Beware of "AI-augmented public chains"; why VANRY makes me rethink the logic of infrastructure
In the past year, there has been a significant change in the narrative of public chains: almost all projects seeking breakthroughs have included AI in their roadmaps. This combination of "AI + blockchain" is repeating the script of the past "DeFi standard". However, upon deeper observation, I am gradually taking a cautious stance on this model—not because I deny the importance of AI, but precisely because AI will become the core user of future infrastructure, and the design flaws of those "AI-augmented public chains" are becoming apparent.
1. The essential difference between AI-first and AI-added
Most public chains adopt the model of 'having a chain first → adding AI modules → announcing support for AI'. This design may be sufficient for human users, but when AI becomes a continuously operating, autonomously deciding system participant, problems will emerge:
- Unpredictability: AI cannot adapt to fee fluctuations and traditional on-chain mechanisms like transaction ordering games
- System adaptability: The incentive models and governance structures of existing public chains are designed for humans
- Cost controllability: The cost model of temporary decisions cannot be embedded in AI's long-term planning
II. Vanar's reverse engineering thinking
The Vanar team is not in a hurry to use AI as a marketing label, but focuses on three underlying elements that traditional public chains have overlooked:
1. Deterministic cost model
Use fixed dollar-denominated transaction costs, which is crucial for AI:
- Precise cost calculation before executing tasks
- Eliminate the interference of fee fluctuations on long-term operations
- The VANRY token serves as a 'cost-behavior' connector here
2. Machine-friendly rules
Choose 'first come, first served' rather than bidding mechanisms for transaction ordering:
- Compress the space for human games
- Ensure behavior reproducibility
- Reduce the decision-making complexity of AI systems
3. Long-term stability design
The mainnet Beta launch achieved:
- The first hour attracted $250 million in stablecoin inflow
- The on-chain stablecoin supply surpassed $7 billion in 24 hours
- The staking ratio is maintained above 40%
III. The crossroads of infrastructure evolution
The design of most current public chains is essentially 'human emotion-friendly', while a true AI-first infrastructure requires:
- System-level adaptation: A comprehensive reconstruction from consensus mechanisms to economic models
- Non-human user presupposition: Reserve interfaces for continuously operating agents
- Value scale innovation: VANRY's long-term potential as a stable value anchor
This design is not popular in the current market because it cannot create short-term emotional premiums. But if we believe that AI will evolve from a tool to the primary user of infrastructure, we must acknowledge: those functions designed for human speculative behavior (such as gas fee fluctuations and transaction sniping) are all noise that needs to be eliminated for AI systems.
IV. Filtering criteria for future public chains
When assessing new public chains, I will focus on:
1. Whether non-human users' existence is presupposed
2. Whether the economic model supports long-term predictability
3. Whether the core mechanism considers AI's decision-making logic
The Vanar team chose a more difficult path: instead of wrapping existing structures with AI concepts, they designed the infrastructure in reverse from the needs of AI systems. This way of thinking, which assumes a stricter future, may be the key to breaking the current public chain dilemma.
Of course, the success of AI-first infrastructure requires time to verify. But at least from my perspective, Vanar offers a development paradigm that differs from 'concept hijacking'. Regarding 'what AI-ready public chains really need', I will continue to explore in subsequent articles. This article only represents my long-term observations based on publicly available information and does not constitute any investment advice.
