Under the trend of AI-driven software, the 5 hard standards for the next generation of high-value software
--- Understanding these standards is essential to anticipate the form of next-generation applications and the future of Web3 applications
1️⃣ AI is the “Execution主体,” not just an “辅助工具”
Old software:
User clicks → System computes → User confirms
New software:
AI makes decisions → AI executes → Human audits
AI is not just helping you write copy, but:
Automatically running processes
Automatically calling resources
Automatically handling exceptions
2️⃣ Software directly binds to “results,” not “functions”
The next generation of software sells not:
“What I can help you do”
But:
“I am responsible for the results”
For example:
Automatically completing a compliance process
Automatically achieving a business goal
Automatically controlling risks within thresholds
👉 Responsibility binding = Moat
3️⃣ Software is a “long-term running system,” not a one-time interaction
Models are applications that solve:
Single issues
Immediate responses
The next generation of software addresses:
Continuous states
Long-term strategic play
Multi-entity collaboration
As long as the system requires:
State memory
Historical constraints
Traceability of responsibility
👉 Models are not enough; a software system is necessary.
4️⃣ Software deeply embeds “irreversible constraints” from the real world
For example:
Money (settlement, risk control)
Legal (contracts, compliance)
Physical world (energy, logistics, manufacturing)
The closer the software is to real-world friction, the less likely it is to be “swallowed by models as applications.”
5️⃣ AI actually increases system migration costs
This is the most counterintuitive point:
The deeper AI participates, the harder it is to replace the system.
Because:
AI learns your data
Your data is embedded in the system
The system is embedded in your organizational processes
👉 AI = Adhesive, not a destroyer (from the system layer perspective)
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Under the trend of AI-driven software, the 5 hard standards for the next generation of high-value software
--- Understanding these standards is essential to anticipate the form of next-generation applications and the future of Web3 applications
1️⃣ AI is the “Execution主体,” not just an “辅助工具”
Old software:
User clicks → System computes → User confirms
New software:
AI makes decisions → AI executes → Human audits
AI is not just helping you write copy, but:
Automatically running processes
Automatically calling resources
Automatically handling exceptions
2️⃣ Software directly binds to “results,” not “functions”
The next generation of software sells not:
“What I can help you do”
But:
“I am responsible for the results”
For example:
Automatically completing a compliance process
Automatically achieving a business goal
Automatically controlling risks within thresholds
👉 Responsibility binding = Moat
3️⃣ Software is a “long-term running system,” not a one-time interaction
Models are applications that solve:
Single issues
Immediate responses
The next generation of software addresses:
Continuous states
Long-term strategic play
Multi-entity collaboration
As long as the system requires:
State memory
Historical constraints
Traceability of responsibility
👉 Models are not enough; a software system is necessary.
4️⃣ Software deeply embeds “irreversible constraints” from the real world
For example:
Money (settlement, risk control)
Legal (contracts, compliance)
Physical world (energy, logistics, manufacturing)
The closer the software is to real-world friction, the less likely it is to be “swallowed by models as applications.”
5️⃣ AI actually increases system migration costs
This is the most counterintuitive point:
The deeper AI participates, the harder it is to replace the system.
Because:
AI learns your data
Your data is embedded in the system
The system is embedded in your organizational processes
👉 AI = Adhesive, not a destroyer (from the system layer perspective)