概念化 DUOLINGO AI的基礎工作始於白皮書的創建,強調了語言學習中的AI進步與區塊鏈技術去中心化潛力之間的協同作用。 2024:Beta發佈 限量的Beta版本推出了流行語言的課程,作為項目社區參與策略的一部分,獎勵早期用戶以代幣激勵。 2025:DAO過渡 在4月,進行了完整的主網發佈,並開始流通代幣,促使社區討論可能擴展到亞洲語言和其他課程開發的問題。 挑戰與未來方向 技術障礙 儘管有雄心勃勃的目標,DUOLINGO AI面臨著重大挑戰。可擴展性仍然是一個持續的擔憂,特別是在平衡與AI處理相關的成本和維持響應靈敏的去中心化網絡方面。此外,在去中心化的提供中確保內容創建和審核的質量,對於維持教育標準來說也帶來了複雜性。 戰略機會 展望未來,DUOLINGO AI有潛力利用與學術機構的微證書合作,提供區塊鏈驗證的語言技能認證。此外,跨鏈擴展可能使該項目能夠接觸到更廣泛的用戶基礎和其他區塊鏈生態系統,增強其互操作性和覆蓋範圍。 結論 DUOLINGO AI代表了人工智能和區塊鏈技術的創新融合,為傳統語言學習系統提供了一種以社區為中心的替代方案。儘管其化名開發和新興經濟模型帶來某些風險,但該項目對遊戲化學習、個性化教育和去中心化治理的承諾為Web3領域的教育技術指明了前進的道路。隨著AI的持續進步和區塊鏈生態系統的演變,像DUOLINGO AI這樣的倡議可能會重新定義用戶與語言教育的互動方式,賦能社區並通過創新的學習機制獎勵參與。

453 人學過發佈於 2025.04.11更新於 2025.04.11

什麼是 DUOLINGO AI

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