I. Current Situation: Anxiety and Crisis among Web2 Tech Professionals
I've noticed an increasing number of people adding me as a friend and asking me how to transition to Web3.These include recent graduates, engineers with three to five years of experience, and middle-aged tech professionals like myself who have been working for over a decade and are starting to feel uneasy about their career prospects.
Their questions are almost all the same: "Is there still a chance with Web3?" "Is it too late for me to learn now?" "The most realistic question is—how can a newcomer find a job in Web3?" This anxiety is not accidental. For the past decade, Web2 built a "world of certainty" for tech professionals—stable jobs, predictable career paths, and platform advantages. But after 2024, this certainty is rapidly collapsing. A structural turning point for the internet industry has arrived, and the wave of AI is making this turning point even more irreversible. 1. The End of the Technological Dividend The growth of the global internet industry is slowing down. In the first half of 2025, global technology companies announced nearly 94,000 layoffs, a three-year high (Observer, July 2025). This is no longer a cyclical adjustment, but a fundamental change in the industry's logic. Microsoft's actions are particularly noteworthy: In July 2025, Microsoft announced layoffs of approximately 9,000 employees, representing about 4% of its global workforce; and in May, it had just completed another round of layoffs affecting over 6,000 people. Simultaneously, the company explicitly required employees to "use AI tools" and incorporated this into its performance evaluation system. This means that even the world's most stable and resource-rich tech giants are proactively "using AI to optimize their workforce structure." The "sense of job security in technical positions" formed under the Web2 model is being systematically eroded. 2. The Substitution Effect of AI The rise of AI is not merely an update of efficiency tools, but a redefinition of "technical work itself." Stack Overflow's 2025 Global Developer Survey revealed that 52% of programmers use AI tools daily (such as Copilot, ChatGPT, and Claude), with 18% stating that AI has significantly changed their job responsibilities. In other words, AI has become part of the development process, not an option. A product that previously required 10 people to collaborate on can now be delivered by 3 people plus AI. The focus of competition for positions is shifting from "who can write better code" to "who can collaborate more efficiently with AI." This represents a silent "middle-level collapse" for traditional Web2 technologists: AI-native engineers are rising in prominence, while purely execution-oriented roles are gradually being marginalized. 3. The Double-Edged Sword of Platform Dependence Web2's prosperity is built on a "platform ecosystem." Tech professionals rely on systems like the App Store, Google, WeChat, and TikTok, but this dependence also means a lack of autonomy and asset value in their personal output. SensorTower data shows that Apple's App Store policy changes at the end of 2024 led to a sharp drop in revenue for approximately 12% of independent developers globally, instantly cutting off the main revenue streams for many small and medium-sized teams. This risk is prevalent in the Web2 ecosystem: Changes in platform rules can directly impact an individual's livelihood; creators' data and works belong to the platform; account or service bans can mean losing everything. In this structure, no matter how hard an individual tries, it's difficult to accumulate transferable and sustainable assets. 4. Restructuring of Skills and Income Structures LinkedIn's "Future of Skills 2025" report indicates that AI, blockchain, and data analytics are the fastest-growing skill areas, while the growth rate of traditional web front-end skills has dropped to 0.3%. Meanwhile, according to Levels.fyi data at the end of 2024, the average salary of FAANG engineers decreased by approximately 8% year-on-year, while AI/LM-related positions bucked the trend, increasing by over 20%. This means that the technological dividend is shifting from "platform development" to a new field of "intelligent systems + decentralized technology." Skills transfer is no longer a "nice-to-have," but a "prerequisite for survival." 5. The Roots of Security Are Shaken These data piece together the following facts: Web2 organizational stability is no longer present; Job skill boundaries are blurred by AI; Income and career development paths are detached from platform logic. More and more engineers, designers, and product managers 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 "company and platform" to "individual's self-evolutionary ability." This is the core logic behind "Web2 is no longer secure": Certainty has migrated from external organizations to individual structures. The next generation of technologists must rebuild their own certainty at the intersection of AI and Web3. II. Inflection Point: The Convergence of AI and Web3 If the previous 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 Overlapping Point of Technological Cycles The emergence of AI and Web3 is not an isolated event, but rather the intersection of two exponential curves. AI Curve: Generative intelligence, represented by LLM (Large Language Model), is achieving "cognitive automation." Web3 Curve: Decentralized infrastructure, represented by blockchain, is achieving "value automation." When these two curves intersect, they form a new interface for the new era: Intelligent individuals can possess identity, assets, and the ability to act on the blockchain. McKinsey estimates in its report, *The Economic Potential of Generative AI* (2025), that AI is expected to contribute between $4 trillion and $7 trillion annually to the global economy; while according to Electric Capital's 2025 Developer Report, Web3 still has over 23,000 monthly active developers continuously building upon it. This indicates that although the two ecosystems are moving at different paces, both are entering a period of practical application and integration. 2. AI: From Tool to Agent 2023–2025 is a crucial stage for the “personalization” of AI. From the initial ChatGPT and Claude to today's Cursor, Claude Code, and Codex, which focus on the coding/Agent model, we have witnessed the evolution of AI from an “auxiliary tool” to an “autonomous intelligent agent.” AI is no longer just an assistant that helps you write code, but a collaborator capable of autonomous decision-making and task execution: It can automatically write and deploy contracts; it can interact with on-chain protocols to execute transactions and manage assets; and it can even learn and optimize itself based on the profit model. This evolution has given rise to a new concept—AI-native Builder: Individuals expand productivity through AI and solidify results through on-chain protocols. This means that future "developers" will no longer be individual engineers, but a hybrid of "human + intelligent agent." 3. Web3: From Speculative Narrative to Structural Infrastructure Alongside AI, Web3 is undergoing a transformation from a speculative narrative to infrastructure. In the past, people talked more about "coin prices," but now the focus is shifting to "protocol layer capabilities"—the underlying infrastructure that can support the digital economy in the long term. Currently, the industry's real focus is concentrated in several directions: These trends collectively demonstrate that Web3 is no longer just a stage for financial innovation, but is evolving into the next generation of the Internet's Trust Layer. A foundation that allows AI, individuals, and the real economy to collaborate freely under a trust mechanism. 4. What happens when AI merges with Web3? We are seeing a completely new system form: AI generation + Web3 settlement + individual ownership. This structure brings about a leap in three levels: Simply put, AI makes "production" more efficient, and Web3 makes "results" more sustainable. Together, they drive a trend—the emergence of the individual economy. AI can give an individual a hundred times the productivity; Web3 allows this productivity to be registered, monetized, and reused. This is precisely the underlying logic behind the rise of the "one-person lab" and even the "one-person company" model. 5. Structural Opportunities: From Platform Dividends to Protocol Dividends Historically, every technological cycle has been accompanied by a rewriting of production relations. From PCs to the internet, from mobile to the platform economy, the center of the dividend has constantly shifted. This time, the dividend is shifting from "platform dividends" to "protocol dividends": Platform dividends: relying on giants and monetizing traffic; Protocol dividends: building open systems and participating in value distribution. In this process, individuals who understand how to use AI to build products and use Web3 to establish ownership of achievements will become the next generation of "micro-production nodes." Whether developers, designers, or independent creators, they all have the opportunity to find new certainty within this framework. 6. The Proposition of the New Era When we say "AI + Web3 is an inflection point," it is not an abstract slogan, but a real structural trend: The tools of production have undergone fundamental changes (AI); The value system has undergone fundamental changes (Web3); And the role of technologists is shifting from "passive execution" to "active creation." This is not a skill upgrade, but a paradigm shift. This is the inflection point represented by the "AI + Web3 convergence": AI redefines productivity, and Web3 redefines ownership. When productivity and ownership overlap at the individual level, a new era for technologists begins. III. The Way Out: From Technical Roles to Individual Nodes When the technological dividend fades and platform certainty collapses, new problems naturally arise: "How should I transition?" In the era of AI and Web3 convergence, the way out for tech professionals is no longer "changing roles," but rather reconstructing their production structure—from passively participating in platforms to actively becoming an "individual node." 1. From Job-Specific Thinking to Systems Thinking In the Web2 era, the value of tech professionals was primarily tied to their "jobs": writing code, designing architectures, and running projects. However, the advent 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. The system can be: An automated development pipeline (AI + DevOps) A smart contract protocol (Web3 application layer) A knowledge and tool product (Notion templates, Agent, API services) These systems do not depend on a platform, but are self-sustaining entities driven by individuals, assisted by AI, and underpinned by protocols. This is 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. Technologists need to shift from "doing tasks" to "building machines," letting systems work for them. 2. Phase One: AI Productivity Upgrade In any transformation path, the first step is always mastering the AI toolchain. It determines whether you have the foundation for "100x productivity".
Text and Cognition Layer: ChatGPT, Claude, Perplexity—for thinking, analysis, decision-making, and writing;
Coding and Development Layer: Cursor, Claude Code, Codex—for code generation, debugging, documentation, and testing;
Creativity and Expression Layer: Midjourney, Runway, Figma AI, ElevenLabs—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 analyze and generate complex contract logic. For my regular writing, I use ChatGPT for copywriting polishing. AI hasn't replaced me; instead, it allows me to focus more on architecture and creation. Mastering these tools isn't about showing off skills, but about embedding AI into your personal workflow: Write requirements → Generate code → Automated testing → Output documentation → Publish content. By doing this, you're no longer an "executor," but an "AI orchestrator." 3. Second Stage: Web3 Technology and Asset Management Mindset 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 Level: Master smart contracts (Solidity), EVM logic, wallet interaction, and on-chain deployment; Product Level: Understand token models, protocol mechanisms, oracles, and governance systems; Mindset Level: Realize that "your code, model, and content" can all become an "Asset Unit". Tech professionals 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. The Third Stage: Individual Productization and Branding When you can produce, establish ownership, and circulate, you enter the third stage: Individual Productization. This means you no longer depend on a job position, but instead 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 companies DAO, tokenized memberships, revenue sharing models. At this point, competitiveness doesn't lie in how much technology you possess, but rather in: Whether you can distill your knowledge, algorithms, and experience into a "reusable structure." The individual is the node, and the node is the brand. When you have your own protocol, codebase, product matrix, and user network, you no longer need a "company" to define your value. 5. Establishing a New "Certainty" Internally In the Web2 era, certainty came from organizations; in the AI + Web3 era, certainty comes from structurally self-consistent individual systems. AI gives you "leverage of productivity," while Web3 gives you "leverage of value distribution." When the two are combined, you possess the ability to survive, create, and accumulate in any environment. This is the true meaning of moving from a "position" to a "node": You are no longer part of the system, but a creator of the system. In summary, the AI + Web3 wave will not eliminate everyone, but it will eliminate those who lack the ability to systematically upgrade themselves. For technologists willing to learn, practice, and build, this era is actually 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 itself." IV. Path: A Transformation Roadmap from 0 to 1 Understanding trends is one thing, completing the transformation is another. Moving from a Web2 technical role to the AI + Web3 era doesn't mean starting over completely, but rather reconstructing skills and mindset through gradual iteration. A realistic and feasible path is to proceed in three stages: Tooling → Protocolization → Productization. 1. Stage One: Tooling – AI-Driven Productivity Restructuring Goal: Make AI a part of your workflow. Key Actions: Use ChatGPT / Claude / Perplexity as a "cognitive assistant," involving it in thinking, structural design, and writing; Integrate Cursor / Claude Code / Codex into your development environment to refactor your development process (requirements → code → testing → documentation); I involve AI in my workflow almost daily, from automatically generating test scripts and updating documentation to assisting in code refactoring and deployment. For me, AI is no longer just a tool, but part of the R&D system.
Measurement Criteria:
When you can use AI tools to complete 80% of the work that originally required human collaboration, you have the rudiments of an "AI-native individual".
2. Phase Two: Protocolization—Learning Web3 Structure and Value Logic
Goal: Understand and be able to build systems that are verifiable, settlementable, and composable.
Key Actions: Learn smart contract languages such as Solidity, Rust, and Move; Understand on-chain components: wallets (EVM/EIP standards), liquidity protocols (Uniswap/PancakeSwap), oracles (Chainlink/Pyth), and indexing services (The Graph/SubQuery); Experiment on-chain with a minimum viable product (MVP), such as BlockETF, which I built in Soluno Lab. Like the on-chain index protocol or BlockLever (leveraged lending protocol), start with the core functionality and first verify the contract logic and economic model; learn how to interact with the front end through Subgraph, API, and implement the complete DApp process. Measurement criteria: When you can independently complete an on-chain project and understand its economic incentive structure, you possess the basic capabilities of a "Web3-native Builder".
3. Phase Three: Productization - Building Your Own "Individual System"
Goal: To transform personal capabilities into reusable, tradable, and sustainable products.
Key Actions: Integrate your AI + Web3 experiments into reusable modules, such as open-source libraries, smart contract templates, educational content, and automation tools; Disseminate and validate your work using GitHub / Mirror / X (Twitter) and localized channels; Build a "personal asset structure": project documentation, code repositories, protocol deployment records, and a content system; Attempt to create a closed-loop revenue stream: courses, consulting, tool subscriptions, and on-chain revenue sharing.
Measurement Criteria:
When your system can continuously create value even when you are offline, you have completed the transformation from a "position" to a "node".
4. Key Mindset: Gradual Evolution, Not a One-Leap
Transformation is not a one-time event, but a continuous evolutionary process. The real risk is not "not being able to learn," but "remaining stuck in the old paradigm."
You don't need to master all new technologies at once, but you must keep yourself on a continuous iteration track.
Treat every learning experience, experiment, and output as part of building an "individual system," and your structure will automatically upgrade as tools evolve. 5. From Skill Trees to Ecosystem Graphs Traditional skill trees are vertical: from beginner → intermediate → advanced; while the AI + Web3 skill graph is network-like: cognition, tools, protocols, content, and community are interconnected. This means your learning path should also be multi-dimensional and parallel: The transition from Web2 to AI + Web3 is not about escaping the old world, but about reconstructing your structure in the new world. AI gives you "efficiency leverage," Web3 gives you "ownership leverage," and productization gives you "compound interest leverage." The real solution isn't finding a new job, but building a self-evolving personal system. V. Conclusion: From "Insecurity" to "New Certainty" Looking back over the past few years, we've witnessed a massive transformation in the entire technology world. AI has brought about a leap in efficiency, Web3 has reshaped the way value is distributed, while the Web2 order—jobs, platforms, companies—is losing its certainty. This sense of insecurity is felt by almost every technologist. You might be asking: "Am I still keeping up with the times?" "Will what I do still be needed?" But the truth is, true certainty never exists in the external world; it always lies within you—whether you possess the ability to create independently and evolve on your own. 1. Certainty comes from structure, not position. In the era of AI + Web3, a person's structure is determining their certainty. AI allows you to accomplish tasks that previously required a team; Web3 enables you to establish ownership, share profits, and accumulate long-term assets. When these two capabilities converge in one person, you no longer depend on a platform, but become an individual node with a complete economic cycle. This is not idealism, but a real trend. More and more people are using AI and on-chain tools to build their own micro-systems: some are creating products, some are creating content, and some are creating protocols. Their common thread is: they no longer seek certainty externally, but instead use their systems to create certainty for themselves. 2. The biggest opportunity for tech professionals is to redefine themselves. From Web2 to AI + Web3, the core of this transformation is not "changing tracks," but "reconstructing oneself": From job roles to system builders; From executing tasks to creating mechanisms; From being dependent on organizations to becoming independent nodes. This transformation is precisely the path I've been practicing at "Soluno Lab". BlockETF and BlockLever are not the end point of a product, but rather iterative processes of a systematic individual. They show me that one person can build complex systems, launch projects, and create a compounding ecosystem. This is our "new certainty". 3. The Future Belongs to Structured People. The future no longer belongs to the most hardworking, but to those who can build systems. AI will continue to amplify your leverage, Web3 will continue to solidify your achievements, and your task is to continuously upgrade this "personal system": making it more automated, more open, and more sustainable. While others are still worrying about "job security," you are already creating security with your own system. Security no longer comes from employers, the market, or platforms, but from your ability to evolve yourself. 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 is not about depicting a future vision, but about recording a reality that is unfolding. AI has entered our daily lives, and the infrastructure of Web3 is gradually improving. When the boundaries of the times are redefined, the best way for technologists to respond is not through fear, but through creation. We start from insecurity and ultimately find ourselves within a structure of certainty.
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