The post has been translated automatically. Original language: English
With the rise of vibecoding and AI-generated software, we are entering an interesting shift.
Before, one of the main problems was:
How do we write the code?
Now, an equally important question is:
Can we trust the code that was generated?
⚠️ What is changing?
In Web3, we already understand the importance of audits:
— smart contract audits are standard practice— security issues can directly lead to financial losses— incorrect logic can affect users, assets, and reputation
But this problem is no longer limited to smart contracts.
AI is now generating significant parts of modern applications.
And the faster code becomes to produce, the more important it becomes to verify it.
🚨 The new problem: code is written quickly, but…
AI can help developers:
— build prototypes in hours— launch MVPs extremely quickly— implement complex logic with a small team— connect APIs and external services— generate large parts of an application
But there is a catch.
The fact that code works in one scenario does not mean that the system is reliable in production.
What happens under load?
What happens when an external API fails?
What happens in an unexpected state?
What happens after several updates?
What happens when blockchain transactions fail or arrive later than expected?
These are the questions that become increasingly important.
🔍 Auditing is becoming broader
Modern application auditing is no longer only about smart contracts.
It can include:
• backend architecture and business logic• security and access control• database and transaction logic• frontend state and edge cases• API and third-party integrations• Telegram and Web3 integrations• blockchain transaction flows• smart contracts• AI-generated code
The goal is not simply to find syntax errors.
The goal is to understand how the system behaves when things don't go according to the happy path.
💡 The important shift
Before:
“The code is written, so it works.”
Now:
“The code is written. Let's verify that it actually works as intended.”
AI can generate code.
But AI does not take responsibility for what happens when that code manages money, users, permissions, transactions, or production infrastructure.
🧩 Why this matters
The barrier to building software is becoming lower.
At the same time, the amount of software being produced is increasing dramatically.
That means the ability to review, understand, test and audit generated code becomes increasingly valuable.
I believe we will see a growing market around:
👉 AI-code auditing and vibecoding project reviews.
Not because AI cannot write good code.
But because even good-looking code can contain assumptions, edge cases and architectural problems that are difficult to see without systematic review.
🔐 And this is especially important in Web3.
When smart contracts are involved, mistakes can become irreversible.
I work with blockchain applications, transaction flows, wallets, APIs and smart contracts, and I’m interested not only in how the code is written, but in how the entire system behaves around it.
If you are building a Web3 product and need another pair of eyes on your smart contracts or blockchain-related code, I can help with a technical review and audit-oriented analysis.
I can also review the surrounding application logic — backend, APIs, transaction flows and integrations — where smart-contract security often depends on what happens outside the contract itself.
🚀 The future is not just about generating code faster.
It is about being able to trust what we generate.
Code is becoming easier to write.
Verification is becoming more important.
With the rise of vibecoding and AI-generated software, we are entering an interesting shift.
Before, one of the main problems was:
How do we write the code?
Now, an equally important question is:
Can we trust the code that was generated?
⚠️ What is changing?
In Web3, we already understand the importance of audits:
— smart contract audits are standard practice— security issues can directly lead to financial losses— incorrect logic can affect users, assets, and reputation
But this problem is no longer limited to smart contracts.
AI is now generating significant parts of modern applications.
And the faster code becomes to produce, the more important it becomes to verify it.
🚨 The new problem: code is written quickly, but…
AI can help developers:
— build prototypes in hours— launch MVPs extremely quickly— implement complex logic with a small team— connect APIs and external services— generate large parts of an application
But there is a catch.
The fact that code works in one scenario does not mean that the system is reliable in production.
What happens under load?
What happens when an external API fails?
What happens in an unexpected state?
What happens after several updates?
What happens when blockchain transactions fail or arrive later than expected?
These are the questions that become increasingly important.
🔍 Auditing is becoming broader
Modern application auditing is no longer only about smart contracts.
It can include:
• backend architecture and business logic• security and access control• database and transaction logic• frontend state and edge cases• API and third-party integrations• Telegram and Web3 integrations• blockchain transaction flows• smart contracts• AI-generated code
The goal is not simply to find syntax errors.
The goal is to understand how the system behaves when things don't go according to the happy path.
💡 The important shift
Before:
“The code is written, so it works.”
Now:
“The code is written. Let's verify that it actually works as intended.”
AI can generate code.
But AI does not take responsibility for what happens when that code manages money, users, permissions, transactions, or production infrastructure.
🧩 Why this matters
The barrier to building software is becoming lower.
At the same time, the amount of software being produced is increasing dramatically.
That means the ability to review, understand, test and audit generated code becomes increasingly valuable.
I believe we will see a growing market around:
👉 AI-code auditing and vibecoding project reviews.
Not because AI cannot write good code.
But because even good-looking code can contain assumptions, edge cases and architectural problems that are difficult to see without systematic review.
🔐 And this is especially important in Web3.
When smart contracts are involved, mistakes can become irreversible.
I work with blockchain applications, transaction flows, wallets, APIs and smart contracts, and I’m interested not only in how the code is written, but in how the entire system behaves around it.
If you are building a Web3 product and need another pair of eyes on your smart contracts or blockchain-related code, I can help with a technical review and audit-oriented analysis.
I can also review the surrounding application logic — backend, APIs, transaction flows and integrations — where smart-contract security often depends on what happens outside the contract itself.
🚀 The future is not just about generating code faster.
It is about being able to trust what we generate.
Code is becoming easier to write.
Verification is becoming more important.
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