Under the AI Wave, Which Web3 Careers Are Rapidly Disappearing?

marsbitОпубликовано 2026-03-01Обновлено 2026-03-01

Введение

The rapid advancement of AI is profoundly impacting the Web3 job market, leading to the decline of several traditional roles while creating new opportunities. Roles such as junior Solidity developers, entry-level researchers, community moderators, crypto traders, and NFT artists are increasingly being replaced by AI, which can perform these tasks faster, cheaper, and often more effectively. Conversely, new Web3 professions are emerging. These include AI-Web3 synergy architects, who design systems for AI and blockchain integration; AI agent training coordinators, managing multi-agent collaboration; advanced prompt engineers crafting behavioral frameworks for AI; on-chain behavioral economists designing anti-AI-exploit tokenomics; Web3 compliance and ethics officers addressing algorithmic bias; and privacy and proof-of-humanity experts verifying human identity in an AI-dominated landscape. The key takeaway is adaptability. Web3 professionals must assess whether their current roles will remain relevant and focus on areas where human-AI collaboration creates value—the intersection of human ingenuity and machine efficiency.

Author: TinTinLand

When AI can perfectly replace complex white-collar tasks at an extremely low cost, the impact on intellectual job positions may be faster and more thorough than any previous industrial revolution.

For ordinary people, a critical question must be seriously considered: In the AI era, which careers are rapidly disappearing? And how does this impact affect job positions in the Web3 industry?

Web3 Careers Rapidly Fading Under the Impact of AI

Junior Solidity / Contract Developers

AI can already generate about 80% of standardized smart contracts. Many Web3 projects have started using AI to generate initial versions of contracts, which are then reviewed and optimized by senior developers.

Junior Researchers / Analysts

If your work involves: organizing materials, writing project introductions, translating whitepapers, creating comparative tables—then you are doing exactly the type of work that AI excels at.

AI Agents can already automatically call APIs, process data, generate charts, and provide insights. A deep report that used to take a data analyst three days to complete can now be generated by AI in minutes.

Community Managers / Customer Support

Today, AI customer support can operate 24/7, respond in multiple languages, automatically filter spam, and provide personalized answers based on user history.

Crypto Traders

High-frequency trading, arbitrage, market making, and other activities were once the core advantages of crypto traders.

AI's advantages in these areas are overwhelming: faster reaction speeds, stronger pattern recognition capabilities, more precise risk control, and tireless execution discipline.

NFT Artists

AI-generated visual content can already match or even surpass the quality of human artists, and more importantly, its creation cost is almost zero.

Emerging New Web3 Careers

AI-Web3 Synergy Architect

As AI Agents begin to directly interact on-chain, projects need to design collaboration methods between the two at the system level.

This role is responsible for solving issues such as how AI can securely control multi-signature wallets, how to participate in DAO governance, and how to verify AI reasoning results on-chain. Essentially, they are building the underlying architecture for "AI-participatory Web3 systems."

AI Agent Training Coordinator

When a project simultaneously runs multiple Agents for trading, community management, risk control, data analysis, etc., how can they collaborate without losing control?

This position requires defining the Agents' responsibility boundaries, permission levels, incentive and constraint mechanisms to prevent博弈, internal consumption, or even systemic risks among Agents.

Senior Prompt Engineer

In Web3 scenarios, Agent behavior highly depends on context and constraints rather than a single prompt. This role is evolving from "writing Prompts" to "designing long-term behavior frameworks," including role setting, memory structure, calling permissions, and failure fallback mechanisms, directly determining the stability and controllability of AI's on-chain behavior.

On-Chain Behavioral Economics Designer

When AI Agents become important participants on-chain, traditional token economic models based on human emotions begin to fail.

On-chain behavioral economics designers need to design incentive mechanisms that can attract human participation while resisting AI arbitrage and manipulation, introducing adaptive parameters and dynamic constraints, and responding to AI's rapid vulnerability identification capabilities.

Web3 Compliance and Ethics Officer

When AI Agents are used for governance decisions, risk control, and user screening, algorithmic bias and accountability become unavoidable issues.

Web3 compliance and ethics officers need to understand legal, technical, and governance logic simultaneously, finding a practical balance between regulatory requirements and decentralized principles.

Privacy and Human Verification Expert

In an era dominated by AI Agents, distinguishing between "human identity" and "machine identity" will generate significant economic value. These experts will use privacy computing and biometric recognition technologies to provide trusted human verification services for the Web3 environment.

Conclusion: Adaptability Is the Only Certainty

For Web3 practitioners, it may indeed be time to start thinking: Will the work I am doing now still require humans three years later?

Understanding what AI can and cannot do, and finding the seams where humans and machines collaborate—that is not only the soil where new careers grow but also the true ticket to the next era.

Связанные с этим вопросы

QWhich Web3 jobs are rapidly disappearing under the impact of AI?

APrimary Solidity/contract developers, junior researchers/analysts, community managers/customer support, crypto traders, and NFT artists are among the Web3 roles being quickly replaced by AI due to automation and efficiency gains.

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

ANew roles include AI-Web3协同架构师 (synergy architects), AI Agent训练协调员 (training coordinators), advanced prompt engineers, on-chain behavioral economists, Web3 compliance and ethics officers, and privacy and human verification experts.

QHow is AI affecting the role of初级研究员/分析师 (junior researchers/analysts) in Web3?

AAI can automate tasks like data整理, report generation, and comparative analysis, completing in minutes what used to take days, making junior analytical roles less necessary.

QWhy are AI Agents posing a need for链上行为经济设计师 (on-chain behavioral economists)?

AAs AI Agents become active on-chain participants, traditional token economies designed for human behavior fail; new economists must design incentives resistant to AI manipulation and套利.

QWhat is the key takeaway for Web3 professionals in the AI era according to the article?

AAdaptability is crucial; professionals must understand AI's capabilities, identify human-machine collaboration opportunities, and evolve their skills to remain relevant in the changing landscape.

Похожее

The Value Distribution of Stablecoins

**Summary: The Value Distribution of Stablecoins** The article argues that stablecoins are evolving from mere trading tools into broader channels for dollar access. It divides the stablecoin ecosystem into four layers to analyze how value is distributed: 1. **Issuance Layer:** Mints stablecoins, holds reserve assets, and captures the spread between reserve yield and user costs (e.g., Tether, Circle). This layer currently earns the largest profit margin. 2. **Infrastructure Layer:** Connects stablecoins to the traditional financial system, handling fiat on/off-ramps, banking integration, compliance (KYC/AML), and asset management (e.g., Bridge, BVNK). This is the "unglamorous" but critical work, building the essential bridges between crypto and real-world finance. 3. **Acquiring/Distribution Layer:** Integrates stablecoins into merchant systems, manages payment flows, and provides enterprise financial software (e.g., Stripe, Coinbase). They act as the access point for businesses. 4. **Application Layer:** The end-users and businesses that ultimately use stablecoins for payments, settlements, or as a store of value. They benefit from convenience but have little pricing power. The core thesis is that while the issuance layer currently dominates profits, the often-overlooked **infrastructure layer holds significant long-term potential**. The real challenge and barrier to mass adoption is not the on-chain transfer of stablecoins (which is simple), but the complex "last mile" integration into existing business workflows, banking systems, and regulatory frameworks across different countries. Companies in this layer are currently in a "land grab" phase, investing heavily to build networks, secure bank partnerships, and establish compliance pathways. While their position is currently pressured by the profitable issuers above and distribution platforms below, the article suggests that if stablecoins become a default financial rail for businesses, the infrastructure providers who have done the hard work of integration will ultimately gain strong pricing power and become entrenched, essential players.

marsbit4 ч. назад

The Value Distribution of Stablecoins

marsbit4 ч. назад

The Value Distribution of Stablecoins

The Value Distribution of Stablecoins The article argues that stablecoins are evolving from a mere trading tool into a broad "dollar channel." It analyzes the industry's value chain through four layers: 1. **Issuance Layer (e.g., Tether, Circle):** The top layer that mints stablecoins, holds reserve assets, and captures the thickest interest rate spread. 2. **Infrastructure Layer (e.g., Bridge, BVNK):** Connects stablecoins to the traditional financial system, handling critical but complex "dirty work" like fiat on/off-ramps, banking integration, compliance (KYC/AML), and cross-border settlement. 3. **Acquiring/Distribution Layer (e.g., Stripe, Coinbase):** Embeds stablecoins into merchant systems, manages payment flows, and integrates with enterprise software. 4. **Application Layer:** End-users and businesses that ultimately use stablecoins for payments, settlement, or storing value. The author posits that while the issuance layer currently captures the most profit, the most overlooked and potentially critical layer is infrastructure. The core challenge for stablecoin adoption isn't the on-chain transfer (which is simple), but bridging the gap between blockchain and the real-world financial system. This involves solving practical problems for businesses: fiat conversion, reconciliation, tax handling, and user onboarding. Infrastructure companies are currently in a difficult "land-grab" phase—building networks, securing banking relationships, and achieving compliance country-by-country. They face pressure from both the profitable issuance layer above and distribution platforms below. However, the author suggests this layer is building a crucial moat. Once stablecoins become a default business rail, the infrastructure players who have done the hard work of integration may gain significant, durable value and pricing power.

链捕手5 ч. назад

The Value Distribution of Stablecoins

链捕手5 ч. назад

How to Do Research Well: Deliberately Practice the Real Skills That Matter

No one truly teaches you how to do research. You're often given a desk, a pre-selected problem, and vague instructions to "create something new." Consequently, many people reverse-engineer the job based on visible outputs—papers, posts, announcements—learning only how to *appear* like a researcher rather than how to *become* one. True research capability is built from stacking small, trainable skills, nearly all of which can be developed through deliberate practice. **Pick Your Own Problem:** Most researchers absorb problems from advisors or trends, lacking the underlying reasoning. Choosing a problem you genuinely care about, as John Schulman advises, leads to original work. Develop "taste" like a muscle: predict experiment outcomes, guess paper results from methods, and track which findings remain important over time. **Upgrade Your Inputs:** Relying on shared reading lists (arXiv hot lists, filtered group chats) leads to unoriginal conclusions. Undervalued old literature often holds crucial insights (e.g., MoE, LSTM, backpropagation). Richard Sutton's "The Bitter Lesson" or Claude Shannon's 1952 talk on creative thinking are more predictive than lengthy modern surveys. Breadth matters as much as depth: draw from neuroscience, mechanism design, hardware knowledge, and honest statistics. Read papers directly, especially appendices and limitations sections. **Write Everything Down:** As Paul Graham noted, writing exposes flaws in seemingly mature ideas. Writing is the cheapest defense against self-deception. Following Feynman's principle, Darwin programmatically wrote down facts contradicting his theory to combat memory bias. Maintain a detailed log of hypotheses, setups, predictions, results, and updated understandings. Reviewing past logs fosters essential humility.

marsbit7 ч. назад

How to Do Research Well: Deliberately Practice the Real Skills That Matter

marsbit7 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

2025 год — год институциональных инвесторов, в будущем он будет доминировать в приложениях реального времени.

1.8k просмотров всегоОпубликовано 2025.12.16Обновлено 2025.12.16

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на AI (AI) представлены ниже.

活动图片