We start from insecurity and ultimately find ourselves in a structure of certainty.

Written by: Keegan Xiaogang

I. Current Situation: The Anxiety and Crisis of Web2 Technicians

I have noticed that more and more people are adding me as a friend and asking for advice on how to transition to Web3.

There are fresh graduates, engineers with three to five years of experience, and middle-aged technicians like me, who have been in the field for over a decade and are beginning to feel uneasy about their career prospects.

Their questions are almost the same:

• "Is there still an opportunity in Web3?"

• "Is it too late for me to learn now?"

• "The most practical question is—how can newcomers find a job in Web3?"

This anxiety is not coincidental. Over the past decade, Web2 has built a "certain world" for technicians—stable positions, predictable promotion paths, and platform dividends. However, entering 2024, this certainty is rapidly collapsing. A structural turning point in the internet industry has arrived, and the wave of AI is making this turning point even more irreversible.

1. The End of Technical Dividends

The growth of the global internet industry is slowing down. In the first half of 2025, global tech companies announced nearly 94,000 layoffs, reaching a three-year high (Observer, 2025.07). This is no longer a cyclical adjustment but a fundamental change in industry logic.

Microsoft's actions are particularly typical:

In July 2025, Microsoft announced layoffs of about 9,000 people, accounting for about 4% of its global workforce; in May, it had just completed another round of layoffs affecting over 6,000 people. At the same time, the company explicitly required employees to "must use AI tools" and incorporated this into the performance evaluation system.

This means that even the most stable and resource-rich tech giants in the world are actively "optimizing their workforce with AI." The "job security" formed under the Web2 model is being systematically eroded.

2. The Substitution Effect of AI

The rise of AI is not just an update of efficiency tools but a rewriting of the definition of "technical work itself." The 2025 global developer survey by Stack Overflow shows that 52% of programmers use AI tools (such as Copilot, ChatGPT, Claude, etc.) daily, with 18% stating that AI has significantly changed their job responsibilities.

In other words, AI has become a part of the development process, rather than an option.

Products that originally required 10 people to collaborate can now be delivered by 3 people plus AI.

The focus of job competition is shifting from "who can write better code" to "who can collaborate more efficiently with AI." This represents a silent "collapse of the middle layer" for traditional Web2 technicians: AI-native engineers are rising, while purely execution-based positions are gradually being marginalized.

3. The Double-Edged Sword of Platform Dependence

The prosperity of Web2 is built on "platform ecosystems." Technicians rely on systems like the App Store, Google, WeChat, and Douyin, but this dependence also means that personal output lacks autonomy and asset value. Data from SensorTower shows that by the end of 2024, policy adjustments in the Apple App Store led to a sudden drop in income for about 12% of independent developers globally, instantly cutting off the main revenue channels for many small and medium-sized teams.

This risk is prevalent within the Web2 system:

• Changes in platform rules can directly affect personal livelihoods;

• Creators' data and works belong to the platform;

• Accounts or services being banned can lead to a "zero" situation.

In this structure, no matter how hard individuals work, it is difficult to accumulate transferable and sustainable assets.

4. The Reconstruction of Skills and Income Structure

The LinkedIn report "Future of Skills 2025" points out that AI, blockchain, and data analysis are the fastest-growing skill areas, while the growth rate of traditional Web front-end skills has dropped to 0.3%. Meanwhile, according to data from Levels.fyi at the end of 2024, the average salary of FAANG engineers has decreased by about 8% year-on-year, while AI/LLM-related positions have risen by over 20%.

This means that the technical dividend is shifting from "platform development" to a new field of "intelligent systems + decentralized technology." Skill migration is no longer "a nice addition" but "a prerequisite for survival."

5. The Erosion of the Roots of Security

The facts pieced together by these data are:

• The organizational stability of Web2 is no longer present;

• Job skill boundaries are blurred by AI;

• Income and growth paths are detached from platform logic.

More and more engineers, designers, and product people are beginning to have the same questions:

• "Can my skills still constitute long-term value?"

• "If I don't rely on a platform, can my output still exist?"

The source of security is shifting from "companies and platforms" to "individual self-evolution capabilities."

🧩 This is the core logic of "Web2 no longer providing a sense of security":

Certainty has shifted from external organizations to individual structures.

The next generation of technicians must reconstruct their own certainty at the intersection of AI and Web3.

II. Turning Point: The Era of Fusion between AI and Web3

If the last wave of the internet (Web2) connected people, then this wave (AI + Web3) is reconstructing the subject of connection—from "platform-centric" to "intelligent agents and individuals."

1. The Overlap of Technical Cycles

The emergence of AI and Web3 is not an isolated event but the intersection of two exponential curves.

• AI Curve: Generative intelligence represented by LLMs (large language models) is achieving "cognitive automation."

• Web3 Curve: Decentralized infrastructure represented by blockchain is achieving "value automation."

When these two curves intersect, a new era interface is formed:

Intelligent individuals can own identity, assets, and agency on the chain.

McKinsey estimates in "The Economic Potential of Generative AI" (2025) that AI is expected to contribute $4 trillion to $7 trillion to the global economy each year; according to Electric Capital's 2025 developer report, Web3 still has over 23,000 monthly active developers continuously building. This indicates that although the two ecosystems have different rhythms, they are both entering a phase of practicality and integration.

2. AI: From Tool to Subject

2023–2025 is a critical phase for AI "personification." From the initial ChatGPT and Claude to the current focus on coding/Agent models like Cursor, Claude Code, and Codex, we have witnessed the evolution of AI from "auxiliary tools" to "autonomous executing agents."

AI is no longer just an assistant that helps you write code; it is a collaborator that can make independent decisions and execute tasks:

• It can automatically draft and deploy contracts;

• It can interact with on-chain protocols, execute transactions, and manage assets;

• It can even self-learn and optimize based on revenue models.

This evolution has given rise to a new concept—AI-native Builder:

Individuals expand their productivity through AI and solidify their results through on-chain protocols.

This means that the future "developer" is no longer a single engineer but a hybrid of "human + intelligent agent."

3. Web3: From Speculative Narrative to Structural Infrastructure

Simultaneously with AI, Web3 is undergoing a transformation from speculative narratives to infrastructure. In the past, discussions focused more on "coin prices," while the current focus is shifting to "protocol layer capabilities"—the underlying facilities that can sustainably support the digital economy.

Today, the true focus of the industry is concentrated in several directions:

These trends collectively indicate:

Web3 is no longer just a stage for financial innovation but is evolving into the trusted execution layer (Trust Layer) of the next generation of the internet—a foundation that allows AI, individuals, and the real economy to collaborate freely under a trust mechanism.

4. What Happens When AI and Web3 Merge?

We are witnessing a brand new system form: AI generation + Web3 settlement + individual ownership. This structure brings about leaps on three levels:

In simple terms, AI makes "production" more efficient, while Web3 makes "results" more sustainable. Together, they drive a trend—the emergence of individual economic entities.

AI can enable one person to have a hundredfold productivity; Web3 allows this productivity to be secured, monetized, and reused. This is the underlying logic behind the rise of "one-person labs" and even "one-person companies."

5. Structural Opportunities: From Platform Dividends to Protocol Dividends

Historically, every technological cycle shift has been accompanied by a rewriting of production relations. From PCs to the internet, from mobile to platform economy, the center of dividends has continuously shifted. This time, the dividends are shifting from "platform dividends" to "protocol dividends":

• Platform Dividends: Relying on giants, monetizing through traffic;

• Protocol Dividends: Building open systems, participating in value distribution.

In this process, individuals who understand how to leverage AI to build products and use Web3 to secure results will become the next generation of "micro-production nodes." Whether developers, designers, or independent creators, there are opportunities to find new certainty within this.

6. The Proposition of the New Era

When we say "AI + Web3 is a turning point," it is not an abstract slogan but a real structural trend:

• The production tools have fundamentally changed (AI);

• The value system has fundamentally changed (Web3);

• And the role of technicians is shifting from "passive execution" to "active creation."

This is not just a skill upgrade but a paradigm shift.

🧭 This is the turning point represented by "the fusion of AI + Web3":

AI redefines productivity, and Web3 redefines ownership.

When productivity and ownership overlap at the individual level, a new era for technicians begins.

III. The Way Out: From Technical Positions to Individual Nodes

As the technical dividends fade and platform certainty collapses, new questions naturally arise:

"What should I do to transition?"

In the era of the fusion of AI and Web3, the way out for technicians is no longer to "change a position," but to reconstruct their own production structure—from passive participation in platforms to actively becoming an "individual node."

1. From Job Thinking to System Thinking

In the Web2 era, the value of technicians mainly depended on "positions": writing code, designing architecture, running projects. However, the arrival of AI has automated tasks, and the emergence of Web3 has made value distribution more open.

The new competitive logic is: it’s not about how many tasks you can complete, but how many systems you can build.

Systems can be:

• An automated development pipeline (AI + DevOps)

• A smart contract protocol (Web3 application layer)

• A knowledge and tool product (Notion templates, Agents, API services)

These systems do not rely on platforms but are self-circulating entities driven by individuals, assisted by AI, and underpinned by protocols.

This was precisely my starting point when building BlockETF and BlockLever at "Soluno Lab": to make each project an independently operable, asset-accumulating, and reusable system unit.

Technicians need to shift from "doing tasks" to "building machines," allowing systems to work for them.

2. Phase One: AI Productivity Upgrade

In any transformation route, the first step is always to master the AI tool stack. It determines whether you have the foundation for "hundredfold productivity."

• Text and cognitive layer: ChatGPT, Claude, Perplexity—used for thinking, analyzing, decision-making, and writing;

• Coding and development layer: Cursor, Claude Code, Codex—used for code generation, debugging, documentation, and testing;

• Creativity and expression layer: Midjourney, Runway, Figma AI, ElevenLabs—used for visual and multimodal creation.

My own work is almost a microcosm of this system. When building BlockETF and BlockLever, I use Claude Code daily to help me analyze and generate complex contract logic. For regular writing, I also use ChatGPT for copy editing. AI has not replaced me; rather, it has allowed me to focus more on architecture and creation.

Mastering these tools is not about showing off skills but about embedding AI into your personal workflow: writing requirements → generating code → automated testing → outputting documentation → publishing content. By achieving this, you are no longer an "executor" but an "AI orchestrator."

3. Phase Two: Web3 Technology and Assetization Thinking

Once you can efficiently produce with AI, the second step is to ensure that the output has ownership, revenue, and continuity. This is the problem that Web3 thinking aims to solve.

• Learning aspect: Master smart contracts (Solidity), EVM logic, wallet interactions, on-chain deployment;

• Product aspect: Understand token models, protocol mechanisms, oracles, and governance systems;

• Thinking aspect: Realize that "your code, models, and content" can all become an asset unit.

Technicians are no longer just developers but asset issuers, protocol designers, and node operators. AI enables you to create efficiently, while Web3 allows you to own and monetize. The combination of these two forms the prototype of a "personal sustainable system."

4. Phase Three: Individual Productization and Branding

When you can produce, secure ownership, and create cycles, you enter the third phase: individual productization. This means you no longer depend on a position but build your own "micro-ecosystem."

Typical paths include:

• Personal brand products: technical blogs, courses, consulting, SaaS tools;

• On-chain product projects: micro-protocols, NFT series, AI Agent-as-a-Service;

• Community economy experiments: one-person company DAOs, tokenized memberships, revenue-sharing models.

At this stage, competitiveness is not about how many technologies you master but whether you can distill your knowledge, algorithms, and experiences into a "reusable structure."

Individuals are nodes, and nodes are brands. When you have your own protocols, code libraries, product matrices, and user networks, you no longer need a "company" to define your value.

5. Establishing New "Certainty" Internally

In the Web2 era, certainty came from organizations; in the AI + Web3 era, certainty comes from the self-consistent individual system.

AI gives you a "leverage of productivity," while Web3 gives you a "leverage of value distribution." When the two combine, you gain the ability to survive, create, and accumulate in any environment.

This is the true meaning of moving from "positions" to "nodes":

You are no longer a part of the system but the creator of the system.

🧩 Summary

The wave of AI + Web3 will not eliminate everyone, but it will eliminate those who lack the ability for systematic self-upgrade. For technicians willing to learn, practice, and build, this era is, in fact, the best era.

"You don’t need to join a big company to change the world. You can use AI + Web3 to become a small company yourself."

IV. Path: Transformation Roadmap from 0 to 1

Understanding trends is one thing; completing a transformation is another. Transitioning from Web2 technical positions to the AI + Web3 era does not mean starting over but rather completing the reconstruction of skills and thinking through progressive iteration.

A realistic and feasible path is to advance through three phases: Tooling → Protocolization → Productization.

1. Phase One: Tooling—AI-Driven Productivity Reconstruction

Goal: Make AI a part of your workflow.

Key actions:

1. Use ChatGPT / Claude / Perplexity as a "cognitive assistant," involving it in thinking, structural design, and writing;

2. Integrate Cursor / Claude Code / Codex into your development environment, reconstructing your development process (requirements → code → testing → documentation);

3. I involve AI in my workflow almost every day, from automatically generating test scripts and updating documentation to assisting with code refactoring and deployment. For me, AI is no longer just a tool but part of the development system.

Measurement criteria:

When you can use AI tools to complete 80% of the work that originally required human collaboration, you have the prototype of an "AI-native individual."

2. Phase Two: Protocolization—Learning Web3 Structure and Value Logic

Goal: Understand and be able to build systems that can secure ownership, settle, and combine.

Key actions:

1. Learn smart contract languages like Solidity / Rust / Move;

2. Understand on-chain components: wallets (EVM / EIP standards), liquidity protocols (Uniswap / PancakeSwap), oracles (Chainlink / Pyth), indexing services (The Graph / SubQuery);

3. Experiment on-chain in the form of a minimum viable product (MVP), such as the BlockETF (on-chain index protocol) or BlockLever (leverage lending protocol) I built at Soluno Lab, starting from core functions to first validate contract logic and economic models;

4. Learn how to interact with the front end through Subgraph and API to achieve a complete DApp process.

Measurement criteria:

When you can independently complete an on-chain project and understand its economic incentive structure, you have the foundational capabilities of a "Web3-native Builder."

3. Phase Three: Productization—Building Your "Individual System"

Goal: Distill personal capabilities into reusable, tradable, and sustainable products.

Key actions:

1. Integrate your AI + Web3 experiments into reusable modules, such as open-source libraries, smart contract templates, educational content, and automation tools;

2. Use GitHub / Mirror / X (Twitter) and localized channels for dissemination and validation;

3. Build a "personal asset structure": project documentation, code repositories, protocol deployment records, content systems;

4. Attempt to create a revenue loop: courses, consulting, tool subscriptions, on-chain revenue sharing.

Measurement criteria:

When your system can continue to create value while you are offline, you have completed the transformation from "positions" to "nodes."

4. Key Mindset: Progressive Evolution, Not a One-Time Leap

Transformation is not a one-time event but a continuous evolutionary process. The real risk is not "not being able to learn," but "staying in the old paradigm."

You don’t have to master all new technologies at once, but you must keep yourself on a path of continuous iteration.

Treat every learning, experiment, and output as part of building your "individual system." As tools evolve, your structure will automatically upgrade.

5. From Skill Tree to Ecosystem Map

The traditional skill tree is vertical: from beginner → intermediate → advanced; while the skill map of AI + Web3 is networked: cognition, tools, protocols, content, and community are interconnected.

This means your learning path should also be multidimensional and parallel:

🧭 Summary

The transition from Web2 to AI + Web3 is not about escaping the old world but reconstructing your structure in the new world. AI gives you a "leverage of efficiency," Web3 gives you a "leverage of ownership," and productization gives you a "leverage of compound interest."

The real way out is not to find a new job but to build a personal system that can self-evolve.

V. Conclusion: From "Insecurity" to "New Certainty"

Looking back over the past few years, we have witnessed tremendous changes in the entire technical world. AI has brought a leap in efficiency, Web3 has reshaped the way value is distributed, and the order of Web2—positions, platforms, companies—is losing its certainty.

This sense of insecurity is something every technician can feel. You may be asking:

• "Can I still keep up with the times?"

• "Will what I do still be needed?"

But the truth is, real certainty has never existed in the external world; it has always been hidden in whether you possess the ability to create independently and evolve yourself.

1. Certainty Comes from Structure, Not Position

In the era of AI + Web3, an individual's structure is determining their certainty. AI allows you to accomplish tasks that previously required a team; Web3 enables you to secure ownership, share profits, and accumulate long-term assets. When these two capabilities converge in one person, you are no longer dependent on platforms but become an individual node with a complete economic cycle.

This is not idealism but a realistic trend. More and more people are using AI and on-chain tools to build their own micro-systems: some are creating products, some are producing content, and some are developing protocols. Their commonality is:

No longer seeking certainty externally, but using systems to establish their own.

2. The Greatest Opportunity for Technicians is to Redefine Themselves

From Web2 to AI + Web3, the core of this transformation is not about "changing tracks," but about "reconstructing oneself":

• Transitioning from job roles to system builders;

• Shifting from executing tasks to creating mechanisms;

• Moving from dependence on organizations to becoming independent nodes.

This transformation is precisely the path I have been practicing at "Soluno Lab." BlockETF and BlockLever are not the end of products but iterations of a systematic individual. They have shown me that one person can also build complex systems, drive projects online, and form a compounding ecosystem. This is our "new certainty."

3. The Future Belongs to Those with Structure

The future will no longer belong to the most diligent but to those who can build systems. AI will continuously amplify your leverage, Web3 will solidify your achievements, and your task is to constantly upgrade this "personal system": making it more automated, more open, and more sustainable.

While others are still worried about "job security," you are already using your own system to create a sense of security.

Security no longer comes from employers, markets, or platforms, but from your ability to self-evolve.

AI + Web3 is not a torrent but a tool. True certainty comes from whether you dare to use them to build your own world.

🧭 Postscript

Writing this content is not about depicting a future vision but recording a reality that is happening. AI has already entered our daily lives, and the infrastructure of Web3 is gradually improving.

As the boundaries of the era are redefined, the best response for technicians is not fear but creation.

We start from insecurity and ultimately find ourselves within a structure of certainty.

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